From 7e461a18d9f6928132afec6f48ce968b3e989ba6 Mon Sep 17 00:00:00 2001
From: Kaiqi Dong <kaiqi@kth.se>
Date: Mon, 3 Dec 2018 17:43:52 +0100
Subject: [PATCH 01/48] remove \n from docstring
---
pandas/core/arrays/datetimes.py | 26 +++++++++++++-------------
pandas/core/arrays/timedeltas.py | 16 ++++++++--------
2 files changed, 21 insertions(+), 21 deletions(-)
diff --git a/pandas/core/arrays/datetimes.py b/pandas/core/arrays/datetimes.py
index cfe3afcf3730a..b3df505d56d78 100644
--- a/pandas/core/arrays/datetimes.py
+++ b/pandas/core/arrays/datetimes.py
@@ -82,7 +82,7 @@ def f(self):
return result
f.__name__ = name
- f.__doc__ = docstring
+ f.__doc__ = "\n{}\n".format(docstring)
return property(f)
@@ -1072,19 +1072,19 @@ def date(self):
return tslib.ints_to_pydatetime(timestamps, box="date")
- year = _field_accessor('year', 'Y', "\n The year of the datetime\n")
+ year = _field_accessor('year', 'Y', "The year of the datetime")
month = _field_accessor('month', 'M',
- "\n The month as January=1, December=12 \n")
- day = _field_accessor('day', 'D', "\nThe days of the datetime\n")
- hour = _field_accessor('hour', 'h', "\nThe hours of the datetime\n")
- minute = _field_accessor('minute', 'm', "\nThe minutes of the datetime\n")
- second = _field_accessor('second', 's', "\nThe seconds of the datetime\n")
+ "The month as January=1, December=12")
+ day = _field_accessor('day', 'D', "The days of the datetime")
+ hour = _field_accessor('hour', 'h', "The hours of the datetime")
+ minute = _field_accessor('minute', 'm', "The minutes of the datetime")
+ second = _field_accessor('second', 's', "The seconds of the datetime")
microsecond = _field_accessor('microsecond', 'us',
- "\nThe microseconds of the datetime\n")
+ "The microseconds of the datetime")
nanosecond = _field_accessor('nanosecond', 'ns',
- "\nThe nanoseconds of the datetime\n")
+ "The nanoseconds of the datetime")
weekofyear = _field_accessor('weekofyear', 'woy',
- "\nThe week ordinal of the year\n")
+ "The week ordinal of the year")
week = weekofyear
_dayofweek_doc = """
The day of the week with Monday=0, Sunday=6.
@@ -1129,12 +1129,12 @@ def date(self):
"The name of day in a week (ex: Friday)\n\n.. deprecated:: 0.23.0")
dayofyear = _field_accessor('dayofyear', 'doy',
- "\nThe ordinal day of the year\n")
- quarter = _field_accessor('quarter', 'q', "\nThe quarter of the date\n")
+ "The ordinal day of the year")
+ quarter = _field_accessor('quarter', 'q', "The quarter of the date")
days_in_month = _field_accessor(
'days_in_month',
'dim',
- "\nThe number of days in the month\n")
+ "The number of days in the month")
daysinmonth = days_in_month
_is_month_doc = """
Indicates whether the date is the {first_or_last} day of the month.
diff --git a/pandas/core/arrays/timedeltas.py b/pandas/core/arrays/timedeltas.py
index 830283d31a929..4afc9f5483c2a 100644
--- a/pandas/core/arrays/timedeltas.py
+++ b/pandas/core/arrays/timedeltas.py
@@ -59,7 +59,7 @@ def f(self):
return result
f.__name__ = name
- f.__doc__ = docstring
+ f.__doc__ = "\n{}\n".format(docstring)
return property(f)
@@ -684,16 +684,16 @@ def to_pytimedelta(self):
return tslibs.ints_to_pytimedelta(self.asi8)
days = _field_accessor("days", "days",
- "\nNumber of days for each element.\n")
+ "Number of days for each element.")
seconds = _field_accessor("seconds", "seconds",
- "\nNumber of seconds (>= 0 and less than 1 day) "
- "for each element.\n")
+ "Number of seconds (>= 0 and less than 1 day) "
+ "for each element.")
microseconds = _field_accessor("microseconds", "microseconds",
- "\nNumber of microseconds (>= 0 and less "
- "than 1 second) for each element.\n")
+ "Number of microseconds (>= 0 and less "
+ "than 1 second) for each element.")
nanoseconds = _field_accessor("nanoseconds", "nanoseconds",
- "\nNumber of nanoseconds (>= 0 and less "
- "than 1 microsecond) for each element.\n")
+ "Number of nanoseconds (>= 0 and less "
+ "than 1 microsecond) for each element.")
@property
def components(self):
From db4440d78ec44aaccd46efb7e8f857401e535e42 Mon Sep 17 00:00:00 2001
From: Kaiqi Dong <kaiqi@kth.se>
Date: Tue, 22 Jan 2019 00:23:18 +0100
Subject: [PATCH 02/48] add sym option for logx logy loglog and tests
---
pandas/plotting/_core.py | 14 ++++++++++----
pandas/tests/plotting/test_frame.py | 6 ++++++
2 files changed, 16 insertions(+), 4 deletions(-)
diff --git a/pandas/plotting/_core.py b/pandas/plotting/_core.py
index 3ba06c0638317..cd5140d57b8d1 100644
--- a/pandas/plotting/_core.py
+++ b/pandas/plotting/_core.py
@@ -83,9 +83,9 @@ def _kind(self):
_default_rot = 0
orientation = None
_pop_attributes = ['label', 'style', 'logy', 'logx', 'loglog',
- 'mark_right', 'stacked']
+ 'mark_right', 'stacked', 'sym']
_attr_defaults = {'logy': False, 'logx': False, 'loglog': False,
- 'mark_right': True, 'stacked': False}
+ 'mark_right': True, 'stacked': False, 'sym': False}
def __init__(self, data, kind=None, by=None, subplots=False, sharex=None,
sharey=False, use_index=True,
@@ -310,9 +310,15 @@ def _setup_subplots(self):
axes = _flatten(axes)
if self.logx or self.loglog:
- [a.set_xscale('log') for a in axes]
+ if self.sym:
+ [a.set_xscale('symlog') for a in axes]
+ else:
+ [a.set_xscale('log') for a in axes]
if self.logy or self.loglog:
- [a.set_yscale('log') for a in axes]
+ if self.sym:
+ [a.set_yscale('symlog') for a in axes]
+ else:
+ [a.set_yscale('log') for a in axes]
self.fig = fig
self.axes = axes
diff --git a/pandas/tests/plotting/test_frame.py b/pandas/tests/plotting/test_frame.py
index 0e7672f4e2f9d..50574b5392557 100644
--- a/pandas/tests/plotting/test_frame.py
+++ b/pandas/tests/plotting/test_frame.py
@@ -233,12 +233,18 @@ def test_logscales(self):
df = DataFrame({'a': np.arange(100)}, index=np.arange(100))
ax = df.plot(logy=True)
self._check_ax_scales(ax, yaxis='log')
+ ax = df.plot(logy=True, sym=True)
+ self._check_ax_scales(ax, yaxis='symlog')
ax = df.plot(logx=True)
self._check_ax_scales(ax, xaxis='log')
+ ax = df.plot(logx=True, sym=True)
+ self._check_ax_scales(ax, xaxis='symlog')
ax = df.plot(loglog=True)
self._check_ax_scales(ax, xaxis='log', yaxis='log')
+ ax = df.plot(loglog=True, sym=True)
+ self._check_ax_scales(ax, xaxis='symlog', yaxis='symlog')
@pytest.mark.slow
def test_xcompat(self):
From a49be7f4ea4773af5b801ebd9504a20e5b40b245 Mon Sep 17 00:00:00 2001
From: Matthew Roeschke <emailformattr@gmail.com>
Date: Tue, 22 Jan 2019 05:04:02 -0800
Subject: [PATCH 03/48] BUG: DataFrame respects dtype with masked recarray
(#24874)
---
doc/source/whatsnew/v0.24.0.rst | 4 ++--
pandas/core/internals/construction.py | 2 +-
pandas/tests/frame/test_constructors.py | 11 +++++++++++
3 files changed, 14 insertions(+), 3 deletions(-)
diff --git a/doc/source/whatsnew/v0.24.0.rst b/doc/source/whatsnew/v0.24.0.rst
index 69b59793f7c0d..d782e3d6858a4 100644
--- a/doc/source/whatsnew/v0.24.0.rst
+++ b/doc/source/whatsnew/v0.24.0.rst
@@ -1692,8 +1692,8 @@ Missing
- Bug in :func:`Series.hasnans` that could be incorrectly cached and return incorrect answers if null elements are introduced after an initial call (:issue:`19700`)
- :func:`Series.isin` now treats all NaN-floats as equal also for ``np.object``-dtype. This behavior is consistent with the behavior for float64 (:issue:`22119`)
- :func:`unique` no longer mangles NaN-floats and the ``NaT``-object for ``np.object``-dtype, i.e. ``NaT`` is no longer coerced to a NaN-value and is treated as a different entity. (:issue:`22295`)
-- :func:`DataFrame` and :func:`Series` now properly handle numpy masked arrays with hardened masks. Previously, constructing a DataFrame or Series from a masked array with a hard mask would create a pandas object containing the underlying value, rather than the expected NaN. (:issue:`24574`)
-
+- :class:`DataFrame` and :class:`Series` now properly handle numpy masked arrays with hardened masks. Previously, constructing a DataFrame or Series from a masked array with a hard mask would create a pandas object containing the underlying value, rather than the expected NaN. (:issue:`24574`)
+- Bug in :class:`DataFrame` constructor where ``dtype`` argument was not honored when handling numpy masked record arrays. (:issue:`24874`)
MultiIndex
^^^^^^^^^^
diff --git a/pandas/core/internals/construction.py b/pandas/core/internals/construction.py
index 7af347a141781..c05a9a0f8f3c7 100644
--- a/pandas/core/internals/construction.py
+++ b/pandas/core/internals/construction.py
@@ -93,7 +93,7 @@ def masked_rec_array_to_mgr(data, index, columns, dtype, copy):
if columns is None:
columns = arr_columns
- mgr = arrays_to_mgr(arrays, arr_columns, index, columns)
+ mgr = arrays_to_mgr(arrays, arr_columns, index, columns, dtype)
if copy:
mgr = mgr.copy()
diff --git a/pandas/tests/frame/test_constructors.py b/pandas/tests/frame/test_constructors.py
index 4f6a2e2bfbebf..90ad48cac3a5f 100644
--- a/pandas/tests/frame/test_constructors.py
+++ b/pandas/tests/frame/test_constructors.py
@@ -787,6 +787,17 @@ def test_constructor_maskedarray_hardened(self):
dtype=float)
tm.assert_frame_equal(result, expected)
+ def test_constructor_maskedrecarray_dtype(self):
+ # Ensure constructor honors dtype
+ data = np.ma.array(
+ np.ma.zeros(5, dtype=[('date', '<f8'), ('price', '<f8')]),
+ mask=[False] * 5)
+ data = data.view(ma.mrecords.mrecarray)
+ result = pd.DataFrame(data, dtype=int)
+ expected = pd.DataFrame(np.zeros((5, 2), dtype=int),
+ columns=['date', 'price'])
+ tm.assert_frame_equal(result, expected)
+
def test_constructor_mrecarray(self):
# Ensure mrecarray produces frame identical to dict of masked arrays
# from GH3479
From 853cd7031ff98737b9a50404c4a181dcda67a0be Mon Sep 17 00:00:00 2001
From: Matthew Roeschke <emailformattr@gmail.com>
Date: Tue, 22 Jan 2019 06:49:32 -0800
Subject: [PATCH 04/48] REF/CLN: Move private method (#24875)
---
pandas/core/computation/expr.py | 20 +++++++++++++++-----
pandas/core/reshape/util.py | 13 -------------
2 files changed, 15 insertions(+), 18 deletions(-)
diff --git a/pandas/core/computation/expr.py b/pandas/core/computation/expr.py
index 9a44198ba3b86..d840bf6ae71a2 100644
--- a/pandas/core/computation/expr.py
+++ b/pandas/core/computation/expr.py
@@ -18,7 +18,6 @@
UndefinedVariableError, _arith_ops_syms, _bool_ops_syms, _cmp_ops_syms,
_mathops, _reductions, _unary_ops_syms, is_term)
from pandas.core.computation.scope import Scope
-from pandas.core.reshape.util import compose
import pandas.io.formats.printing as printing
@@ -103,8 +102,19 @@ def _replace_locals(tok):
return toknum, tokval
-def _preparse(source, f=compose(_replace_locals, _replace_booleans,
- _rewrite_assign)):
+def _compose2(f, g):
+ """Compose 2 callables"""
+ return lambda *args, **kwargs: f(g(*args, **kwargs))
+
+
+def _compose(*funcs):
+ """Compose 2 or more callables"""
+ assert len(funcs) > 1, 'At least 2 callables must be passed to compose'
+ return reduce(_compose2, funcs)
+
+
+def _preparse(source, f=_compose(_replace_locals, _replace_booleans,
+ _rewrite_assign)):
"""Compose a collection of tokenization functions
Parameters
@@ -701,8 +711,8 @@ def visitor(x, y):
class PandasExprVisitor(BaseExprVisitor):
def __init__(self, env, engine, parser,
- preparser=partial(_preparse, f=compose(_replace_locals,
- _replace_booleans))):
+ preparser=partial(_preparse, f=_compose(_replace_locals,
+ _replace_booleans))):
super(PandasExprVisitor, self).__init__(env, engine, parser, preparser)
diff --git a/pandas/core/reshape/util.py b/pandas/core/reshape/util.py
index 7f43a0e9719b8..9d4135a7f310e 100644
--- a/pandas/core/reshape/util.py
+++ b/pandas/core/reshape/util.py
@@ -1,7 +1,5 @@
import numpy as np
-from pandas.compat import reduce
-
from pandas.core.dtypes.common import is_list_like
from pandas.core import common as com
@@ -57,14 +55,3 @@ def cartesian_product(X):
return [np.tile(np.repeat(np.asarray(com.values_from_object(x)), b[i]),
np.product(a[i]))
for i, x in enumerate(X)]
-
-
-def _compose2(f, g):
- """Compose 2 callables"""
- return lambda *args, **kwargs: f(g(*args, **kwargs))
-
-
-def compose(*funcs):
- """Compose 2 or more callables"""
- assert len(funcs) > 1, 'At least 2 callables must be passed to compose'
- return reduce(_compose2, funcs)
From 6155ffde425a584a7baa32ca78fbbe0a8435d4cd Mon Sep 17 00:00:00 2001
From: Kaiqi Dong <kaiqi@kth.se>
Date: Tue, 22 Jan 2019 23:04:44 +0100
Subject: [PATCH 05/48] changes based on reviews
---
pandas/plotting/_core.py | 28 ++++++++++++++++------------
pandas/tests/plotting/test_frame.py | 26 +++++++++++++++++++++++---
2 files changed, 39 insertions(+), 15 deletions(-)
diff --git a/pandas/plotting/_core.py b/pandas/plotting/_core.py
index cd5140d57b8d1..8002811acc88a 100644
--- a/pandas/plotting/_core.py
+++ b/pandas/plotting/_core.py
@@ -83,9 +83,9 @@ def _kind(self):
_default_rot = 0
orientation = None
_pop_attributes = ['label', 'style', 'logy', 'logx', 'loglog',
- 'mark_right', 'stacked', 'sym']
+ 'mark_right', 'stacked']
_attr_defaults = {'logy': False, 'logx': False, 'loglog': False,
- 'mark_right': True, 'stacked': False, 'sym': False}
+ 'mark_right': True, 'stacked': False}
def __init__(self, data, kind=None, by=None, subplots=False, sharex=None,
sharey=False, use_index=True,
@@ -309,16 +309,20 @@ def _setup_subplots(self):
axes = _flatten(axes)
- if self.logx or self.loglog:
- if self.sym:
- [a.set_xscale('symlog') for a in axes]
- else:
- [a.set_xscale('log') for a in axes]
- if self.logy or self.loglog:
- if self.sym:
- [a.set_yscale('symlog') for a in axes]
- else:
- [a.set_yscale('log') for a in axes]
+ valid_log = [False, True, 'sym']
+ for i in [self.logx, self.logy, self.loglog]:
+ if i not in valid_log:
+ raise ValueError("Wrong input for log option.")
+
+ if self.logx is True or self.loglog is True:
+ [a.set_xscale('log') for a in axes]
+ elif self.logx == 'sym' or self.loglog == 'sym':
+ [a.set_xscale('symlog') for a in axes]
+
+ if self.logy is True or self.loglog is True:
+ [a.set_yscale('log') for a in axes]
+ elif self.logy == 'sym' or self.loglog == 'sym':
+ [a.set_yscale('symlog') for a in axes]
self.fig = fig
self.axes = axes
diff --git a/pandas/tests/plotting/test_frame.py b/pandas/tests/plotting/test_frame.py
index 50574b5392557..344afa940bb7a 100644
--- a/pandas/tests/plotting/test_frame.py
+++ b/pandas/tests/plotting/test_frame.py
@@ -231,20 +231,40 @@ def test_plot_xy(self):
@pytest.mark.slow
def test_logscales(self):
df = DataFrame({'a': np.arange(100)}, index=np.arange(100))
+
ax = df.plot(logy=True)
self._check_ax_scales(ax, yaxis='log')
- ax = df.plot(logy=True, sym=True)
+ assert ax.get_yscale() == 'log'
+
+ ax = df.plot(logy='sym')
self._check_ax_scales(ax, yaxis='symlog')
+ assert ax.get_yscale() == 'symlog'
ax = df.plot(logx=True)
self._check_ax_scales(ax, xaxis='log')
- ax = df.plot(logx=True, sym=True)
+ assert ax.get_xscale() == 'log'
+
+ ax = df.plot(logx='sym')
self._check_ax_scales(ax, xaxis='symlog')
+ assert ax.get_xscale() == 'symlog'
ax = df.plot(loglog=True)
self._check_ax_scales(ax, xaxis='log', yaxis='log')
- ax = df.plot(loglog=True, sym=True)
+ assert ax.get_xscale() == 'log'
+ assert ax.get_yscale() == 'log'
+
+ ax = df.plot(loglog='sym')
self._check_ax_scales(ax, xaxis='symlog', yaxis='symlog')
+ assert ax.get_xscale() == 'symlog'
+ assert ax.get_yscale() == 'symlog'
+
+ @pytest.mark.parametrize("wrong_input", ["sm", "symlog"])
+ def test_invalid_logscale(self, wrong_input):
+ df = DataFrame({'a': np.arange(100)}, index=np.arange(100))
+
+ msg = "Wrong input for log option."
+ with pytest.raises(ValueError, match=msg):
+ df.plot(logy=wrong_input)
@pytest.mark.slow
def test_xcompat(self):
From 597f9f31639eeb5724e49bec602e15b9bf8be092 Mon Sep 17 00:00:00 2001
From: cgangwar11 <chandan.gangwar0411@gmail.com>
Date: Wed, 23 Jan 2019 04:59:33 +0530
Subject: [PATCH 06/48] BUG : ValueError in case on NaN value in groupby
columns (#24850)
---
doc/source/whatsnew/v0.24.0.rst | 1 +
pandas/core/groupby/grouper.py | 1 +
pandas/tests/groupby/test_categorical.py | 33 ++++++++++++++++++++++++
3 files changed, 35 insertions(+)
diff --git a/doc/source/whatsnew/v0.24.0.rst b/doc/source/whatsnew/v0.24.0.rst
index d782e3d6858a4..9d2dea3aeb796 100644
--- a/doc/source/whatsnew/v0.24.0.rst
+++ b/doc/source/whatsnew/v0.24.0.rst
@@ -1786,6 +1786,7 @@ Groupby/Resample/Rolling
- Bug in :meth:`DataFrame.groupby` did not respect the ``observed`` argument when selecting a column and instead always used ``observed=False`` (:issue:`23970`)
- Bug in :func:`pandas.core.groupby.SeriesGroupBy.pct_change` or :func:`pandas.core.groupby.DataFrameGroupBy.pct_change` would previously work across groups when calculating the percent change, where it now correctly works per group (:issue:`21200`, :issue:`21235`).
- Bug preventing hash table creation with very large number (2^32) of rows (:issue:`22805`)
+- Bug in groupby when grouping on categorical causes ``ValueError`` and incorrect grouping if ``observed=True`` and ``nan`` is present in categorical column (:issue:`24740`, :issue:`21151`).
Reshaping
^^^^^^^^^
diff --git a/pandas/core/groupby/grouper.py b/pandas/core/groupby/grouper.py
index 633a1643f6cdd..260417bc0d598 100644
--- a/pandas/core/groupby/grouper.py
+++ b/pandas/core/groupby/grouper.py
@@ -299,6 +299,7 @@ def __init__(self, index, grouper=None, obj=None, name=None, level=None,
self._labels = self.grouper.codes
if observed:
codes = algorithms.unique1d(self.grouper.codes)
+ codes = codes[codes != -1]
else:
codes = np.arange(len(categories))
diff --git a/pandas/tests/groupby/test_categorical.py b/pandas/tests/groupby/test_categorical.py
index 144b64025e1c0..e118135ccc75d 100644
--- a/pandas/tests/groupby/test_categorical.py
+++ b/pandas/tests/groupby/test_categorical.py
@@ -420,6 +420,39 @@ def test_observed_groups(observed):
tm.assert_dict_equal(result, expected)
+def test_observed_groups_with_nan(observed):
+ # GH 24740
+ df = pd.DataFrame({'cat': pd.Categorical(['a', np.nan, 'a'],
+ categories=['a', 'b', 'd']),
+ 'vals': [1, 2, 3]})
+ g = df.groupby('cat', observed=observed)
+ result = g.groups
+ if observed:
+ expected = {'a': Index([0, 2], dtype='int64')}
+ else:
+ expected = {'a': Index([0, 2], dtype='int64'),
+ 'b': Index([], dtype='int64'),
+ 'd': Index([], dtype='int64')}
+ tm.assert_dict_equal(result, expected)
+
+
+def test_dataframe_categorical_with_nan(observed):
+ # GH 21151
+ s1 = pd.Categorical([np.nan, 'a', np.nan, 'a'],
+ categories=['a', 'b', 'c'])
+ s2 = pd.Series([1, 2, 3, 4])
+ df = pd.DataFrame({'s1': s1, 's2': s2})
+ result = df.groupby('s1', observed=observed).first().reset_index()
+ if observed:
+ expected = DataFrame({'s1': pd.Categorical(['a'],
+ categories=['a', 'b', 'c']), 's2': [2]})
+ else:
+ expected = DataFrame({'s1': pd.Categorical(['a', 'b', 'c'],
+ categories=['a', 'b', 'c']),
+ 's2': [2, np.nan, np.nan]})
+ tm.assert_frame_equal(result, expected)
+
+
def test_datetime():
# GH9049: ensure backward compatibility
levels = pd.date_range('2014-01-01', periods=4)
From c588437f116a080cdcabb023a5e746dda2cb63c9 Mon Sep 17 00:00:00 2001
From: Guillaume Lemaitre <g.lemaitre58@gmail.com>
Date: Wed, 23 Jan 2019 13:23:49 +0100
Subject: [PATCH 07/48] BUG: fix floating precision formatting in presence of
inf (#24863)
---
doc/source/whatsnew/v0.24.0.rst | 1 +
pandas/io/formats/format.py | 14 +++++++----
pandas/tests/io/formats/test_format.py | 33 ++++++++++++++++++++++++++
3 files changed, 43 insertions(+), 5 deletions(-)
diff --git a/doc/source/whatsnew/v0.24.0.rst b/doc/source/whatsnew/v0.24.0.rst
index 9d2dea3aeb796..3dd345890881c 100644
--- a/doc/source/whatsnew/v0.24.0.rst
+++ b/doc/source/whatsnew/v0.24.0.rst
@@ -1751,6 +1751,7 @@ I/O
- Bug in :meth:`DataFrame.to_stata`, :class:`pandas.io.stata.StataWriter` and :class:`pandas.io.stata.StataWriter117` where a exception would leave a partially written and invalid dta file (:issue:`23573`)
- Bug in :meth:`DataFrame.to_stata` and :class:`pandas.io.stata.StataWriter117` that produced invalid files when using strLs with non-ASCII characters (:issue:`23573`)
- Bug in :class:`HDFStore` that caused it to raise ``ValueError`` when reading a Dataframe in Python 3 from fixed format written in Python 2 (:issue:`24510`)
+- Bug in :func:`DataFrame.to_string()` and more generally in the floating ``repr`` formatter. Zeros were not trimmed if ``inf`` was present in a columns while it was the case with NA values. Zeros are now trimmed as in the presence of NA (:issue:`24861`).
Plotting
^^^^^^^^
diff --git a/pandas/io/formats/format.py b/pandas/io/formats/format.py
index bdeed58d856cc..2c1fcab1ebde9 100644
--- a/pandas/io/formats/format.py
+++ b/pandas/io/formats/format.py
@@ -1414,16 +1414,20 @@ def _trim_zeros(str_floats, na_rep='NaN'):
"""
trimmed = str_floats
+ def _is_number(x):
+ return (x != na_rep and not x.endswith('inf'))
+
def _cond(values):
- non_na = [x for x in values if x != na_rep]
- return (len(non_na) > 0 and all(x.endswith('0') for x in non_na) and
- not (any(('e' in x) or ('E' in x) for x in non_na)))
+ finite = [x for x in values if _is_number(x)]
+ return (len(finite) > 0 and all(x.endswith('0') for x in finite) and
+ not (any(('e' in x) or ('E' in x) for x in finite)))
while _cond(trimmed):
- trimmed = [x[:-1] if x != na_rep else x for x in trimmed]
+ trimmed = [x[:-1] if _is_number(x) else x for x in trimmed]
# leave one 0 after the decimal points if need be.
- return [x + "0" if x.endswith('.') and x != na_rep else x for x in trimmed]
+ return [x + "0" if x.endswith('.') and _is_number(x) else x
+ for x in trimmed]
def _has_names(index):
diff --git a/pandas/tests/io/formats/test_format.py b/pandas/tests/io/formats/test_format.py
index 52dce572c6d4f..31ab1e050d95c 100644
--- a/pandas/tests/io/formats/test_format.py
+++ b/pandas/tests/io/formats/test_format.py
@@ -1465,6 +1465,39 @@ def test_to_string_format_na(self):
'4 4.0 bar')
assert result == expected
+ def test_to_string_format_inf(self):
+ # Issue #24861
+ tm.reset_display_options()
+ df = DataFrame({
+ 'A': [-np.inf, np.inf, -1, -2.1234, 3, 4],
+ 'B': [-np.inf, np.inf, 'foo', 'foooo', 'fooooo', 'bar']
+ })
+ result = df.to_string()
+
+ expected = (' A B\n'
+ '0 -inf -inf\n'
+ '1 inf inf\n'
+ '2 -1.0000 foo\n'
+ '3 -2.1234 foooo\n'
+ '4 3.0000 fooooo\n'
+ '5 4.0000 bar')
+ assert result == expected
+
+ df = DataFrame({
+ 'A': [-np.inf, np.inf, -1., -2., 3., 4.],
+ 'B': [-np.inf, np.inf, 'foo', 'foooo', 'fooooo', 'bar']
+ })
+ result = df.to_string()
+
+ expected = (' A B\n'
+ '0 -inf -inf\n'
+ '1 inf inf\n'
+ '2 -1.0 foo\n'
+ '3 -2.0 foooo\n'
+ '4 3.0 fooooo\n'
+ '5 4.0 bar')
+ assert result == expected
+
def test_to_string_decimal(self):
# Issue #23614
df = DataFrame({'A': [6.0, 3.1, 2.2]})
From 8972ddf13f6d0ba827f99a63d4261944baf3f29f Mon Sep 17 00:00:00 2001
From: Marc Garcia <garcia.marc@gmail.com>
Date: Wed, 23 Jan 2019 16:22:24 +0000
Subject: [PATCH 08/48] DOC: Creating top-level user guide section, and moving
pages inside (#24677)
---
doc/source/index.rst.template | 20 +---------
doc/source/{ => user_guide}/advanced.rst | 0
doc/source/{ => user_guide}/categorical.rst | 0
doc/source/{ => user_guide}/computation.rst | 0
doc/source/{ => user_guide}/enhancingperf.rst | 4 +-
doc/source/{ => user_guide}/gotchas.rst | 0
doc/source/{ => user_guide}/groupby.rst | 0
doc/source/user_guide/index.rst | 39 +++++++++++++++++++
doc/source/{ => user_guide}/indexing.rst | 4 +-
doc/source/{ => user_guide}/integer_na.rst | 0
doc/source/{ => user_guide}/io.rst | 14 +++----
doc/source/{ => user_guide}/merging.rst | 0
doc/source/{ => user_guide}/missing_data.rst | 0
doc/source/{ => user_guide}/options.rst | 8 ++--
doc/source/{ => user_guide}/reshaping.rst | 12 +++---
doc/source/{ => user_guide}/sparse.rst | 0
doc/source/{ => user_guide}/style.ipynb | 2 +-
doc/source/{ => user_guide}/text.rst | 0
doc/source/{ => user_guide}/timedeltas.rst | 0
doc/source/{ => user_guide}/timeseries.rst | 0
doc/source/{ => user_guide}/visualization.rst | 0
21 files changed, 62 insertions(+), 41 deletions(-)
rename doc/source/{ => user_guide}/advanced.rst (100%)
rename doc/source/{ => user_guide}/categorical.rst (100%)
rename doc/source/{ => user_guide}/computation.rst (100%)
rename doc/source/{ => user_guide}/enhancingperf.rst (99%)
rename doc/source/{ => user_guide}/gotchas.rst (100%)
rename doc/source/{ => user_guide}/groupby.rst (100%)
create mode 100644 doc/source/user_guide/index.rst
rename doc/source/{ => user_guide}/indexing.rst (99%)
rename doc/source/{ => user_guide}/integer_na.rst (100%)
rename doc/source/{ => user_guide}/io.rst (99%)
rename doc/source/{ => user_guide}/merging.rst (100%)
rename doc/source/{ => user_guide}/missing_data.rst (100%)
rename doc/source/{ => user_guide}/options.rst (99%)
rename doc/source/{ => user_guide}/reshaping.rst (98%)
rename doc/source/{ => user_guide}/sparse.rst (100%)
rename doc/source/{ => user_guide}/style.ipynb (99%)
rename doc/source/{ => user_guide}/text.rst (100%)
rename doc/source/{ => user_guide}/timedeltas.rst (100%)
rename doc/source/{ => user_guide}/timeseries.rst (100%)
rename doc/source/{ => user_guide}/visualization.rst (100%)
diff --git a/doc/source/index.rst.template b/doc/source/index.rst.template
index b85150c3444b7..571c906acbd43 100644
--- a/doc/source/index.rst.template
+++ b/doc/source/index.rst.template
@@ -131,25 +131,7 @@ See the package overview for more detail about what's in the library.
cookbook
dsintro
basics
- text
- options
- indexing
- advanced
- computation
- missing_data
- groupby
- merging
- reshaping
- timeseries
- timedeltas
- categorical
- integer_na
- visualization
- style
- io
- enhancingperf
- sparse
- gotchas
+ user_guide/index
r_interface
ecosystem
comparison_with_r
diff --git a/doc/source/advanced.rst b/doc/source/user_guide/advanced.rst
similarity index 100%
rename from doc/source/advanced.rst
rename to doc/source/user_guide/advanced.rst
diff --git a/doc/source/categorical.rst b/doc/source/user_guide/categorical.rst
similarity index 100%
rename from doc/source/categorical.rst
rename to doc/source/user_guide/categorical.rst
diff --git a/doc/source/computation.rst b/doc/source/user_guide/computation.rst
similarity index 100%
rename from doc/source/computation.rst
rename to doc/source/user_guide/computation.rst
diff --git a/doc/source/enhancingperf.rst b/doc/source/user_guide/enhancingperf.rst
similarity index 99%
rename from doc/source/enhancingperf.rst
rename to doc/source/user_guide/enhancingperf.rst
index 0e3d389aa4f6e..9941ffcc9de4d 100644
--- a/doc/source/enhancingperf.rst
+++ b/doc/source/user_guide/enhancingperf.rst
@@ -783,7 +783,7 @@ significant performance benefit. Here is a plot showing the running time of
computation. The two lines are two different engines.
-.. image:: _static/eval-perf.png
+.. image:: ../_static/eval-perf.png
.. note::
@@ -791,7 +791,7 @@ computation. The two lines are two different engines.
Operations with smallish objects (around 15k-20k rows) are faster using
plain Python:
- .. image:: _static/eval-perf-small.png
+ .. image:: ../_static/eval-perf-small.png
This plot was created using a ``DataFrame`` with 3 columns each containing
diff --git a/doc/source/gotchas.rst b/doc/source/user_guide/gotchas.rst
similarity index 100%
rename from doc/source/gotchas.rst
rename to doc/source/user_guide/gotchas.rst
diff --git a/doc/source/groupby.rst b/doc/source/user_guide/groupby.rst
similarity index 100%
rename from doc/source/groupby.rst
rename to doc/source/user_guide/groupby.rst
diff --git a/doc/source/user_guide/index.rst b/doc/source/user_guide/index.rst
new file mode 100644
index 0000000000000..60e722808d647
--- /dev/null
+++ b/doc/source/user_guide/index.rst
@@ -0,0 +1,39 @@
+{{ header }}
+
+.. _user_guide:
+
+==========
+User Guide
+==========
+
+The User Guide covers all of pandas by topic area. Each of the subsections
+introduces a topic (such as "working with missing data"), and discusses how
+pandas approaches the problem, with many examples throughout.
+
+Users brand-new to pandas should start with :ref:`10min`.
+
+Further information on any specific method can be obtained in the
+:ref:`api`.
+
+.. toctree::
+ :maxdepth: 2
+
+ io
+ indexing
+ advanced
+ merging
+ reshaping
+ text
+ missing_data
+ categorical
+ integer_na
+ visualization
+ computation
+ groupby
+ timeseries
+ timedeltas
+ style
+ options
+ enhancingperf
+ sparse
+ gotchas
diff --git a/doc/source/indexing.rst b/doc/source/user_guide/indexing.rst
similarity index 99%
rename from doc/source/indexing.rst
rename to doc/source/user_guide/indexing.rst
index 3fe416c48f670..be1745e2664a1 100644
--- a/doc/source/indexing.rst
+++ b/doc/source/user_guide/indexing.rst
@@ -1392,7 +1392,7 @@ Performance of :meth:`~pandas.DataFrame.query`
``DataFrame.query()`` using ``numexpr`` is slightly faster than Python for
large frames.
-.. image:: _static/query-perf.png
+.. image:: ../_static/query-perf.png
.. note::
@@ -1400,7 +1400,7 @@ large frames.
with ``DataFrame.query()`` if your frame has more than approximately 200,000
rows.
- .. image:: _static/query-perf-small.png
+ .. image:: ../_static/query-perf-small.png
This plot was created using a ``DataFrame`` with 3 columns each containing
floating point values generated using ``numpy.random.randn()``.
diff --git a/doc/source/integer_na.rst b/doc/source/user_guide/integer_na.rst
similarity index 100%
rename from doc/source/integer_na.rst
rename to doc/source/user_guide/integer_na.rst
diff --git a/doc/source/io.rst b/doc/source/user_guide/io.rst
similarity index 99%
rename from doc/source/io.rst
rename to doc/source/user_guide/io.rst
index dd1cde0bdff73..0132392aacaff 100644
--- a/doc/source/io.rst
+++ b/doc/source/user_guide/io.rst
@@ -2549,7 +2549,7 @@ in the method ``to_string`` described above.
HTML:
.. raw:: html
- :file: _static/basic.html
+ :file: ../_static/basic.html
The ``columns`` argument will limit the columns shown:
@@ -2565,7 +2565,7 @@ The ``columns`` argument will limit the columns shown:
HTML:
.. raw:: html
- :file: _static/columns.html
+ :file: ../_static/columns.html
``float_format`` takes a Python callable to control the precision of floating
point values:
@@ -2582,7 +2582,7 @@ point values:
HTML:
.. raw:: html
- :file: _static/float_format.html
+ :file: ../_static/float_format.html
``bold_rows`` will make the row labels bold by default, but you can turn that
off:
@@ -2597,7 +2597,7 @@ off:
write_html(df, 'nobold', bold_rows=False)
.. raw:: html
- :file: _static/nobold.html
+ :file: ../_static/nobold.html
The ``classes`` argument provides the ability to give the resulting HTML
table CSS classes. Note that these classes are *appended* to the existing
@@ -2627,7 +2627,7 @@ that contain URLs.
HTML:
.. raw:: html
- :file: _static/render_links.html
+ :file: ../_static/render_links.html
Finally, the ``escape`` argument allows you to control whether the
"<", ">" and "&" characters escaped in the resulting HTML (by default it is
@@ -2651,7 +2651,7 @@ Escaped:
print(df.to_html())
.. raw:: html
- :file: _static/escape.html
+ :file: ../_static/escape.html
Not escaped:
@@ -2660,7 +2660,7 @@ Not escaped:
print(df.to_html(escape=False))
.. raw:: html
- :file: _static/noescape.html
+ :file: ../_static/noescape.html
.. note::
diff --git a/doc/source/merging.rst b/doc/source/user_guide/merging.rst
similarity index 100%
rename from doc/source/merging.rst
rename to doc/source/user_guide/merging.rst
diff --git a/doc/source/missing_data.rst b/doc/source/user_guide/missing_data.rst
similarity index 100%
rename from doc/source/missing_data.rst
rename to doc/source/user_guide/missing_data.rst
diff --git a/doc/source/options.rst b/doc/source/user_guide/options.rst
similarity index 99%
rename from doc/source/options.rst
rename to doc/source/user_guide/options.rst
index e91be3e6ae730..d640d8b1153c5 100644
--- a/doc/source/options.rst
+++ b/doc/source/user_guide/options.rst
@@ -487,7 +487,7 @@ If a DataFrame or Series contains these characters, the default output mode may
df = pd.DataFrame({u'国籍': ['UK', u'日本'], u'名前': ['Alice', u'しのぶ']})
df
-.. image:: _static/option_unicode01.png
+.. image:: ../_static/option_unicode01.png
Enabling ``display.unicode.east_asian_width`` allows pandas to check each character's "East Asian Width" property.
These characters can be aligned properly by setting this option to ``True``. However, this will result in longer render
@@ -498,7 +498,7 @@ times than the standard ``len`` function.
pd.set_option('display.unicode.east_asian_width', True)
df
-.. image:: _static/option_unicode02.png
+.. image:: ../_static/option_unicode02.png
In addition, Unicode characters whose width is "Ambiguous" can either be 1 or 2 characters wide depending on the
terminal setting or encoding. The option ``display.unicode.ambiguous_as_wide`` can be used to handle the ambiguity.
@@ -510,7 +510,7 @@ By default, an "Ambiguous" character's width, such as "¡" (inverted exclamation
df = pd.DataFrame({'a': ['xxx', u'¡¡'], 'b': ['yyy', u'¡¡']})
df
-.. image:: _static/option_unicode03.png
+.. image:: ../_static/option_unicode03.png
Enabling ``display.unicode.ambiguous_as_wide`` makes pandas interpret these characters' widths to be 2.
(Note that this option will only be effective when ``display.unicode.east_asian_width`` is enabled.)
@@ -522,7 +522,7 @@ However, setting this option incorrectly for your terminal will cause these char
pd.set_option('display.unicode.ambiguous_as_wide', True)
df
-.. image:: _static/option_unicode04.png
+.. image:: ../_static/option_unicode04.png
.. ipython:: python
:suppress:
diff --git a/doc/source/reshaping.rst b/doc/source/user_guide/reshaping.rst
similarity index 98%
rename from doc/source/reshaping.rst
rename to doc/source/user_guide/reshaping.rst
index 9891e22e9d552..5c11be34e6ed4 100644
--- a/doc/source/reshaping.rst
+++ b/doc/source/user_guide/reshaping.rst
@@ -9,7 +9,7 @@ Reshaping and Pivot Tables
Reshaping by pivoting DataFrame objects
---------------------------------------
-.. image:: _static/reshaping_pivot.png
+.. image:: ../_static/reshaping_pivot.png
.. ipython:: python
:suppress:
@@ -101,7 +101,7 @@ are homogeneously-typed.
Reshaping by stacking and unstacking
------------------------------------
-.. image:: _static/reshaping_stack.png
+.. image:: ../_static/reshaping_stack.png
Closely related to the :meth:`~DataFrame.pivot` method are the related
:meth:`~DataFrame.stack` and :meth:`~DataFrame.unstack` methods available on
@@ -116,7 +116,7 @@ Closely related to the :meth:`~DataFrame.pivot` method are the related
(possibly hierarchical) row index to the column axis, producing a reshaped
``DataFrame`` with a new inner-most level of column labels.
-.. image:: _static/reshaping_unstack.png
+.. image:: ../_static/reshaping_unstack.png
The clearest way to explain is by example. Let's take a prior example data set
from the hierarchical indexing section:
@@ -158,7 +158,7 @@ unstacks the **last level**:
.. _reshaping.unstack_by_name:
-.. image:: _static/reshaping_unstack_1.png
+.. image:: ../_static/reshaping_unstack_1.png
If the indexes have names, you can use the level names instead of specifying
the level numbers:
@@ -168,7 +168,7 @@ the level numbers:
stacked.unstack('second')
-.. image:: _static/reshaping_unstack_0.png
+.. image:: ../_static/reshaping_unstack_0.png
Notice that the ``stack`` and ``unstack`` methods implicitly sort the index
levels involved. Hence a call to ``stack`` and then ``unstack``, or vice versa,
@@ -279,7 +279,7 @@ the right thing:
Reshaping by Melt
-----------------
-.. image:: _static/reshaping_melt.png
+.. image:: ../_static/reshaping_melt.png
The top-level :func:`~pandas.melt` function and the corresponding :meth:`DataFrame.melt`
are useful to massage a ``DataFrame`` into a format where one or more columns
diff --git a/doc/source/sparse.rst b/doc/source/user_guide/sparse.rst
similarity index 100%
rename from doc/source/sparse.rst
rename to doc/source/user_guide/sparse.rst
diff --git a/doc/source/style.ipynb b/doc/source/user_guide/style.ipynb
similarity index 99%
rename from doc/source/style.ipynb
rename to doc/source/user_guide/style.ipynb
index 792fe5120f6e8..a238c3b16e9ad 100644
--- a/doc/source/style.ipynb
+++ b/doc/source/user_guide/style.ipynb
@@ -992,7 +992,7 @@
"source": [
"A screenshot of the output:\n",
"\n",
- "\n"
+ "\n"
]
},
{
diff --git a/doc/source/text.rst b/doc/source/user_guide/text.rst
similarity index 100%
rename from doc/source/text.rst
rename to doc/source/user_guide/text.rst
diff --git a/doc/source/timedeltas.rst b/doc/source/user_guide/timedeltas.rst
similarity index 100%
rename from doc/source/timedeltas.rst
rename to doc/source/user_guide/timedeltas.rst
diff --git a/doc/source/timeseries.rst b/doc/source/user_guide/timeseries.rst
similarity index 100%
rename from doc/source/timeseries.rst
rename to doc/source/user_guide/timeseries.rst
diff --git a/doc/source/visualization.rst b/doc/source/user_guide/visualization.rst
similarity index 100%
rename from doc/source/visualization.rst
rename to doc/source/user_guide/visualization.rst
From 14eac280e1b7516714d117e65b45023dee7feee7 Mon Sep 17 00:00:00 2001
From: Marc Garcia <garcia.marc@gmail.com>
Date: Wed, 23 Jan 2019 16:23:18 +0000
Subject: [PATCH 09/48] DOC: Creating top-level development section, and moving
pages inside (#24691)
---
doc/source/{ => development}/contributing.rst | 2 +-
.../{ => development}/contributing_docstring.rst | 0
doc/source/{ => development}/developer.rst | 0
doc/source/{ => development}/extending.rst | 0
doc/source/development/index.rst | 15 +++++++++++++++
doc/source/{ => development}/internals.rst | 0
doc/source/index.rst.template | 5 +----
setup.cfg | 2 +-
8 files changed, 18 insertions(+), 6 deletions(-)
rename doc/source/{ => development}/contributing.rst (99%)
rename doc/source/{ => development}/contributing_docstring.rst (100%)
rename doc/source/{ => development}/developer.rst (100%)
rename doc/source/{ => development}/extending.rst (100%)
create mode 100644 doc/source/development/index.rst
rename doc/source/{ => development}/internals.rst (100%)
diff --git a/doc/source/contributing.rst b/doc/source/development/contributing.rst
similarity index 99%
rename from doc/source/contributing.rst
rename to doc/source/development/contributing.rst
index a68e5c70087e9..c9d6845107dfc 100644
--- a/doc/source/contributing.rst
+++ b/doc/source/development/contributing.rst
@@ -698,7 +698,7 @@ A pull-request will be considered for merging when you have an all 'green' build
then you will get a red 'X', where you can click through to see the individual failed tests.
This is an example of a green build.
-.. image:: _static/ci.png
+.. image:: ../_static/ci.png
.. note::
diff --git a/doc/source/contributing_docstring.rst b/doc/source/development/contributing_docstring.rst
similarity index 100%
rename from doc/source/contributing_docstring.rst
rename to doc/source/development/contributing_docstring.rst
diff --git a/doc/source/developer.rst b/doc/source/development/developer.rst
similarity index 100%
rename from doc/source/developer.rst
rename to doc/source/development/developer.rst
diff --git a/doc/source/extending.rst b/doc/source/development/extending.rst
similarity index 100%
rename from doc/source/extending.rst
rename to doc/source/development/extending.rst
diff --git a/doc/source/development/index.rst b/doc/source/development/index.rst
new file mode 100644
index 0000000000000..d67a6c3a2ca04
--- /dev/null
+++ b/doc/source/development/index.rst
@@ -0,0 +1,15 @@
+{{ header }}
+
+.. _development:
+
+===========
+Development
+===========
+
+.. toctree::
+ :maxdepth: 2
+
+ contributing
+ internals
+ extending
+ developer
diff --git a/doc/source/internals.rst b/doc/source/development/internals.rst
similarity index 100%
rename from doc/source/internals.rst
rename to doc/source/development/internals.rst
diff --git a/doc/source/index.rst.template b/doc/source/index.rst.template
index 571c906acbd43..53f116a1a0e0a 100644
--- a/doc/source/index.rst.template
+++ b/doc/source/index.rst.template
@@ -124,7 +124,6 @@ See the package overview for more detail about what's in the library.
{% if not single_doc -%}
What's New <whatsnew/v0.24.0>
install
- contributing
overview
10min
tutorials
@@ -143,8 +142,6 @@ See the package overview for more detail about what's in the library.
api/index
{% endif -%}
{% if not single_doc -%}
- developer
- internals
- extending
+ development/index
whatsnew/index
{% endif -%}
diff --git a/setup.cfg b/setup.cfg
index 95c71826a80d4..6143cb8446216 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -47,7 +47,7 @@ ignore = E402, # module level import not at top of file
exclude =
doc/source/basics.rst
- doc/source/contributing_docstring.rst
+ doc/source/development/contributing_docstring.rst
[yapf]
From 4b937ff59127bf0edec8e07a667fa222bf2e3b4e Mon Sep 17 00:00:00 2001
From: Marc Garcia <garcia.marc@gmail.com>
Date: Wed, 23 Jan 2019 17:52:11 +0000
Subject: [PATCH 10/48] DOC: Creating top-level getting started section, and
moving pages inside (#24678)
---
doc/source/{ => getting_started}/10min.rst | 0
doc/source/{ => getting_started}/basics.rst | 0
doc/source/{ => getting_started}/dsintro.rst | 0
doc/source/getting_started/index.rst | 16 ++++++++++++++++
doc/source/{ => getting_started}/overview.rst | 2 +-
doc/source/{ => getting_started}/tutorials.rst | 0
doc/source/index.rst.template | 6 +-----
setup.cfg | 2 +-
8 files changed, 19 insertions(+), 7 deletions(-)
rename doc/source/{ => getting_started}/10min.rst (100%)
rename doc/source/{ => getting_started}/basics.rst (100%)
rename doc/source/{ => getting_started}/dsintro.rst (100%)
create mode 100644 doc/source/getting_started/index.rst
rename doc/source/{ => getting_started}/overview.rst (99%)
rename doc/source/{ => getting_started}/tutorials.rst (100%)
diff --git a/doc/source/10min.rst b/doc/source/getting_started/10min.rst
similarity index 100%
rename from doc/source/10min.rst
rename to doc/source/getting_started/10min.rst
diff --git a/doc/source/basics.rst b/doc/source/getting_started/basics.rst
similarity index 100%
rename from doc/source/basics.rst
rename to doc/source/getting_started/basics.rst
diff --git a/doc/source/dsintro.rst b/doc/source/getting_started/dsintro.rst
similarity index 100%
rename from doc/source/dsintro.rst
rename to doc/source/getting_started/dsintro.rst
diff --git a/doc/source/getting_started/index.rst b/doc/source/getting_started/index.rst
new file mode 100644
index 0000000000000..116efe79beef1
--- /dev/null
+++ b/doc/source/getting_started/index.rst
@@ -0,0 +1,16 @@
+{{ header }}
+
+.. _getting_started:
+
+===============
+Getting started
+===============
+
+.. toctree::
+ :maxdepth: 2
+
+ overview
+ 10min
+ basics
+ dsintro
+ tutorials
diff --git a/doc/source/overview.rst b/doc/source/getting_started/overview.rst
similarity index 99%
rename from doc/source/overview.rst
rename to doc/source/getting_started/overview.rst
index b98e2d4b9963c..1e07df47aadca 100644
--- a/doc/source/overview.rst
+++ b/doc/source/getting_started/overview.rst
@@ -119,5 +119,5 @@ The information about current institutional partners can be found on `pandas web
License
-------
-.. literalinclude:: ../../LICENSE
+.. literalinclude:: ../../../LICENSE
diff --git a/doc/source/tutorials.rst b/doc/source/getting_started/tutorials.rst
similarity index 100%
rename from doc/source/tutorials.rst
rename to doc/source/getting_started/tutorials.rst
diff --git a/doc/source/index.rst.template b/doc/source/index.rst.template
index 53f116a1a0e0a..bc420a906b59c 100644
--- a/doc/source/index.rst.template
+++ b/doc/source/index.rst.template
@@ -124,12 +124,8 @@ See the package overview for more detail about what's in the library.
{% if not single_doc -%}
What's New <whatsnew/v0.24.0>
install
- overview
- 10min
- tutorials
+ getting_started/index
cookbook
- dsintro
- basics
user_guide/index
r_interface
ecosystem
diff --git a/setup.cfg b/setup.cfg
index 6143cb8446216..7155cc1013544 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -46,7 +46,7 @@ ignore = E402, # module level import not at top of file
E711, # comparison to none should be 'if cond is none:'
exclude =
- doc/source/basics.rst
+ doc/source/getting_started/basics.rst
doc/source/development/contributing_docstring.rst
From 6a745d826d9d5f5f46e208b0dad4d4ce0524defe Mon Sep 17 00:00:00 2001
From: Marc Garcia <garcia.marc@gmail.com>
Date: Wed, 23 Jan 2019 18:30:34 +0000
Subject: [PATCH 11/48] DOC: Implementing redirect system, and adding
user_guide redirects (#24715)
* DOC: Implementing redirect system, and adding user_guide redirects
* Using relative urls for the redirect
* Validating that no file is overwritten by a redirect
* Adding redirects for getting started and development sections
---
doc/make.py | 78 ++++++++++++++++++++++++++++++++++++++++++++++-
doc/redirects.csv | 37 ++++++++++++++++++++++
2 files changed, 114 insertions(+), 1 deletion(-)
create mode 100644 doc/redirects.csv
diff --git a/doc/make.py b/doc/make.py
index 0b14a9dcd4c34..eb4a33a569c5a 100755
--- a/doc/make.py
+++ b/doc/make.py
@@ -15,15 +15,18 @@
import sys
import os
import shutil
+import csv
import subprocess
import argparse
import webbrowser
+import docutils
+import docutils.parsers.rst
DOC_PATH = os.path.dirname(os.path.abspath(__file__))
SOURCE_PATH = os.path.join(DOC_PATH, 'source')
BUILD_PATH = os.path.join(DOC_PATH, 'build')
-BUILD_DIRS = ['doctrees', 'html', 'latex', 'plots', '_static', '_templates']
+REDIRECTS_FILE = os.path.join(DOC_PATH, 'redirects.csv')
class DocBuilder:
@@ -139,6 +142,77 @@ def _open_browser(self, single_doc_html):
single_doc_html)
webbrowser.open(url, new=2)
+ def _get_page_title(self, page):
+ """
+ Open the rst file `page` and extract its title.
+ """
+ fname = os.path.join(SOURCE_PATH, '{}.rst'.format(page))
+ option_parser = docutils.frontend.OptionParser(
+ components=(docutils.parsers.rst.Parser,))
+ doc = docutils.utils.new_document(
+ '<doc>',
+ option_parser.get_default_values())
+ with open(fname) as f:
+ data = f.read()
+
+ parser = docutils.parsers.rst.Parser()
+ # do not generate any warning when parsing the rst
+ with open(os.devnull, 'a') as f:
+ doc.reporter.stream = f
+ parser.parse(data, doc)
+
+ section = next(node for node in doc.children
+ if isinstance(node, docutils.nodes.section))
+ title = next(node for node in section.children
+ if isinstance(node, docutils.nodes.title))
+
+ return title.astext()
+
+ def _add_redirects(self):
+ """
+ Create in the build directory an html file with a redirect,
+ for every row in REDIRECTS_FILE.
+ """
+ html = '''
+ <html>
+ <head>
+ <meta http-equiv="refresh" content="0;URL={url}"/>
+ </head>
+ <body>
+ <p>
+ The page has been moved to <a href="{url}">{title}</a>
+ </p>
+ </body>
+ <html>
+ '''
+ with open(REDIRECTS_FILE) as mapping_fd:
+ reader = csv.reader(mapping_fd)
+ for row in reader:
+ if not row or row[0].strip().startswith('#'):
+ continue
+
+ path = os.path.join(BUILD_PATH,
+ 'html',
+ *row[0].split('/')) + '.html'
+
+ try:
+ title = self._get_page_title(row[1])
+ except Exception:
+ # the file can be an ipynb and not an rst, or docutils
+ # may not be able to read the rst because it has some
+ # sphinx specific stuff
+ title = 'this page'
+
+ if os.path.exists(path):
+ raise RuntimeError((
+ 'Redirection would overwrite an existing file: '
+ '{}').format(path))
+
+ with open(path, 'w') as moved_page_fd:
+ moved_page_fd.write(
+ html.format(url='{}.html'.format(row[1]),
+ title=title))
+
def html(self):
"""
Build HTML documentation.
@@ -150,6 +224,8 @@ def html(self):
if self.single_doc_html is not None:
self._open_browser(self.single_doc_html)
+ else:
+ self._add_redirects()
return ret_code
def latex(self, force=False):
diff --git a/doc/redirects.csv b/doc/redirects.csv
new file mode 100644
index 0000000000000..4f4b3d7fc0780
--- /dev/null
+++ b/doc/redirects.csv
@@ -0,0 +1,37 @@
+# This file should contain all the redirects in the documentation
+# in the format `<old_path>,<new_path>`
+
+# getting started
+10min,getting_started/10min
+basics,getting_started/basics
+dsintro,getting_started/dsintro
+overview,getting_started/overview
+tutorials,getting_started/tutorials
+
+# user guide
+advanced,user_guide/advanced
+categorical,user_guide/categorical
+computation,user_guide/computation
+enhancingperf,user_guide/enhancingperf
+gotchas,user_guide/gotchas
+groupby,user_guide/groupby
+indexing,user_guide/indexing
+integer_na,user_guide/integer_na
+io,user_guide/io
+merging,user_guide/merging
+missing_data,user_guide/missing_data
+options,user_guide/options
+reshaping,user_guide/reshaping
+sparse,user_guide/sparse
+style,user_guide/style
+text,user_guide/text
+timedeltas,user_guide/timedeltas
+timeseries,user_guide/timeseries
+visualization,user_guide/visualization
+
+# development
+contributing,development/contributing
+contributing_docstring,development/contributing_docstring
+developer,development/developer
+extending,development/extending
+internals,development/internals
From 2fa0835737a0e3e111e893d30ed2f25b7249fd4b Mon Sep 17 00:00:00 2001
From: Tom Augspurger <TomAugspurger@users.noreply.github.com>
Date: Wed, 23 Jan 2019 15:37:15 -0600
Subject: [PATCH 12/48] DOC: fixups (#24888)
* Fixed heading on whatnew
* Remove empty scalars.rst
---
doc/source/api/scalars.rst | 0
doc/source/whatsnew/v0.24.0.rst | 5 ++++-
2 files changed, 4 insertions(+), 1 deletion(-)
delete mode 100644 doc/source/api/scalars.rst
diff --git a/doc/source/api/scalars.rst b/doc/source/api/scalars.rst
deleted file mode 100644
index e69de29bb2d1d..0000000000000
diff --git a/doc/source/whatsnew/v0.24.0.rst b/doc/source/whatsnew/v0.24.0.rst
index 3dd345890881c..9198c610f0f44 100644
--- a/doc/source/whatsnew/v0.24.0.rst
+++ b/doc/source/whatsnew/v0.24.0.rst
@@ -13,6 +13,9 @@ What's New in 0.24.0 (January XX, 2019)
These are the changes in pandas 0.24.0. See :ref:`release` for a full changelog
including other versions of pandas.
+Enhancements
+~~~~~~~~~~~~
+
Highlights include
* :ref:`Optional Nullable Integer Support <whatsnew_0240.enhancements.intna>`
@@ -1165,7 +1168,7 @@ Other API Changes
.. _whatsnew_0240.api.extension:
ExtensionType Changes
-^^^^^^^^^^^^^^^^^^^^^
+~~~~~~~~~~~~~~~~~~~~~
**Equality and Hashability**
From 94d989e4ae682bbd39f5599ef1d1f455bea0c3fd Mon Sep 17 00:00:00 2001
From: Christopher Whelan <topherwhelan@gmail.com>
Date: Thu, 24 Jan 2019 04:44:54 -0800
Subject: [PATCH 13/48] CLN: fix typo in ctors.SeriesDtypesConstructors setup
(#24894)
---
asv_bench/benchmarks/ctors.py | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/asv_bench/benchmarks/ctors.py b/asv_bench/benchmarks/ctors.py
index 9082b4186bfa4..5715c4fb2d0d4 100644
--- a/asv_bench/benchmarks/ctors.py
+++ b/asv_bench/benchmarks/ctors.py
@@ -72,7 +72,7 @@ class SeriesDtypesConstructors(object):
def setup(self):
N = 10**4
- self.arr = np.random.randn(N, N)
+ self.arr = np.random.randn(N)
self.arr_str = np.array(['foo', 'bar', 'baz'], dtype=object)
self.s = Series([Timestamp('20110101'), Timestamp('20120101'),
Timestamp('20130101')] * N * 10)
From 0c319f55761a60e0a626f57c0ee46d4326121cfd Mon Sep 17 00:00:00 2001
From: Tom Augspurger <TomAugspurger@users.noreply.github.com>
Date: Thu, 24 Jan 2019 08:44:11 -0600
Subject: [PATCH 14/48] DOC: No clean in sphinx_build (#24902)
Closes https://github.com/pandas-dev/pandas/issues/24727
---
doc/make.py | 2 --
1 file changed, 2 deletions(-)
diff --git a/doc/make.py b/doc/make.py
index eb4a33a569c5a..bc458d6b53cb0 100755
--- a/doc/make.py
+++ b/doc/make.py
@@ -121,8 +121,6 @@ def _sphinx_build(self, kind):
raise ValueError('kind must be html or latex, '
'not {}'.format(kind))
- self.clean()
-
cmd = ['sphinx-build', '-b', kind]
if self.num_jobs:
cmd += ['-j', str(self.num_jobs)]
From 17ad7916b970e7117fcaf36b37e113d6aff9b4fb Mon Sep 17 00:00:00 2001
From: Joris Van den Bossche <jorisvandenbossche@gmail.com>
Date: Thu, 24 Jan 2019 16:25:29 +0100
Subject: [PATCH 15/48] BUG (output formatting): use fixed with for truncation
column instead of inferring from last column (#24905)
---
doc/source/whatsnew/v0.24.0.rst | 1 +
pandas/io/formats/format.py | 12 ++------
pandas/tests/io/formats/test_format.py | 41 ++++++++++++++++++--------
3 files changed, 32 insertions(+), 22 deletions(-)
diff --git a/doc/source/whatsnew/v0.24.0.rst b/doc/source/whatsnew/v0.24.0.rst
index 9198c610f0f44..1c44d35aae4d1 100644
--- a/doc/source/whatsnew/v0.24.0.rst
+++ b/doc/source/whatsnew/v0.24.0.rst
@@ -1755,6 +1755,7 @@ I/O
- Bug in :meth:`DataFrame.to_stata` and :class:`pandas.io.stata.StataWriter117` that produced invalid files when using strLs with non-ASCII characters (:issue:`23573`)
- Bug in :class:`HDFStore` that caused it to raise ``ValueError`` when reading a Dataframe in Python 3 from fixed format written in Python 2 (:issue:`24510`)
- Bug in :func:`DataFrame.to_string()` and more generally in the floating ``repr`` formatter. Zeros were not trimmed if ``inf`` was present in a columns while it was the case with NA values. Zeros are now trimmed as in the presence of NA (:issue:`24861`).
+- Bug in the ``repr`` when truncating the number of columns and having a wide last column (:issue:`24849`).
Plotting
^^^^^^^^
diff --git a/pandas/io/formats/format.py b/pandas/io/formats/format.py
index 2c1fcab1ebde9..62fa04e784072 100644
--- a/pandas/io/formats/format.py
+++ b/pandas/io/formats/format.py
@@ -435,9 +435,6 @@ def _chk_truncate(self):
"""
from pandas.core.reshape.concat import concat
- # Column of which first element is used to determine width of a dot col
- self.tr_size_col = -1
-
# Cut the data to the information actually printed
max_cols = self.max_cols
max_rows = self.max_rows
@@ -556,10 +553,7 @@ def _to_str_columns(self):
if truncate_h:
col_num = self.tr_col_num
- # infer from column header
- col_width = self.adj.len(strcols[self.tr_size_col][0])
- strcols.insert(self.tr_col_num + 1, ['...'.center(col_width)] *
- (len(str_index)))
+ strcols.insert(self.tr_col_num + 1, [' ...'] * (len(str_index)))
if truncate_v:
n_header_rows = len(str_index) - len(frame)
row_num = self.tr_row_num
@@ -577,8 +571,8 @@ def _to_str_columns(self):
if ix == 0:
dot_mode = 'left'
elif is_dot_col:
- cwidth = self.adj.len(strcols[self.tr_size_col][0])
- dot_mode = 'center'
+ cwidth = 4
+ dot_mode = 'right'
else:
dot_mode = 'right'
dot_str = self.adj.justify([my_str], cwidth, mode=dot_mode)[0]
diff --git a/pandas/tests/io/formats/test_format.py b/pandas/tests/io/formats/test_format.py
index 31ab1e050d95c..5d922ccaf1fd5 100644
--- a/pandas/tests/io/formats/test_format.py
+++ b/pandas/tests/io/formats/test_format.py
@@ -345,6 +345,15 @@ def test_repr_truncates_terminal_size_full(self, monkeypatch):
lambda: terminal_size)
assert "..." not in str(df)
+ def test_repr_truncation_column_size(self):
+ # dataframe with last column very wide -> check it is not used to
+ # determine size of truncation (...) column
+ df = pd.DataFrame({'a': [108480, 30830], 'b': [12345, 12345],
+ 'c': [12345, 12345], 'd': [12345, 12345],
+ 'e': ['a' * 50] * 2})
+ assert "..." in str(df)
+ assert " ... " not in str(df)
+
def test_repr_max_columns_max_rows(self):
term_width, term_height = get_terminal_size()
if term_width < 10 or term_height < 10:
@@ -543,7 +552,7 @@ def test_to_string_with_formatters_unicode(self):
formatters={u('c/\u03c3'): lambda x: '{x}'.format(x=x)})
assert result == u(' c/\u03c3\n') + '0 1\n1 2\n2 3'
- def test_east_asian_unicode_frame(self):
+ def test_east_asian_unicode_false(self):
if PY3:
_rep = repr
else:
@@ -643,17 +652,23 @@ def test_east_asian_unicode_frame(self):
u'ああああ': [u'さ', u'し', u'す', u'せ']},
columns=['a', 'b', 'c', u'ああああ'])
- expected = (u" a ... ああああ\n0 あああああ ... さ\n"
- u".. ... ... ...\n3 えええ ... せ\n"
+ expected = (u" a ... ああああ\n0 あああああ ... さ\n"
+ u".. ... ... ...\n3 えええ ... せ\n"
u"\n[4 rows x 4 columns]")
assert _rep(df) == expected
df.index = [u'あああ', u'いいいい', u'う', 'aaa']
- expected = (u" a ... ああああ\nあああ あああああ ... さ\n"
- u".. ... ... ...\naaa えええ ... せ\n"
+ expected = (u" a ... ああああ\nあああ あああああ ... さ\n"
+ u".. ... ... ...\naaa えええ ... せ\n"
u"\n[4 rows x 4 columns]")
assert _rep(df) == expected
+ def test_east_asian_unicode_true(self):
+ if PY3:
+ _rep = repr
+ else:
+ _rep = unicode # noqa
+
# Emable Unicode option -----------------------------------------
with option_context('display.unicode.east_asian_width', True):
@@ -757,18 +772,18 @@ def test_east_asian_unicode_frame(self):
u'ああああ': [u'さ', u'し', u'す', u'せ']},
columns=['a', 'b', 'c', u'ああああ'])
- expected = (u" a ... ああああ\n"
- u"0 あああああ ... さ\n"
- u".. ... ... ...\n"
- u"3 えええ ... せ\n"
+ expected = (u" a ... ああああ\n"
+ u"0 あああああ ... さ\n"
+ u".. ... ... ...\n"
+ u"3 えええ ... せ\n"
u"\n[4 rows x 4 columns]")
assert _rep(df) == expected
df.index = [u'あああ', u'いいいい', u'う', 'aaa']
- expected = (u" a ... ああああ\n"
- u"あああ あああああ ... さ\n"
- u"... ... ... ...\n"
- u"aaa えええ ... せ\n"
+ expected = (u" a ... ああああ\n"
+ u"あああ あああああ ... さ\n"
+ u"... ... ... ...\n"
+ u"aaa えええ ... せ\n"
u"\n[4 rows x 4 columns]")
assert _rep(df) == expected
From e2c0b120eb19ecc93a70f9a9c3cb51417cb55d1f Mon Sep 17 00:00:00 2001
From: Joris Van den Bossche <jorisvandenbossche@gmail.com>
Date: Thu, 24 Jan 2019 16:26:06 +0100
Subject: [PATCH 16/48] DOC: also redirect old whatsnew url (#24906)
---
doc/redirects.csv | 4 ++++
1 file changed, 4 insertions(+)
diff --git a/doc/redirects.csv b/doc/redirects.csv
index 4f4b3d7fc0780..e0de03745aaa8 100644
--- a/doc/redirects.csv
+++ b/doc/redirects.csv
@@ -1,6 +1,10 @@
# This file should contain all the redirects in the documentation
# in the format `<old_path>,<new_path>`
+# whatsnew
+whatsnew,whatsnew/index
+release,whatsnew/index
+
# getting started
10min,getting_started/10min
basics,getting_started/basics
From 0a4665a5fe716c28ec2e756611b64efd32d63148 Mon Sep 17 00:00:00 2001
From: Tom Augspurger <TomAugspurger@users.noreply.github.com>
Date: Thu, 24 Jan 2019 10:45:05 -0600
Subject: [PATCH 17/48] Revert BUG-24212 fix usage of Index.take in pd.merge
(#24904)
* Revert BUG-24212 fix usage of Index.take in pd.merge
xref https://github.com/pandas-dev/pandas/pull/24733/
xref https://github.com/pandas-dev/pandas/issues/24897
* test 0.23.4 output
* added note about buggy test
---
doc/source/whatsnew/v0.24.0.rst | 1 -
pandas/core/reshape/merge.py | 41 ++----------------------
pandas/tests/reshape/merge/test_merge.py | 17 ++++++++++
3 files changed, 19 insertions(+), 40 deletions(-)
diff --git a/doc/source/whatsnew/v0.24.0.rst b/doc/source/whatsnew/v0.24.0.rst
index 1c44d35aae4d1..4efe24789af28 100644
--- a/doc/source/whatsnew/v0.24.0.rst
+++ b/doc/source/whatsnew/v0.24.0.rst
@@ -1827,7 +1827,6 @@ Reshaping
- Bug in :func:`DataFrame.unstack` where a ``ValueError`` was raised when unstacking timezone aware values (:issue:`18338`)
- Bug in :func:`DataFrame.stack` where timezone aware values were converted to timezone naive values (:issue:`19420`)
- Bug in :func:`merge_asof` where a ``TypeError`` was raised when ``by_col`` were timezone aware values (:issue:`21184`)
-- Bug in :func:`merge` when merging by index name would sometimes result in an incorrectly numbered index (:issue:`24212`)
- Bug showing an incorrect shape when throwing error during ``DataFrame`` construction. (:issue:`20742`)
.. _whatsnew_0240.bug_fixes.sparse:
diff --git a/pandas/core/reshape/merge.py b/pandas/core/reshape/merge.py
index 0a51f2ee0dce7..e11847d2b8ce2 100644
--- a/pandas/core/reshape/merge.py
+++ b/pandas/core/reshape/merge.py
@@ -757,19 +757,13 @@ def _get_join_info(self):
if self.right_index:
if len(self.left) > 0:
- join_index = self._create_join_index(self.left.index,
- self.right.index,
- left_indexer,
- how='right')
+ join_index = self.left.index.take(left_indexer)
else:
join_index = self.right.index.take(right_indexer)
left_indexer = np.array([-1] * len(join_index))
elif self.left_index:
if len(self.right) > 0:
- join_index = self._create_join_index(self.right.index,
- self.left.index,
- right_indexer,
- how='left')
+ join_index = self.right.index.take(right_indexer)
else:
join_index = self.left.index.take(left_indexer)
right_indexer = np.array([-1] * len(join_index))
@@ -780,37 +774,6 @@ def _get_join_info(self):
join_index = join_index.astype(object)
return join_index, left_indexer, right_indexer
- def _create_join_index(self, index, other_index, indexer, how='left'):
- """
- Create a join index by rearranging one index to match another
-
- Parameters
- ----------
- index: Index being rearranged
- other_index: Index used to supply values not found in index
- indexer: how to rearrange index
- how: replacement is only necessary if indexer based on other_index
-
- Returns
- -------
- join_index
- """
- join_index = index.take(indexer)
- if (self.how in (how, 'outer') and
- not isinstance(other_index, MultiIndex)):
- # if final index requires values in other_index but not target
- # index, indexer may hold missing (-1) values, causing Index.take
- # to take the final value in target index
- mask = indexer == -1
- if np.any(mask):
- # if values missing (-1) from target index,
- # take from other_index instead
- join_list = join_index.to_numpy()
- join_list[mask] = other_index.to_numpy()[mask]
- join_index = Index(join_list, dtype=join_index.dtype,
- name=join_index.name)
- return join_index
-
def _get_merge_keys(self):
"""
Note: has side effects (copy/delete key columns)
diff --git a/pandas/tests/reshape/merge/test_merge.py b/pandas/tests/reshape/merge/test_merge.py
index e123a5171769d..f0a3ddc8ce8a4 100644
--- a/pandas/tests/reshape/merge/test_merge.py
+++ b/pandas/tests/reshape/merge/test_merge.py
@@ -940,6 +940,7 @@ def test_merge_two_empty_df_no_division_error(self):
merge(a, a, on=('a', 'b'))
@pytest.mark.parametrize('how', ['left', 'outer'])
+ @pytest.mark.xfail(reason="GH-24897")
def test_merge_on_index_with_more_values(self, how):
# GH 24212
# pd.merge gets [-1, -1, 0, 1] as right_indexer, ensure that -1 is
@@ -959,6 +960,22 @@ def test_merge_on_index_with_more_values(self, how):
expected.set_index('a', drop=False, inplace=True)
assert_frame_equal(result, expected)
+ def test_merge_right_index_right(self):
+ # Note: the expected output here is probably incorrect.
+ # See https://github.com/pandas-dev/pandas/issues/17257 for more.
+ # We include this as a regression test for GH-24897.
+ left = pd.DataFrame({'a': [1, 2, 3], 'key': [0, 1, 1]})
+ right = pd.DataFrame({'b': [1, 2, 3]})
+
+ expected = pd.DataFrame({'a': [1, 2, 3, None],
+ 'key': [0, 1, 1, 2],
+ 'b': [1, 2, 2, 3]},
+ columns=['a', 'key', 'b'],
+ index=[0, 1, 2, 2])
+ result = left.merge(right, left_on='key', right_index=True,
+ how='right')
+ tm.assert_frame_equal(result, expected)
+
def _check_merge(x, y):
for how in ['inner', 'left', 'outer']:
From fa12b9ecbea36a504249e74579ee2124f98bcc3f Mon Sep 17 00:00:00 2001
From: Tom Augspurger <TomAugspurger@users.noreply.github.com>
Date: Thu, 24 Jan 2019 10:48:54 -0600
Subject: [PATCH 18/48] DOC: Add experimental note to DatetimeArray and
TimedeltaArray (#24882)
* DOC: Add experimental note to DatetimeArray and TimedeltaArray
---
doc/source/user_guide/integer_na.rst | 6 +++++
doc/source/whatsnew/v0.24.0.rst | 8 ++++++
pandas/core/arrays/datetimes.py | 13 ++++++++++
pandas/core/arrays/integer.py | 39 +++++++++++++++++++++++++---
pandas/core/arrays/timedeltas.py | 36 +++++++++++++++++++++++++
5 files changed, 99 insertions(+), 3 deletions(-)
diff --git a/doc/source/user_guide/integer_na.rst b/doc/source/user_guide/integer_na.rst
index eb0c5e3d05863..c5667e9319ca6 100644
--- a/doc/source/user_guide/integer_na.rst
+++ b/doc/source/user_guide/integer_na.rst
@@ -10,6 +10,12 @@ Nullable Integer Data Type
.. versionadded:: 0.24.0
+.. note::
+
+ IntegerArray is currently experimental. Its API or implementation may
+ change without warning.
+
+
In :ref:`missing_data`, we saw that pandas primarily uses ``NaN`` to represent
missing data. Because ``NaN`` is a float, this forces an array of integers with
any missing values to become floating point. In some cases, this may not matter
diff --git a/doc/source/whatsnew/v0.24.0.rst b/doc/source/whatsnew/v0.24.0.rst
index 4efe24789af28..3b3fad22ce949 100644
--- a/doc/source/whatsnew/v0.24.0.rst
+++ b/doc/source/whatsnew/v0.24.0.rst
@@ -32,6 +32,11 @@ Optional Integer NA Support
Pandas has gained the ability to hold integer dtypes with missing values. This long requested feature is enabled through the use of :ref:`extension types <extending.extension-types>`.
Here is an example of the usage.
+.. note::
+
+ IntegerArray is currently experimental. Its API or implementation may
+ change without warning.
+
We can construct a ``Series`` with the specified dtype. The dtype string ``Int64`` is a pandas ``ExtensionDtype``. Specifying a list or array using the traditional missing value
marker of ``np.nan`` will infer to integer dtype. The display of the ``Series`` will also use the ``NaN`` to indicate missing values in string outputs. (:issue:`20700`, :issue:`20747`, :issue:`22441`, :issue:`21789`, :issue:`22346`)
@@ -213,6 +218,9 @@ from the ``Series``:
ser.array
pser.array
+These return an instance of :class:`IntervalArray` or :class:`arrays.PeriodArray`,
+the new extension arrays that back interval and period data.
+
.. warning::
For backwards compatibility, :attr:`Series.values` continues to return
diff --git a/pandas/core/arrays/datetimes.py b/pandas/core/arrays/datetimes.py
index f2aeb1c1309de..d7a8417a71be2 100644
--- a/pandas/core/arrays/datetimes.py
+++ b/pandas/core/arrays/datetimes.py
@@ -218,6 +218,13 @@ class DatetimeArray(dtl.DatetimeLikeArrayMixin,
.. versionadded:: 0.24.0
+ .. warning::
+
+ DatetimeArray is currently experimental, and its API may change
+ without warning. In particular, :attr:`DatetimeArray.dtype` is
+ expected to change to always be an instance of an ``ExtensionDtype``
+ subclass.
+
Parameters
----------
values : Series, Index, DatetimeArray, ndarray
@@ -511,6 +518,12 @@ def dtype(self):
"""
The dtype for the DatetimeArray.
+ .. warning::
+
+ A future version of pandas will change dtype to never be a
+ ``numpy.dtype``. Instead, :attr:`DatetimeArray.dtype` will
+ always be an instance of an ``ExtensionDtype`` subclass.
+
Returns
-------
numpy.dtype or DatetimeTZDtype
diff --git a/pandas/core/arrays/integer.py b/pandas/core/arrays/integer.py
index b3dde6bf2bd93..a6a4a49d3a939 100644
--- a/pandas/core/arrays/integer.py
+++ b/pandas/core/arrays/integer.py
@@ -225,24 +225,57 @@ class IntegerArray(ExtensionArray, ExtensionOpsMixin):
"""
Array of integer (optional missing) values.
+ .. versionadded:: 0.24.0
+
+ .. warning::
+
+ IntegerArray is currently experimental, and its API or internal
+ implementation may change without warning.
+
We represent an IntegerArray with 2 numpy arrays:
- data: contains a numpy integer array of the appropriate dtype
- mask: a boolean array holding a mask on the data, True is missing
To construct an IntegerArray from generic array-like input, use
- ``integer_array`` function instead.
+ :func:`pandas.array` with one of the integer dtypes (see examples).
+
+ See :ref:`integer_na` for more.
Parameters
----------
- values : integer 1D numpy array
- mask : boolean 1D numpy array
+ values : numpy.ndarray
+ A 1-d integer-dtype array.
+ mask : numpy.ndarray
+ A 1-d boolean-dtype array indicating missing values.
copy : bool, default False
+ Whether to copy the `values` and `mask`.
Returns
-------
IntegerArray
+ Examples
+ --------
+ Create an IntegerArray with :func:`pandas.array`.
+
+ >>> int_array = pd.array([1, None, 3], dtype=pd.Int32Dtype())
+ >>> int_array
+ <IntegerArray>
+ [1, NaN, 3]
+ Length: 3, dtype: Int32
+
+ String aliases for the dtypes are also available. They are capitalized.
+
+ >>> pd.array([1, None, 3], dtype='Int32')
+ <IntegerArray>
+ [1, NaN, 3]
+ Length: 3, dtype: Int32
+
+ >>> pd.array([1, None, 3], dtype='UInt16')
+ <IntegerArray>
+ [1, NaN, 3]
+ Length: 3, dtype: UInt16
"""
@cache_readonly
diff --git a/pandas/core/arrays/timedeltas.py b/pandas/core/arrays/timedeltas.py
index 910cb96a86216..4f0c96f7927da 100644
--- a/pandas/core/arrays/timedeltas.py
+++ b/pandas/core/arrays/timedeltas.py
@@ -107,6 +107,29 @@ def wrapper(self, other):
class TimedeltaArray(dtl.DatetimeLikeArrayMixin, dtl.TimelikeOps):
+ """
+ Pandas ExtensionArray for timedelta data.
+
+ .. versionadded:: 0.24.0
+
+ .. warning::
+
+ TimedeltaArray is currently experimental, and its API may change
+ without warning. In particular, :attr:`TimedeltaArray.dtype` is
+ expected to change to be an instance of an ``ExtensionDtype``
+ subclass.
+
+ Parameters
+ ----------
+ values : array-like
+ The timedelta data.
+
+ dtype : numpy.dtype
+ Currently, only ``numpy.dtype("timedelta64[ns]")`` is accepted.
+ freq : Offset, optional
+ copy : bool, default False
+ Whether to copy the underlying array of data.
+ """
_typ = "timedeltaarray"
_scalar_type = Timedelta
__array_priority__ = 1000
@@ -128,6 +151,19 @@ def _box_func(self):
@property
def dtype(self):
+ """
+ The dtype for the TimedeltaArray.
+
+ .. warning::
+
+ A future version of pandas will change dtype to be an instance
+ of a :class:`pandas.api.extensions.ExtensionDtype` subclass,
+ not a ``numpy.dtype``.
+
+ Returns
+ -------
+ numpy.dtype
+ """
return _TD_DTYPE
# ----------------------------------------------------------------
From 5761e359b65631db491349a65fc21d0da51dcc0f Mon Sep 17 00:00:00 2001
From: Tom Augspurger <TomAugspurger@users.noreply.github.com>
Date: Thu, 24 Jan 2019 13:01:23 -0600
Subject: [PATCH 19/48] Disable M8 in nanops (#24907)
* Disable M8 in nanops
Closes https://github.com/pandas-dev/pandas/issues/24752
---
pandas/core/nanops.py | 6 ++++--
pandas/tests/frame/test_analytics.py | 19 +++++++++++++++++++
pandas/tests/test_nanops.py | 3 +++
3 files changed, 26 insertions(+), 2 deletions(-)
diff --git a/pandas/core/nanops.py b/pandas/core/nanops.py
index cafd3a9915fa0..86c3c380636c9 100644
--- a/pandas/core/nanops.py
+++ b/pandas/core/nanops.py
@@ -14,7 +14,8 @@
_get_dtype, is_any_int_dtype, is_bool_dtype, is_complex, is_complex_dtype,
is_datetime64_dtype, is_datetime64tz_dtype, is_datetime_or_timedelta_dtype,
is_float, is_float_dtype, is_integer, is_integer_dtype, is_numeric_dtype,
- is_object_dtype, is_scalar, is_timedelta64_dtype)
+ is_object_dtype, is_scalar, is_timedelta64_dtype, pandas_dtype)
+from pandas.core.dtypes.dtypes import DatetimeTZDtype
from pandas.core.dtypes.missing import isna, na_value_for_dtype, notna
import pandas.core.common as com
@@ -57,7 +58,7 @@ class disallow(object):
def __init__(self, *dtypes):
super(disallow, self).__init__()
- self.dtypes = tuple(np.dtype(dtype).type for dtype in dtypes)
+ self.dtypes = tuple(pandas_dtype(dtype).type for dtype in dtypes)
def check(self, obj):
return hasattr(obj, 'dtype') and issubclass(obj.dtype.type,
@@ -437,6 +438,7 @@ def nansum(values, axis=None, skipna=True, min_count=0, mask=None):
return _wrap_results(the_sum, dtype)
+@disallow('M8', DatetimeTZDtype)
@bottleneck_switch()
def nanmean(values, axis=None, skipna=True, mask=None):
"""
diff --git a/pandas/tests/frame/test_analytics.py b/pandas/tests/frame/test_analytics.py
index f2c3f50c291c3..386e5f57617cf 100644
--- a/pandas/tests/frame/test_analytics.py
+++ b/pandas/tests/frame/test_analytics.py
@@ -794,6 +794,25 @@ def test_mean(self, float_frame_with_na, float_frame, float_string_frame):
check_dates=True)
assert_stat_op_api('mean', float_frame, float_string_frame)
+ @pytest.mark.parametrize('tz', [None, 'UTC'])
+ def test_mean_mixed_datetime_numeric(self, tz):
+ # https://github.com/pandas-dev/pandas/issues/24752
+ df = pd.DataFrame({"A": [1, 1],
+ "B": [pd.Timestamp('2000', tz=tz)] * 2})
+ result = df.mean()
+ expected = pd.Series([1.0], index=['A'])
+ tm.assert_series_equal(result, expected)
+
+ @pytest.mark.parametrize('tz', [None, 'UTC'])
+ def test_mean_excludeds_datetimes(self, tz):
+ # https://github.com/pandas-dev/pandas/issues/24752
+ # Our long-term desired behavior is unclear, but the behavior in
+ # 0.24.0rc1 was buggy.
+ df = pd.DataFrame({"A": [pd.Timestamp('2000', tz=tz)] * 2})
+ result = df.mean()
+ expected = pd.Series()
+ tm.assert_series_equal(result, expected)
+
def test_product(self, float_frame_with_na, float_frame,
float_string_frame):
assert_stat_op_calc('product', np.prod, float_frame_with_na)
diff --git a/pandas/tests/test_nanops.py b/pandas/tests/test_nanops.py
index 4bcd16a86e865..cf5ef6cf15eca 100644
--- a/pandas/tests/test_nanops.py
+++ b/pandas/tests/test_nanops.py
@@ -971,6 +971,9 @@ def prng(self):
class TestDatetime64NaNOps(object):
@pytest.mark.parametrize('tz', [None, 'UTC'])
+ @pytest.mark.xfail(reason="disabled")
+ # Enabling mean changes the behavior of DataFrame.mean
+ # See https://github.com/pandas-dev/pandas/issues/24752
def test_nanmean(self, tz):
dti = pd.date_range('2016-01-01', periods=3, tz=tz)
expected = dti[1]
From 539c54f30736b4163b70f1ba903aee7a4243ab1f Mon Sep 17 00:00:00 2001
From: Christopher Whelan <topherwhelan@gmail.com>
Date: Thu, 24 Jan 2019 18:26:45 -0800
Subject: [PATCH 20/48] CLN: fix typo in asv benchmark of non_unique_sorted,
which was not sorted (#24917)
---
asv_bench/benchmarks/index_object.py | 3 ++-
1 file changed, 2 insertions(+), 1 deletion(-)
diff --git a/asv_bench/benchmarks/index_object.py b/asv_bench/benchmarks/index_object.py
index f76040921393f..bbe164d4858ab 100644
--- a/asv_bench/benchmarks/index_object.py
+++ b/asv_bench/benchmarks/index_object.py
@@ -138,7 +138,8 @@ def setup(self, dtype):
self.sorted = self.idx.sort_values()
half = N // 2
self.non_unique = self.idx[:half].append(self.idx[:half])
- self.non_unique_sorted = self.sorted[:half].append(self.sorted[:half])
+ self.non_unique_sorted = (self.sorted[:half].append(self.sorted[:half])
+ .sort_values())
self.key = self.sorted[N // 4]
def time_boolean_array(self, dtype):
From f971b11024362c797fd5e83ea2f2b708157e39c8 Mon Sep 17 00:00:00 2001
From: Joris Van den Bossche <jorisvandenbossche@gmail.com>
Date: Fri, 25 Jan 2019 08:10:40 +0100
Subject: [PATCH 21/48] API/VIS: remove misc plotting methods from plot
accessor (revert #23811) (#24912)
---
doc/source/whatsnew/v0.24.0.rst | 1 -
pandas/plotting/_core.py | 23 -----------------------
pandas/tests/plotting/test_frame.py | 16 ----------------
pandas/tests/plotting/test_series.py | 13 -------------
4 files changed, 53 deletions(-)
diff --git a/doc/source/whatsnew/v0.24.0.rst b/doc/source/whatsnew/v0.24.0.rst
index 3b3fad22ce949..e7c9a4752db06 100644
--- a/doc/source/whatsnew/v0.24.0.rst
+++ b/doc/source/whatsnew/v0.24.0.rst
@@ -429,7 +429,6 @@ Other Enhancements
- :meth:`MultiIndex.to_flat_index` has been added to flatten multiple levels into a single-level :class:`Index` object.
- :meth:`DataFrame.to_stata` and :class:`pandas.io.stata.StataWriter117` can write mixed sting columns to Stata strl format (:issue:`23633`)
- :meth:`DataFrame.between_time` and :meth:`DataFrame.at_time` have gained the ``axis`` parameter (:issue:`8839`)
-- The ``scatter_matrix``, ``andrews_curves``, ``parallel_coordinates``, ``lag_plot``, ``autocorrelation_plot``, ``bootstrap_plot``, and ``radviz`` plots from the ``pandas.plotting`` module are now accessible from calling :meth:`DataFrame.plot` (:issue:`11978`)
- :meth:`DataFrame.to_records` now accepts ``index_dtypes`` and ``column_dtypes`` parameters to allow different data types in stored column and index records (:issue:`18146`)
- :class:`IntervalIndex` has gained the :attr:`~IntervalIndex.is_overlapping` attribute to indicate if the ``IntervalIndex`` contains any overlapping intervals (:issue:`23309`)
- :func:`pandas.DataFrame.to_sql` has gained the ``method`` argument to control SQL insertion clause. See the :ref:`insertion method <io.sql.method>` section in the documentation. (:issue:`8953`)
diff --git a/pandas/plotting/_core.py b/pandas/plotting/_core.py
index 3ba06c0638317..e543ab88f53b2 100644
--- a/pandas/plotting/_core.py
+++ b/pandas/plotting/_core.py
@@ -26,7 +26,6 @@
from pandas.core.generic import _shared_doc_kwargs, _shared_docs
from pandas.io.formats.printing import pprint_thing
-from pandas.plotting import _misc as misc
from pandas.plotting._compat import _mpl_ge_3_0_0
from pandas.plotting._style import _get_standard_colors, plot_params
from pandas.plotting._tools import (
@@ -2906,15 +2905,6 @@ def pie(self, **kwds):
"""
return self(kind='pie', **kwds)
- def lag(self, *args, **kwds):
- return misc.lag_plot(self._parent, *args, **kwds)
-
- def autocorrelation(self, *args, **kwds):
- return misc.autocorrelation_plot(self._parent, *args, **kwds)
-
- def bootstrap(self, *args, **kwds):
- return misc.bootstrap_plot(self._parent, *args, **kwds)
-
class FramePlotMethods(BasePlotMethods):
"""DataFrame plotting accessor and method
@@ -3610,16 +3600,3 @@ def hexbin(self, x, y, C=None, reduce_C_function=None, gridsize=None,
if gridsize is not None:
kwds['gridsize'] = gridsize
return self(kind='hexbin', x=x, y=y, C=C, **kwds)
-
- def scatter_matrix(self, *args, **kwds):
- return misc.scatter_matrix(self._parent, *args, **kwds)
-
- def andrews_curves(self, class_column, *args, **kwds):
- return misc.andrews_curves(self._parent, class_column, *args, **kwds)
-
- def parallel_coordinates(self, class_column, *args, **kwds):
- return misc.parallel_coordinates(self._parent, class_column,
- *args, **kwds)
-
- def radviz(self, class_column, *args, **kwds):
- return misc.radviz(self._parent, class_column, *args, **kwds)
diff --git a/pandas/tests/plotting/test_frame.py b/pandas/tests/plotting/test_frame.py
index 0e7672f4e2f9d..98b241f5c8206 100644
--- a/pandas/tests/plotting/test_frame.py
+++ b/pandas/tests/plotting/test_frame.py
@@ -2988,22 +2988,6 @@ def test_secondary_axis_font_size(self, method):
self._check_ticks_props(axes=ax.right_ax,
ylabelsize=fontsize)
- def test_misc_bindings(self, monkeypatch):
- df = pd.DataFrame(randn(10, 10), columns=list('abcdefghij'))
- monkeypatch.setattr('pandas.plotting._misc.scatter_matrix',
- lambda x: 2)
- monkeypatch.setattr('pandas.plotting._misc.andrews_curves',
- lambda x, y: 2)
- monkeypatch.setattr('pandas.plotting._misc.parallel_coordinates',
- lambda x, y: 2)
- monkeypatch.setattr('pandas.plotting._misc.radviz',
- lambda x, y: 2)
-
- assert df.plot.scatter_matrix() == 2
- assert df.plot.andrews_curves('a') == 2
- assert df.plot.parallel_coordinates('a') == 2
- assert df.plot.radviz('a') == 2
-
def _generate_4_axes_via_gridspec():
import matplotlib.pyplot as plt
diff --git a/pandas/tests/plotting/test_series.py b/pandas/tests/plotting/test_series.py
index 1e223c20f55b7..07a4b168a66f1 100644
--- a/pandas/tests/plotting/test_series.py
+++ b/pandas/tests/plotting/test_series.py
@@ -878,19 +878,6 @@ def test_custom_business_day_freq(self):
_check_plot_works(s.plot)
- def test_misc_bindings(self, monkeypatch):
- s = Series(randn(10))
- monkeypatch.setattr('pandas.plotting._misc.lag_plot',
- lambda x: 2)
- monkeypatch.setattr('pandas.plotting._misc.autocorrelation_plot',
- lambda x: 2)
- monkeypatch.setattr('pandas.plotting._misc.bootstrap_plot',
- lambda x: 2)
-
- assert s.plot.lag() == 2
- assert s.plot.autocorrelation() == 2
- assert s.plot.bootstrap() == 2
-
@pytest.mark.xfail
def test_plot_accessor_updates_on_inplace(self):
s = Series([1, 2, 3, 4])
From bb86a9d3708c3ddf1f301d7988128e84518d0cce Mon Sep 17 00:00:00 2001
From: Joris Van den Bossche <jorisvandenbossche@gmail.com>
Date: Fri, 25 Jan 2019 09:45:35 +0100
Subject: [PATCH 22/48] DOC: some 0.24.0 whatsnew clean-up (#24911)
---
doc/source/whatsnew/v0.24.0.rst | 116 +++++++++++++++++---------------
1 file changed, 62 insertions(+), 54 deletions(-)
diff --git a/doc/source/whatsnew/v0.24.0.rst b/doc/source/whatsnew/v0.24.0.rst
index e7c9a4752db06..f0f99d2def136 100644
--- a/doc/source/whatsnew/v0.24.0.rst
+++ b/doc/source/whatsnew/v0.24.0.rst
@@ -10,27 +10,34 @@ What's New in 0.24.0 (January XX, 2019)
{{ header }}
-These are the changes in pandas 0.24.0. See :ref:`release` for a full changelog
-including other versions of pandas.
+This is a major release from 0.23.4 and includes a number of API changes, new
+features, enhancements, and performance improvements along with a large number
+of bug fixes.
-Enhancements
-~~~~~~~~~~~~
+Highlights include:
-Highlights include
-
-* :ref:`Optional Nullable Integer Support <whatsnew_0240.enhancements.intna>`
+* :ref:`Optional Integer NA Support <whatsnew_0240.enhancements.intna>`
* :ref:`New APIs for accessing the array backing a Series or Index <whatsnew_0240.values_api>`
* :ref:`A new top-level method for creating arrays <whatsnew_0240.enhancements.array>`
* :ref:`Store Interval and Period data in a Series or DataFrame <whatsnew_0240.enhancements.interval>`
* :ref:`Support for joining on two MultiIndexes <whatsnew_0240.enhancements.join_with_two_multiindexes>`
+
+Check the :ref:`API Changes <whatsnew_0240.api_breaking>` and :ref:`deprecations <whatsnew_0240.deprecations>` before updating.
+
+These are the changes in pandas 0.24.0. See :ref:`release` for a full changelog
+including other versions of pandas.
+
+
+Enhancements
+~~~~~~~~~~~~
+
.. _whatsnew_0240.enhancements.intna:
Optional Integer NA Support
^^^^^^^^^^^^^^^^^^^^^^^^^^^
Pandas has gained the ability to hold integer dtypes with missing values. This long requested feature is enabled through the use of :ref:`extension types <extending.extension-types>`.
-Here is an example of the usage.
.. note::
@@ -65,7 +72,7 @@ Operations on these dtypes will propagate ``NaN`` as other pandas operations.
# coerce when needed
s + 0.01
-These dtypes can operate as part of of ``DataFrame``.
+These dtypes can operate as part of a ``DataFrame``.
.. ipython:: python
@@ -74,7 +81,7 @@ These dtypes can operate as part of of ``DataFrame``.
df.dtypes
-These dtypes can be merged & reshaped & casted.
+These dtypes can be merged, reshaped, and casted.
.. ipython:: python
@@ -117,6 +124,7 @@ a new ndarray of period objects each time.
.. ipython:: python
+ idx.values
id(idx.values)
id(idx.values)
@@ -129,7 +137,7 @@ If you need an actual NumPy array, use :meth:`Series.to_numpy` or :meth:`Index.t
For Series and Indexes backed by normal NumPy arrays, :attr:`Series.array` will return a
new :class:`arrays.PandasArray`, which is a thin (no-copy) wrapper around a
-:class:`numpy.ndarray`. :class:`arrays.PandasArray` isn't especially useful on its own,
+:class:`numpy.ndarray`. :class:`~arrays.PandasArray` isn't especially useful on its own,
but it does provide the same interface as any extension array defined in pandas or by
a third-party library.
@@ -147,14 +155,13 @@ See :ref:`Dtypes <basics.dtypes>` and :ref:`Attributes and Underlying Data <basi
.. _whatsnew_0240.enhancements.array:
-Array
-^^^^^
+``pandas.array``: a new top-level method for creating arrays
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
A new top-level method :func:`array` has been added for creating 1-dimensional arrays (:issue:`22860`).
This can be used to create any :ref:`extension array <extending.extension-types>`, including
-extension arrays registered by :ref:`3rd party libraries <ecosystem.extensions>`. See
-
-See :ref:`Dtypes <basics.dtypes>` for more on extension arrays.
+extension arrays registered by :ref:`3rd party libraries <ecosystem.extensions>`.
+See the :ref:`dtypes docs <basics.dtypes>` for more on extension arrays.
.. ipython:: python
@@ -163,15 +170,15 @@ See :ref:`Dtypes <basics.dtypes>` for more on extension arrays.
Passing data for which there isn't dedicated extension type (e.g. float, integer, etc.)
will return a new :class:`arrays.PandasArray`, which is just a thin (no-copy)
-wrapper around a :class:`numpy.ndarray` that satisfies the extension array interface.
+wrapper around a :class:`numpy.ndarray` that satisfies the pandas extension array interface.
.. ipython:: python
pd.array([1, 2, 3])
-On their own, a :class:`arrays.PandasArray` isn't a very useful object.
+On their own, a :class:`~arrays.PandasArray` isn't a very useful object.
But if you need write low-level code that works generically for any
-:class:`~pandas.api.extensions.ExtensionArray`, :class:`arrays.PandasArray`
+:class:`~pandas.api.extensions.ExtensionArray`, :class:`~arrays.PandasArray`
satisfies that need.
Notice that by default, if no ``dtype`` is specified, the dtype of the returned
@@ -202,7 +209,7 @@ For periods:
.. ipython:: python
- pser = pd.Series(pd.date_range("2000", freq="D", periods=5))
+ pser = pd.Series(pd.period_range("2000", freq="D", periods=5))
pser
pser.dtype
@@ -267,23 +274,6 @@ For earlier versions this can be done using the following.
pd.merge(left.reset_index(), right.reset_index(),
on=['key'], how='inner').set_index(['key', 'X', 'Y'])
-
-.. _whatsnew_0240.enhancements.extension_array_operators:
-
-``ExtensionArray`` operator support
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-
-A ``Series`` based on an ``ExtensionArray`` now supports arithmetic and comparison
-operators (:issue:`19577`). There are two approaches for providing operator support for an ``ExtensionArray``:
-
-1. Define each of the operators on your ``ExtensionArray`` subclass.
-2. Use an operator implementation from pandas that depends on operators that are already defined
- on the underlying elements (scalars) of the ``ExtensionArray``.
-
-See the :ref:`ExtensionArray Operator Support
-<extending.extension.operator>` documentation section for details on both
-ways of adding operator support.
-
.. _whatsnew_0240.enhancements.read_html:
``read_html`` Enhancements
@@ -343,7 +333,7 @@ convenient way to apply users' predefined styling functions, and can help reduce
df.style.pipe(format_and_align).set_caption('Summary of results.')
Similar methods already exist for other classes in pandas, including :meth:`DataFrame.pipe`,
-:meth:`pandas.core.groupby.GroupBy.pipe`, and :meth:`pandas.core.resample.Resampler.pipe`.
+:meth:`GroupBy.pipe() <pandas.core.groupby.GroupBy.pipe>`, and :meth:`Resampler.pipe() <pandas.core.resample.Resampler.pipe>`.
.. _whatsnew_0240.enhancements.rename_axis:
@@ -351,7 +341,7 @@ Renaming names in a MultiIndex
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
:func:`DataFrame.rename_axis` now supports ``index`` and ``columns`` arguments
-and :func:`Series.rename_axis` supports ``index`` argument (:issue:`19978`)
+and :func:`Series.rename_axis` supports ``index`` argument (:issue:`19978`).
This change allows a dictionary to be passed so that some of the names
of a ``MultiIndex`` can be changed.
@@ -379,13 +369,13 @@ Other Enhancements
- :func:`DataFrame.to_parquet` now accepts ``index`` as an argument, allowing
the user to override the engine's default behavior to include or omit the
dataframe's indexes from the resulting Parquet file. (:issue:`20768`)
+- :func:`read_feather` now accepts ``columns`` as an argument, allowing the user to specify which columns should be read. (:issue:`24025`)
- :meth:`DataFrame.corr` and :meth:`Series.corr` now accept a callable for generic calculation methods of correlation, e.g. histogram intersection (:issue:`22684`)
- :func:`DataFrame.to_string` now accepts ``decimal`` as an argument, allowing the user to specify which decimal separator should be used in the output. (:issue:`23614`)
-- :func:`read_feather` now accepts ``columns`` as an argument, allowing the user to specify which columns should be read. (:issue:`24025`)
- :func:`DataFrame.to_html` now accepts ``render_links`` as an argument, allowing the user to generate HTML with links to any URLs that appear in the DataFrame.
See the :ref:`section on writing HTML <io.html>` in the IO docs for example usage. (:issue:`2679`)
- :func:`pandas.read_csv` now supports pandas extension types as an argument to ``dtype``, allowing the user to use pandas extension types when reading CSVs. (:issue:`23228`)
-- :meth:`DataFrame.shift` :meth:`Series.shift`, :meth:`ExtensionArray.shift`, :meth:`SparseArray.shift`, :meth:`Period.shift`, :meth:`GroupBy.shift`, :meth:`Categorical.shift`, :meth:`NDFrame.shift` and :meth:`Block.shift` now accept `fill_value` as an argument, allowing the user to specify a value which will be used instead of NA/NaT in the empty periods. (:issue:`15486`)
+- The :meth:`~DataFrame.shift` method now accepts `fill_value` as an argument, allowing the user to specify a value which will be used instead of NA/NaT in the empty periods. (:issue:`15486`)
- :func:`to_datetime` now supports the ``%Z`` and ``%z`` directive when passed into ``format`` (:issue:`13486`)
- :func:`Series.mode` and :func:`DataFrame.mode` now support the ``dropna`` parameter which can be used to specify whether ``NaN``/``NaT`` values should be considered (:issue:`17534`)
- :func:`DataFrame.to_csv` and :func:`Series.to_csv` now support the ``compression`` keyword when a file handle is passed. (:issue:`21227`)
@@ -407,18 +397,19 @@ Other Enhancements
The default compression for ``to_csv``, ``to_json``, and ``to_pickle`` methods has been updated to ``'infer'`` (:issue:`22004`).
- :meth:`DataFrame.to_sql` now supports writing ``TIMESTAMP WITH TIME ZONE`` types for supported databases. For databases that don't support timezones, datetime data will be stored as timezone unaware local timestamps. See the :ref:`io.sql_datetime_data` for implications (:issue:`9086`).
- :func:`to_timedelta` now supports iso-formated timedelta strings (:issue:`21877`)
-- :class:`Series` and :class:`DataFrame` now support :class:`Iterable` in constructor (:issue:`2193`)
+- :class:`Series` and :class:`DataFrame` now support :class:`Iterable` objects in the constructor (:issue:`2193`)
- :class:`DatetimeIndex` has gained the :attr:`DatetimeIndex.timetz` attribute. This returns the local time with timezone information. (:issue:`21358`)
-- :meth:`Timestamp.round`, :meth:`Timestamp.ceil`, and :meth:`Timestamp.floor` for :class:`DatetimeIndex` and :class:`Timestamp` now support an ``ambiguous`` argument for handling datetimes that are rounded to ambiguous times (:issue:`18946`)
-- :meth:`Timestamp.round`, :meth:`Timestamp.ceil`, and :meth:`Timestamp.floor` for :class:`DatetimeIndex` and :class:`Timestamp` now support a ``nonexistent`` argument for handling datetimes that are rounded to nonexistent times. See :ref:`timeseries.timezone_nonexistent` (:issue:`22647`)
-- :class:`pandas.core.resample.Resampler` now is iterable like :class:`pandas.core.groupby.GroupBy` (:issue:`15314`).
+- :meth:`~Timestamp.round`, :meth:`~Timestamp.ceil`, and :meth:`~Timestamp.floor` for :class:`DatetimeIndex` and :class:`Timestamp`
+ now support an ``ambiguous`` argument for handling datetimes that are rounded to ambiguous times (:issue:`18946`)
+ and a ``nonexistent`` argument for handling datetimes that are rounded to nonexistent times. See :ref:`timeseries.timezone_nonexistent` (:issue:`22647`)
+- The result of :meth:`~DataFrame.resample` is now iterable similar to ``groupby()`` (:issue:`15314`).
- :meth:`Series.resample` and :meth:`DataFrame.resample` have gained the :meth:`pandas.core.resample.Resampler.quantile` (:issue:`15023`).
- :meth:`DataFrame.resample` and :meth:`Series.resample` with a :class:`PeriodIndex` will now respect the ``base`` argument in the same fashion as with a :class:`DatetimeIndex`. (:issue:`23882`)
- :meth:`pandas.api.types.is_list_like` has gained a keyword ``allow_sets`` which is ``True`` by default; if ``False``,
all instances of ``set`` will not be considered "list-like" anymore (:issue:`23061`)
- :meth:`Index.to_frame` now supports overriding column name(s) (:issue:`22580`).
- :meth:`Categorical.from_codes` now can take a ``dtype`` parameter as an alternative to passing ``categories`` and ``ordered`` (:issue:`24398`).
-- New attribute :attr:`__git_version__` will return git commit sha of current build (:issue:`21295`).
+- New attribute ``__git_version__`` will return git commit sha of current build (:issue:`21295`).
- Compatibility with Matplotlib 3.0 (:issue:`22790`).
- Added :meth:`Interval.overlaps`, :meth:`IntervalArray.overlaps`, and :meth:`IntervalIndex.overlaps` for determining overlaps between interval-like objects (:issue:`21998`)
- :func:`read_fwf` now accepts keyword ``infer_nrows`` (:issue:`15138`).
@@ -433,7 +424,7 @@ Other Enhancements
- :class:`IntervalIndex` has gained the :attr:`~IntervalIndex.is_overlapping` attribute to indicate if the ``IntervalIndex`` contains any overlapping intervals (:issue:`23309`)
- :func:`pandas.DataFrame.to_sql` has gained the ``method`` argument to control SQL insertion clause. See the :ref:`insertion method <io.sql.method>` section in the documentation. (:issue:`8953`)
- :meth:`DataFrame.corrwith` now supports Spearman's rank correlation, Kendall's tau as well as callable correlation methods. (:issue:`21925`)
-- :meth:`DataFrame.to_json`, :meth:`DataFrame.to_csv`, :meth:`DataFrame.to_pickle`, and :meth:`DataFrame.to_XXX` etc. now support tilde(~) in path argument. (:issue:`23473`)
+- :meth:`DataFrame.to_json`, :meth:`DataFrame.to_csv`, :meth:`DataFrame.to_pickle`, and other export methods now support tilde(~) in path argument. (:issue:`23473`)
.. _whatsnew_0240.api_breaking:
@@ -445,8 +436,8 @@ Pandas 0.24.0 includes a number of API breaking changes.
.. _whatsnew_0240.api_breaking.deps:
-Dependencies have increased minimum versions
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+Increased minimum versions for dependencies
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
We have updated our minimum supported versions of dependencies (:issue:`21242`, :issue:`18742`, :issue:`23774`, :issue:`24767`).
If installed, we now require:
@@ -1174,17 +1165,19 @@ Other API Changes
.. _whatsnew_0240.api.extension:
-ExtensionType Changes
-~~~~~~~~~~~~~~~~~~~~~
+Extension Type Changes
+~~~~~~~~~~~~~~~~~~~~~~
**Equality and Hashability**
-Pandas now requires that extension dtypes be hashable. The base class implements
+Pandas now requires that extension dtypes be hashable (i.e. the respective
+``ExtensionDtype`` objects; hashability is not a requirement for the values
+of the corresponding ``ExtensionArray``). The base class implements
a default ``__eq__`` and ``__hash__``. If you have a parametrized dtype, you should
update the ``ExtensionDtype._metadata`` tuple to match the signature of your
``__init__`` method. See :class:`pandas.api.extensions.ExtensionDtype` for more (:issue:`22476`).
-**Reshaping changes**
+**New and changed methods**
- :meth:`~pandas.api.types.ExtensionArray.dropna` has been added (:issue:`21185`)
- :meth:`~pandas.api.types.ExtensionArray.repeat` has been added (:issue:`24349`)
@@ -1202,9 +1195,25 @@ update the ``ExtensionDtype._metadata`` tuple to match the signature of your
- Added :meth:`pandas.api.types.register_extension_dtype` to register an extension type with pandas (:issue:`22664`)
- Updated the ``.type`` attribute for ``PeriodDtype``, ``DatetimeTZDtype``, and ``IntervalDtype`` to be instances of the dtype (``Period``, ``Timestamp``, and ``Interval`` respectively) (:issue:`22938`)
+.. _whatsnew_0240.enhancements.extension_array_operators:
+
+**Operator support**
+
+A ``Series`` based on an ``ExtensionArray`` now supports arithmetic and comparison
+operators (:issue:`19577`). There are two approaches for providing operator support for an ``ExtensionArray``:
+
+1. Define each of the operators on your ``ExtensionArray`` subclass.
+2. Use an operator implementation from pandas that depends on operators that are already defined
+ on the underlying elements (scalars) of the ``ExtensionArray``.
+
+See the :ref:`ExtensionArray Operator Support
+<extending.extension.operator>` documentation section for details on both
+ways of adding operator support.
+
**Other changes**
- A default repr for :class:`pandas.api.extensions.ExtensionArray` is now provided (:issue:`23601`).
+- :meth:`ExtensionArray._formatting_values` is deprecated. Use :attr:`ExtensionArray._formatter` instead. (:issue:`23601`)
- An ``ExtensionArray`` with a boolean dtype now works correctly as a boolean indexer. :meth:`pandas.api.types.is_bool_dtype` now properly considers them boolean (:issue:`22326`)
**Bug Fixes**
@@ -1253,7 +1262,6 @@ Deprecations
- The methods :meth:`DataFrame.update` and :meth:`Panel.update` have deprecated the ``raise_conflict=False|True`` keyword in favor of ``errors='ignore'|'raise'`` (:issue:`23585`)
- The methods :meth:`Series.str.partition` and :meth:`Series.str.rpartition` have deprecated the ``pat`` keyword in favor of ``sep`` (:issue:`22676`)
- Deprecated the ``nthreads`` keyword of :func:`pandas.read_feather` in favor of ``use_threads`` to reflect the changes in ``pyarrow>=0.11.0``. (:issue:`23053`)
-- :meth:`ExtensionArray._formatting_values` is deprecated. Use :attr:`ExtensionArray._formatter` instead. (:issue:`23601`)
- :func:`pandas.read_excel` has deprecated accepting ``usecols`` as an integer. Please pass in a list of ints from 0 to ``usecols`` inclusive instead (:issue:`23527`)
- Constructing a :class:`TimedeltaIndex` from data with ``datetime64``-dtyped data is deprecated, will raise ``TypeError`` in a future version (:issue:`23539`)
- Constructing a :class:`DatetimeIndex` from data with ``timedelta64``-dtyped data is deprecated, will raise ``TypeError`` in a future version (:issue:`23675`)
From 013ae3daf2b6793478f58e9e88d6d36c308f69b7 Mon Sep 17 00:00:00 2001
From: Marc Garcia <garcia.marc@gmail.com>
Date: Fri, 25 Jan 2019 12:40:37 +0000
Subject: [PATCH 23/48] DOC: Final reorganization of documentation pages
(#24890)
* DOC: Final reorganization of documentation pages
* Move ecosystem to top level
---
doc/redirects.csv | 5 +
.../comparison}/comparison_with_r.rst | 0
.../comparison}/comparison_with_sas.rst | 0
.../comparison}/comparison_with_sql.rst | 0
.../comparison}/comparison_with_stata.rst | 0
.../getting_started/comparison/index.rst | 15 +++
doc/source/getting_started/index.rst | 1 +
doc/source/getting_started/overview.rst | 93 ++++++++++++++----
doc/source/index.rst.template | 96 ++-----------------
doc/source/r_interface.rst | 94 ------------------
doc/source/{ => user_guide}/cookbook.rst | 0
doc/source/user_guide/index.rst | 1 +
doc/source/user_guide/style.ipynb | 2 +-
.../{ => user_guide}/templates/myhtml.tpl | 0
.../templates}/template_structure.html | 0
15 files changed, 103 insertions(+), 204 deletions(-)
rename doc/source/{ => getting_started/comparison}/comparison_with_r.rst (100%)
rename doc/source/{ => getting_started/comparison}/comparison_with_sas.rst (100%)
rename doc/source/{ => getting_started/comparison}/comparison_with_sql.rst (100%)
rename doc/source/{ => getting_started/comparison}/comparison_with_stata.rst (100%)
create mode 100644 doc/source/getting_started/comparison/index.rst
delete mode 100644 doc/source/r_interface.rst
rename doc/source/{ => user_guide}/cookbook.rst (100%)
rename doc/source/{ => user_guide}/templates/myhtml.tpl (100%)
rename doc/source/{ => user_guide/templates}/template_structure.html (100%)
diff --git a/doc/redirects.csv b/doc/redirects.csv
index e0de03745aaa8..c4e14359f7f75 100644
--- a/doc/redirects.csv
+++ b/doc/redirects.csv
@@ -8,6 +8,10 @@ release,whatsnew/index
# getting started
10min,getting_started/10min
basics,getting_started/basics
+comparison_with_r,getting_started/comparison/comparison_with_r
+comparison_with_sql,getting_started/comparison/comparison_with_sql
+comparison_with_sas,getting_started/comparison/comparison_with_sas
+comparison_with_stata,getting_started/comparison/comparison_with_stata
dsintro,getting_started/dsintro
overview,getting_started/overview
tutorials,getting_started/tutorials
@@ -16,6 +20,7 @@ tutorials,getting_started/tutorials
advanced,user_guide/advanced
categorical,user_guide/categorical
computation,user_guide/computation
+cookbook,user_guide/cookbook
enhancingperf,user_guide/enhancingperf
gotchas,user_guide/gotchas
groupby,user_guide/groupby
diff --git a/doc/source/comparison_with_r.rst b/doc/source/getting_started/comparison/comparison_with_r.rst
similarity index 100%
rename from doc/source/comparison_with_r.rst
rename to doc/source/getting_started/comparison/comparison_with_r.rst
diff --git a/doc/source/comparison_with_sas.rst b/doc/source/getting_started/comparison/comparison_with_sas.rst
similarity index 100%
rename from doc/source/comparison_with_sas.rst
rename to doc/source/getting_started/comparison/comparison_with_sas.rst
diff --git a/doc/source/comparison_with_sql.rst b/doc/source/getting_started/comparison/comparison_with_sql.rst
similarity index 100%
rename from doc/source/comparison_with_sql.rst
rename to doc/source/getting_started/comparison/comparison_with_sql.rst
diff --git a/doc/source/comparison_with_stata.rst b/doc/source/getting_started/comparison/comparison_with_stata.rst
similarity index 100%
rename from doc/source/comparison_with_stata.rst
rename to doc/source/getting_started/comparison/comparison_with_stata.rst
diff --git a/doc/source/getting_started/comparison/index.rst b/doc/source/getting_started/comparison/index.rst
new file mode 100644
index 0000000000000..998706ce0c639
--- /dev/null
+++ b/doc/source/getting_started/comparison/index.rst
@@ -0,0 +1,15 @@
+{{ header }}
+
+.. _comparison:
+
+===========================
+Comparison with other tools
+===========================
+
+.. toctree::
+ :maxdepth: 2
+
+ comparison_with_r
+ comparison_with_sql
+ comparison_with_sas
+ comparison_with_stata
diff --git a/doc/source/getting_started/index.rst b/doc/source/getting_started/index.rst
index 116efe79beef1..4c5d26461a667 100644
--- a/doc/source/getting_started/index.rst
+++ b/doc/source/getting_started/index.rst
@@ -13,4 +13,5 @@ Getting started
10min
basics
dsintro
+ comparison/index
tutorials
diff --git a/doc/source/getting_started/overview.rst b/doc/source/getting_started/overview.rst
index 1e07df47aadca..b531f686951fc 100644
--- a/doc/source/getting_started/overview.rst
+++ b/doc/source/getting_started/overview.rst
@@ -6,25 +6,80 @@
Package overview
****************
-:mod:`pandas` is an open source, BSD-licensed library providing high-performance,
-easy-to-use data structures and data analysis tools for the `Python <https://www.python.org/>`__
-programming language.
-
-:mod:`pandas` consists of the following elements:
-
-* A set of labeled array data structures, the primary of which are
- Series and DataFrame.
-* Index objects enabling both simple axis indexing and multi-level /
- hierarchical axis indexing.
-* An integrated group by engine for aggregating and transforming data sets.
-* Date range generation (date_range) and custom date offsets enabling the
- implementation of customized frequencies.
-* Input/Output tools: loading tabular data from flat files (CSV, delimited,
- Excel 2003), and saving and loading pandas objects from the fast and
- efficient PyTables/HDF5 format.
-* Memory-efficient "sparse" versions of the standard data structures for storing
- data that is mostly missing or mostly constant (some fixed value).
-* Moving window statistics (rolling mean, rolling standard deviation, etc.).
+**pandas** is a `Python <https://www.python.org>`__ package providing fast,
+flexible, and expressive data structures designed to make working with
+"relational" or "labeled" data both easy and intuitive. It aims to be the
+fundamental high-level building block for doing practical, **real world** data
+analysis in Python. Additionally, it has the broader goal of becoming **the
+most powerful and flexible open source data analysis / manipulation tool
+available in any language**. It is already well on its way toward this goal.
+
+pandas is well suited for many different kinds of data:
+
+ - Tabular data with heterogeneously-typed columns, as in an SQL table or
+ Excel spreadsheet
+ - Ordered and unordered (not necessarily fixed-frequency) time series data.
+ - Arbitrary matrix data (homogeneously typed or heterogeneous) with row and
+ column labels
+ - Any other form of observational / statistical data sets. The data actually
+ need not be labeled at all to be placed into a pandas data structure
+
+The two primary data structures of pandas, :class:`Series` (1-dimensional)
+and :class:`DataFrame` (2-dimensional), handle the vast majority of typical use
+cases in finance, statistics, social science, and many areas of
+engineering. For R users, :class:`DataFrame` provides everything that R's
+``data.frame`` provides and much more. pandas is built on top of `NumPy
+<https://www.numpy.org>`__ and is intended to integrate well within a scientific
+computing environment with many other 3rd party libraries.
+
+Here are just a few of the things that pandas does well:
+
+ - Easy handling of **missing data** (represented as NaN) in floating point as
+ well as non-floating point data
+ - Size mutability: columns can be **inserted and deleted** from DataFrame and
+ higher dimensional objects
+ - Automatic and explicit **data alignment**: objects can be explicitly
+ aligned to a set of labels, or the user can simply ignore the labels and
+ let `Series`, `DataFrame`, etc. automatically align the data for you in
+ computations
+ - Powerful, flexible **group by** functionality to perform
+ split-apply-combine operations on data sets, for both aggregating and
+ transforming data
+ - Make it **easy to convert** ragged, differently-indexed data in other
+ Python and NumPy data structures into DataFrame objects
+ - Intelligent label-based **slicing**, **fancy indexing**, and **subsetting**
+ of large data sets
+ - Intuitive **merging** and **joining** data sets
+ - Flexible **reshaping** and pivoting of data sets
+ - **Hierarchical** labeling of axes (possible to have multiple labels per
+ tick)
+ - Robust IO tools for loading data from **flat files** (CSV and delimited),
+ Excel files, databases, and saving / loading data from the ultrafast **HDF5
+ format**
+ - **Time series**-specific functionality: date range generation and frequency
+ conversion, moving window statistics, moving window linear regressions,
+ date shifting and lagging, etc.
+
+Many of these principles are here to address the shortcomings frequently
+experienced using other languages / scientific research environments. For data
+scientists, working with data is typically divided into multiple stages:
+munging and cleaning data, analyzing / modeling it, then organizing the results
+of the analysis into a form suitable for plotting or tabular display. pandas
+is the ideal tool for all of these tasks.
+
+Some other notes
+
+ - pandas is **fast**. Many of the low-level algorithmic bits have been
+ extensively tweaked in `Cython <https://cython.org>`__ code. However, as with
+ anything else generalization usually sacrifices performance. So if you focus
+ on one feature for your application you may be able to create a faster
+ specialized tool.
+
+ - pandas is a dependency of `statsmodels
+ <https://www.statsmodels.org/stable/index.html>`__, making it an important part of the
+ statistical computing ecosystem in Python.
+
+ - pandas has been used extensively in production in financial applications.
Data Structures
---------------
diff --git a/doc/source/index.rst.template b/doc/source/index.rst.template
index bc420a906b59c..ab51911a610e3 100644
--- a/doc/source/index.rst.template
+++ b/doc/source/index.rst.template
@@ -22,93 +22,15 @@ pandas: powerful Python data analysis toolkit
**Developer Mailing List:** https://groups.google.com/forum/#!forum/pydata
-**pandas** is a `Python <https://www.python.org>`__ package providing fast,
-flexible, and expressive data structures designed to make working with
-"relational" or "labeled" data both easy and intuitive. It aims to be the
-fundamental high-level building block for doing practical, **real world** data
-analysis in Python. Additionally, it has the broader goal of becoming **the
-most powerful and flexible open source data analysis / manipulation tool
-available in any language**. It is already well on its way toward this goal.
-
-pandas is well suited for many different kinds of data:
-
- - Tabular data with heterogeneously-typed columns, as in an SQL table or
- Excel spreadsheet
- - Ordered and unordered (not necessarily fixed-frequency) time series data.
- - Arbitrary matrix data (homogeneously typed or heterogeneous) with row and
- column labels
- - Any other form of observational / statistical data sets. The data actually
- need not be labeled at all to be placed into a pandas data structure
-
-The two primary data structures of pandas, :class:`Series` (1-dimensional)
-and :class:`DataFrame` (2-dimensional), handle the vast majority of typical use
-cases in finance, statistics, social science, and many areas of
-engineering. For R users, :class:`DataFrame` provides everything that R's
-``data.frame`` provides and much more. pandas is built on top of `NumPy
-<https://www.numpy.org>`__ and is intended to integrate well within a scientific
-computing environment with many other 3rd party libraries.
-
-Here are just a few of the things that pandas does well:
-
- - Easy handling of **missing data** (represented as NaN) in floating point as
- well as non-floating point data
- - Size mutability: columns can be **inserted and deleted** from DataFrame and
- higher dimensional objects
- - Automatic and explicit **data alignment**: objects can be explicitly
- aligned to a set of labels, or the user can simply ignore the labels and
- let `Series`, `DataFrame`, etc. automatically align the data for you in
- computations
- - Powerful, flexible **group by** functionality to perform
- split-apply-combine operations on data sets, for both aggregating and
- transforming data
- - Make it **easy to convert** ragged, differently-indexed data in other
- Python and NumPy data structures into DataFrame objects
- - Intelligent label-based **slicing**, **fancy indexing**, and **subsetting**
- of large data sets
- - Intuitive **merging** and **joining** data sets
- - Flexible **reshaping** and pivoting of data sets
- - **Hierarchical** labeling of axes (possible to have multiple labels per
- tick)
- - Robust IO tools for loading data from **flat files** (CSV and delimited),
- Excel files, databases, and saving / loading data from the ultrafast **HDF5
- format**
- - **Time series**-specific functionality: date range generation and frequency
- conversion, moving window statistics, moving window linear regressions,
- date shifting and lagging, etc.
-
-Many of these principles are here to address the shortcomings frequently
-experienced using other languages / scientific research environments. For data
-scientists, working with data is typically divided into multiple stages:
-munging and cleaning data, analyzing / modeling it, then organizing the results
-of the analysis into a form suitable for plotting or tabular display. pandas
-is the ideal tool for all of these tasks.
-
-Some other notes
-
- - pandas is **fast**. Many of the low-level algorithmic bits have been
- extensively tweaked in `Cython <https://cython.org>`__ code. However, as with
- anything else generalization usually sacrifices performance. So if you focus
- on one feature for your application you may be able to create a faster
- specialized tool.
-
- - pandas is a dependency of `statsmodels
- <https://www.statsmodels.org/stable/index.html>`__, making it an important part of the
- statistical computing ecosystem in Python.
-
- - pandas has been used extensively in production in financial applications.
-
-.. note::
-
- This documentation assumes general familiarity with NumPy. If you haven't
- used NumPy much or at all, do invest some time in `learning about NumPy
- <https://docs.scipy.org>`__ first.
-
-See the package overview for more detail about what's in the library.
+:mod:`pandas` is an open source, BSD-licensed library providing high-performance,
+easy-to-use data structures and data analysis tools for the `Python <https://www.python.org/>`__
+programming language.
+See the :ref:`overview` for more detail about what's in the library.
{% if single_doc and single_doc.endswith('.rst') -%}
.. toctree::
- :maxdepth: 4
+ :maxdepth: 2
{{ single_doc[:-4] }}
{% elif single_doc %}
@@ -118,21 +40,15 @@ See the package overview for more detail about what's in the library.
{{ single_doc }}
{% else -%}
.. toctree::
- :maxdepth: 4
+ :maxdepth: 2
{% endif %}
{% if not single_doc -%}
What's New <whatsnew/v0.24.0>
install
getting_started/index
- cookbook
user_guide/index
- r_interface
ecosystem
- comparison_with_r
- comparison_with_sql
- comparison_with_sas
- comparison_with_stata
{% endif -%}
{% if include_api -%}
api/index
diff --git a/doc/source/r_interface.rst b/doc/source/r_interface.rst
deleted file mode 100644
index 9839bba4884d4..0000000000000
--- a/doc/source/r_interface.rst
+++ /dev/null
@@ -1,94 +0,0 @@
-.. _rpy:
-
-{{ header }}
-
-******************
-rpy2 / R interface
-******************
-
-.. warning::
-
- Up to pandas 0.19, a ``pandas.rpy`` module existed with functionality to
- convert between pandas and ``rpy2`` objects. This functionality now lives in
- the `rpy2 <https://rpy2.readthedocs.io/>`__ project itself.
- See the `updating section <http://pandas.pydata.org/pandas-docs/version/0.19.0/r_interface.html#updating-your-code-to-use-rpy2-functions>`__
- of the previous documentation for a guide to port your code from the
- removed ``pandas.rpy`` to ``rpy2`` functions.
-
-
-`rpy2 <http://rpy2.bitbucket.org/>`__ is an interface to R running embedded in a Python process, and also includes functionality to deal with pandas DataFrames.
-Converting data frames back and forth between rpy2 and pandas should be largely
-automated (no need to convert explicitly, it will be done on the fly in most
-rpy2 functions).
-To convert explicitly, the functions are ``pandas2ri.py2ri()`` and
-``pandas2ri.ri2py()``.
-
-
-See also the documentation of the `rpy2 <http://rpy2.bitbucket.org/>`__ project: https://rpy2.readthedocs.io.
-
-In the remainder of this page, a few examples of explicit conversion is given. The pandas conversion of rpy2 needs first to be activated:
-
-.. ipython::
- :verbatim:
-
- In [1]: from rpy2.robjects import pandas2ri
- ...: pandas2ri.activate()
-
-Transferring R data sets into Python
-------------------------------------
-
-Once the pandas conversion is activated (``pandas2ri.activate()``), many conversions
-of R to pandas objects will be done automatically. For example, to obtain the 'iris' dataset as a pandas DataFrame:
-
-.. ipython::
- :verbatim:
-
- In [2]: from rpy2.robjects import r
-
- In [3]: r.data('iris')
-
- In [4]: r['iris'].head()
- Out[4]:
- Sepal.Length Sepal.Width Petal.Length Petal.Width Species
- 0 5.1 3.5 1.4 0.2 setosa
- 1 4.9 3.0 1.4 0.2 setosa
- 2 4.7 3.2 1.3 0.2 setosa
- 3 4.6 3.1 1.5 0.2 setosa
- 4 5.0 3.6 1.4 0.2 setosa
-
-If the pandas conversion was not activated, the above could also be accomplished
-by explicitly converting it with the ``pandas2ri.ri2py`` function
-(``pandas2ri.ri2py(r['iris'])``).
-
-Converting DataFrames into R objects
-------------------------------------
-
-The ``pandas2ri.py2ri`` function support the reverse operation to convert
-DataFrames into the equivalent R object (that is, **data.frame**):
-
-.. ipython::
- :verbatim:
-
- In [5]: df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6], 'C': [7, 8, 9]},
- ...: index=["one", "two", "three"])
-
- In [6]: r_dataframe = pandas2ri.py2ri(df)
-
- In [7]: print(type(r_dataframe))
- Out[7]: <class 'rpy2.robjects.vectors.DataFrame'>
-
- In [8]: print(r_dataframe)
- Out[8]:
- A B C
- one 1 4 7
- two 2 5 8
- three 3 6 9
-
-
-The DataFrame's index is stored as the ``rownames`` attribute of the
-data.frame instance.
-
-
-..
- Calling R functions with pandas objects
- High-level interface to R estimators
diff --git a/doc/source/cookbook.rst b/doc/source/user_guide/cookbook.rst
similarity index 100%
rename from doc/source/cookbook.rst
rename to doc/source/user_guide/cookbook.rst
diff --git a/doc/source/user_guide/index.rst b/doc/source/user_guide/index.rst
index 60e722808d647..d39cf7103ab63 100644
--- a/doc/source/user_guide/index.rst
+++ b/doc/source/user_guide/index.rst
@@ -37,3 +37,4 @@ Further information on any specific method can be obtained in the
enhancingperf
sparse
gotchas
+ cookbook
diff --git a/doc/source/user_guide/style.ipynb b/doc/source/user_guide/style.ipynb
index a238c3b16e9ad..79a9848704eec 100644
--- a/doc/source/user_guide/style.ipynb
+++ b/doc/source/user_guide/style.ipynb
@@ -1133,7 +1133,7 @@
"metadata": {},
"outputs": [],
"source": [
- "with open(\"template_structure.html\") as f:\n",
+ "with open(\"templates/template_structure.html\") as f:\n",
" structure = f.read()\n",
" \n",
"HTML(structure)"
diff --git a/doc/source/templates/myhtml.tpl b/doc/source/user_guide/templates/myhtml.tpl
similarity index 100%
rename from doc/source/templates/myhtml.tpl
rename to doc/source/user_guide/templates/myhtml.tpl
diff --git a/doc/source/template_structure.html b/doc/source/user_guide/templates/template_structure.html
similarity index 100%
rename from doc/source/template_structure.html
rename to doc/source/user_guide/templates/template_structure.html
From 85982ed73a30a66a3138652b4454bb04d29bf7a9 Mon Sep 17 00:00:00 2001
From: Marc Garcia <garcia.marc@gmail.com>
Date: Fri, 25 Jan 2019 13:07:03 +0000
Subject: [PATCH 24/48] DOC: Adding redirects to API moved pages (#24909)
* DOC: Adding redirects to API moved pages
---
.gitignore | 2 +-
doc/make.py | 6 +-
doc/redirects.csv | 1535 +++++++++++++++++
doc/source/index.rst.template | 4 +-
doc/source/{api => reference}/arrays.rst | 48 +-
doc/source/{api => reference}/extensions.rst | 2 +-
doc/source/{api => reference}/frame.rst | 36 +-
.../{api => reference}/general_functions.rst | 16 +-
.../general_utility_functions.rst | 14 +-
doc/source/{api => reference}/groupby.rst | 14 +-
doc/source/{api => reference}/index.rst | 52 +-
doc/source/{api => reference}/indexing.rst | 68 +-
doc/source/{api => reference}/io.rst | 32 +-
.../{api => reference}/offset_frequency.rst | 272 +--
doc/source/{api => reference}/panel.rst | 28 +-
doc/source/{api => reference}/plotting.rst | 2 +-
doc/source/{api => reference}/resampling.rst | 8 +-
doc/source/{api => reference}/series.rst | 58 +-
doc/source/{api => reference}/style.rst | 10 +-
doc/source/{api => reference}/window.rst | 6 +-
doc/source/user_guide/io.rst | 2 +-
scripts/validate_docstrings.py | 3 +-
22 files changed, 1877 insertions(+), 341 deletions(-)
rename doc/source/{api => reference}/arrays.rst (93%)
rename doc/source/{api => reference}/extensions.rst (95%)
rename doc/source/{api => reference}/frame.rst (93%)
rename doc/source/{api => reference}/general_functions.rst (84%)
rename doc/source/{api => reference}/general_utility_functions.rst (93%)
rename doc/source/{api => reference}/groupby.rst (94%)
rename doc/source/{api => reference}/index.rst (56%)
rename doc/source/{api => reference}/indexing.rst (91%)
rename doc/source/{api => reference}/io.rst (78%)
rename doc/source/{api => reference}/offset_frequency.rst (84%)
rename doc/source/{api => reference}/panel.rst (90%)
rename doc/source/{api => reference}/plotting.rst (93%)
rename doc/source/{api => reference}/resampling.rst (91%)
rename doc/source/{api => reference}/series.rst (93%)
rename doc/source/{api => reference}/style.rst (88%)
rename doc/source/{api => reference}/window.rst (95%)
diff --git a/.gitignore b/.gitignore
index 4598714db6c6a..9891883879cf1 100644
--- a/.gitignore
+++ b/.gitignore
@@ -101,7 +101,7 @@ asv_bench/pandas/
# Documentation generated files #
#################################
doc/source/generated
-doc/source/api/generated
+doc/source/reference/api
doc/source/_static
doc/source/vbench
doc/source/vbench.rst
diff --git a/doc/make.py b/doc/make.py
index bc458d6b53cb0..438c4a04a3f08 100755
--- a/doc/make.py
+++ b/doc/make.py
@@ -53,7 +53,7 @@ def __init__(self, num_jobs=0, include_api=True, single_doc=None,
if single_doc and single_doc.endswith('.rst'):
self.single_doc_html = os.path.splitext(single_doc)[0] + '.html'
elif single_doc:
- self.single_doc_html = 'api/generated/pandas.{}.html'.format(
+ self.single_doc_html = 'reference/api/pandas.{}.html'.format(
single_doc)
def _process_single_doc(self, single_doc):
@@ -63,7 +63,7 @@ def _process_single_doc(self, single_doc):
For example, categorial.rst or pandas.DataFrame.head. For the latter,
return the corresponding file path
- (e.g. generated/pandas.DataFrame.head.rst).
+ (e.g. reference/api/pandas.DataFrame.head.rst).
"""
base_name, extension = os.path.splitext(single_doc)
if extension in ('.rst', '.ipynb'):
@@ -258,7 +258,7 @@ def clean():
Clean documentation generated files.
"""
shutil.rmtree(BUILD_PATH, ignore_errors=True)
- shutil.rmtree(os.path.join(SOURCE_PATH, 'api', 'generated'),
+ shutil.rmtree(os.path.join(SOURCE_PATH, 'reference', 'api'),
ignore_errors=True)
def zip_html(self):
diff --git a/doc/redirects.csv b/doc/redirects.csv
index c4e14359f7f75..a7886779c97d5 100644
--- a/doc/redirects.csv
+++ b/doc/redirects.csv
@@ -44,3 +44,1538 @@ contributing_docstring,development/contributing_docstring
developer,development/developer
extending,development/extending
internals,development/internals
+
+# api
+api,reference/index
+generated/pandas.api.extensions.ExtensionArray.argsort,../reference/api/pandas.api.extensions.ExtensionArray.argsort
+generated/pandas.api.extensions.ExtensionArray.astype,../reference/api/pandas.api.extensions.ExtensionArray.astype
+generated/pandas.api.extensions.ExtensionArray.copy,../reference/api/pandas.api.extensions.ExtensionArray.copy
+generated/pandas.api.extensions.ExtensionArray.dropna,../reference/api/pandas.api.extensions.ExtensionArray.dropna
+generated/pandas.api.extensions.ExtensionArray.dtype,../reference/api/pandas.api.extensions.ExtensionArray.dtype
+generated/pandas.api.extensions.ExtensionArray.factorize,../reference/api/pandas.api.extensions.ExtensionArray.factorize
+generated/pandas.api.extensions.ExtensionArray.fillna,../reference/api/pandas.api.extensions.ExtensionArray.fillna
+generated/pandas.api.extensions.ExtensionArray,../reference/api/pandas.api.extensions.ExtensionArray
+generated/pandas.api.extensions.ExtensionArray.isna,../reference/api/pandas.api.extensions.ExtensionArray.isna
+generated/pandas.api.extensions.ExtensionArray.nbytes,../reference/api/pandas.api.extensions.ExtensionArray.nbytes
+generated/pandas.api.extensions.ExtensionArray.ndim,../reference/api/pandas.api.extensions.ExtensionArray.ndim
+generated/pandas.api.extensions.ExtensionArray.shape,../reference/api/pandas.api.extensions.ExtensionArray.shape
+generated/pandas.api.extensions.ExtensionArray.take,../reference/api/pandas.api.extensions.ExtensionArray.take
+generated/pandas.api.extensions.ExtensionArray.unique,../reference/api/pandas.api.extensions.ExtensionArray.unique
+generated/pandas.api.extensions.ExtensionDtype.construct_array_type,../reference/api/pandas.api.extensions.ExtensionDtype.construct_array_type
+generated/pandas.api.extensions.ExtensionDtype.construct_from_string,../reference/api/pandas.api.extensions.ExtensionDtype.construct_from_string
+generated/pandas.api.extensions.ExtensionDtype,../reference/api/pandas.api.extensions.ExtensionDtype
+generated/pandas.api.extensions.ExtensionDtype.is_dtype,../reference/api/pandas.api.extensions.ExtensionDtype.is_dtype
+generated/pandas.api.extensions.ExtensionDtype.kind,../reference/api/pandas.api.extensions.ExtensionDtype.kind
+generated/pandas.api.extensions.ExtensionDtype.name,../reference/api/pandas.api.extensions.ExtensionDtype.name
+generated/pandas.api.extensions.ExtensionDtype.names,../reference/api/pandas.api.extensions.ExtensionDtype.names
+generated/pandas.api.extensions.ExtensionDtype.na_value,../reference/api/pandas.api.extensions.ExtensionDtype.na_value
+generated/pandas.api.extensions.ExtensionDtype.type,../reference/api/pandas.api.extensions.ExtensionDtype.type
+generated/pandas.api.extensions.register_dataframe_accessor,../reference/api/pandas.api.extensions.register_dataframe_accessor
+generated/pandas.api.extensions.register_extension_dtype,../reference/api/pandas.api.extensions.register_extension_dtype
+generated/pandas.api.extensions.register_index_accessor,../reference/api/pandas.api.extensions.register_index_accessor
+generated/pandas.api.extensions.register_series_accessor,../reference/api/pandas.api.extensions.register_series_accessor
+generated/pandas.api.types.infer_dtype,../reference/api/pandas.api.types.infer_dtype
+generated/pandas.api.types.is_bool_dtype,../reference/api/pandas.api.types.is_bool_dtype
+generated/pandas.api.types.is_bool,../reference/api/pandas.api.types.is_bool
+generated/pandas.api.types.is_categorical_dtype,../reference/api/pandas.api.types.is_categorical_dtype
+generated/pandas.api.types.is_categorical,../reference/api/pandas.api.types.is_categorical
+generated/pandas.api.types.is_complex_dtype,../reference/api/pandas.api.types.is_complex_dtype
+generated/pandas.api.types.is_complex,../reference/api/pandas.api.types.is_complex
+generated/pandas.api.types.is_datetime64_any_dtype,../reference/api/pandas.api.types.is_datetime64_any_dtype
+generated/pandas.api.types.is_datetime64_dtype,../reference/api/pandas.api.types.is_datetime64_dtype
+generated/pandas.api.types.is_datetime64_ns_dtype,../reference/api/pandas.api.types.is_datetime64_ns_dtype
+generated/pandas.api.types.is_datetime64tz_dtype,../reference/api/pandas.api.types.is_datetime64tz_dtype
+generated/pandas.api.types.is_datetimetz,../reference/api/pandas.api.types.is_datetimetz
+generated/pandas.api.types.is_dict_like,../reference/api/pandas.api.types.is_dict_like
+generated/pandas.api.types.is_extension_array_dtype,../reference/api/pandas.api.types.is_extension_array_dtype
+generated/pandas.api.types.is_extension_type,../reference/api/pandas.api.types.is_extension_type
+generated/pandas.api.types.is_file_like,../reference/api/pandas.api.types.is_file_like
+generated/pandas.api.types.is_float_dtype,../reference/api/pandas.api.types.is_float_dtype
+generated/pandas.api.types.is_float,../reference/api/pandas.api.types.is_float
+generated/pandas.api.types.is_hashable,../reference/api/pandas.api.types.is_hashable
+generated/pandas.api.types.is_int64_dtype,../reference/api/pandas.api.types.is_int64_dtype
+generated/pandas.api.types.is_integer_dtype,../reference/api/pandas.api.types.is_integer_dtype
+generated/pandas.api.types.is_integer,../reference/api/pandas.api.types.is_integer
+generated/pandas.api.types.is_interval_dtype,../reference/api/pandas.api.types.is_interval_dtype
+generated/pandas.api.types.is_interval,../reference/api/pandas.api.types.is_interval
+generated/pandas.api.types.is_iterator,../reference/api/pandas.api.types.is_iterator
+generated/pandas.api.types.is_list_like,../reference/api/pandas.api.types.is_list_like
+generated/pandas.api.types.is_named_tuple,../reference/api/pandas.api.types.is_named_tuple
+generated/pandas.api.types.is_number,../reference/api/pandas.api.types.is_number
+generated/pandas.api.types.is_numeric_dtype,../reference/api/pandas.api.types.is_numeric_dtype
+generated/pandas.api.types.is_object_dtype,../reference/api/pandas.api.types.is_object_dtype
+generated/pandas.api.types.is_period_dtype,../reference/api/pandas.api.types.is_period_dtype
+generated/pandas.api.types.is_period,../reference/api/pandas.api.types.is_period
+generated/pandas.api.types.is_re_compilable,../reference/api/pandas.api.types.is_re_compilable
+generated/pandas.api.types.is_re,../reference/api/pandas.api.types.is_re
+generated/pandas.api.types.is_scalar,../reference/api/pandas.api.types.is_scalar
+generated/pandas.api.types.is_signed_integer_dtype,../reference/api/pandas.api.types.is_signed_integer_dtype
+generated/pandas.api.types.is_sparse,../reference/api/pandas.api.types.is_sparse
+generated/pandas.api.types.is_string_dtype,../reference/api/pandas.api.types.is_string_dtype
+generated/pandas.api.types.is_timedelta64_dtype,../reference/api/pandas.api.types.is_timedelta64_dtype
+generated/pandas.api.types.is_timedelta64_ns_dtype,../reference/api/pandas.api.types.is_timedelta64_ns_dtype
+generated/pandas.api.types.is_unsigned_integer_dtype,../reference/api/pandas.api.types.is_unsigned_integer_dtype
+generated/pandas.api.types.pandas_dtype,../reference/api/pandas.api.types.pandas_dtype
+generated/pandas.api.types.union_categoricals,../reference/api/pandas.api.types.union_categoricals
+generated/pandas.bdate_range,../reference/api/pandas.bdate_range
+generated/pandas.Categorical.__array__,../reference/api/pandas.Categorical.__array__
+generated/pandas.Categorical.categories,../reference/api/pandas.Categorical.categories
+generated/pandas.Categorical.codes,../reference/api/pandas.Categorical.codes
+generated/pandas.CategoricalDtype.categories,../reference/api/pandas.CategoricalDtype.categories
+generated/pandas.Categorical.dtype,../reference/api/pandas.Categorical.dtype
+generated/pandas.CategoricalDtype,../reference/api/pandas.CategoricalDtype
+generated/pandas.CategoricalDtype.ordered,../reference/api/pandas.CategoricalDtype.ordered
+generated/pandas.Categorical.from_codes,../reference/api/pandas.Categorical.from_codes
+generated/pandas.Categorical,../reference/api/pandas.Categorical
+generated/pandas.CategoricalIndex.add_categories,../reference/api/pandas.CategoricalIndex.add_categories
+generated/pandas.CategoricalIndex.as_ordered,../reference/api/pandas.CategoricalIndex.as_ordered
+generated/pandas.CategoricalIndex.as_unordered,../reference/api/pandas.CategoricalIndex.as_unordered
+generated/pandas.CategoricalIndex.categories,../reference/api/pandas.CategoricalIndex.categories
+generated/pandas.CategoricalIndex.codes,../reference/api/pandas.CategoricalIndex.codes
+generated/pandas.CategoricalIndex.equals,../reference/api/pandas.CategoricalIndex.equals
+generated/pandas.CategoricalIndex,../reference/api/pandas.CategoricalIndex
+generated/pandas.CategoricalIndex.map,../reference/api/pandas.CategoricalIndex.map
+generated/pandas.CategoricalIndex.ordered,../reference/api/pandas.CategoricalIndex.ordered
+generated/pandas.CategoricalIndex.remove_categories,../reference/api/pandas.CategoricalIndex.remove_categories
+generated/pandas.CategoricalIndex.remove_unused_categories,../reference/api/pandas.CategoricalIndex.remove_unused_categories
+generated/pandas.CategoricalIndex.rename_categories,../reference/api/pandas.CategoricalIndex.rename_categories
+generated/pandas.CategoricalIndex.reorder_categories,../reference/api/pandas.CategoricalIndex.reorder_categories
+generated/pandas.CategoricalIndex.set_categories,../reference/api/pandas.CategoricalIndex.set_categories
+generated/pandas.Categorical.ordered,../reference/api/pandas.Categorical.ordered
+generated/pandas.concat,../reference/api/pandas.concat
+generated/pandas.core.groupby.DataFrameGroupBy.all,../reference/api/pandas.core.groupby.DataFrameGroupBy.all
+generated/pandas.core.groupby.DataFrameGroupBy.any,../reference/api/pandas.core.groupby.DataFrameGroupBy.any
+generated/pandas.core.groupby.DataFrameGroupBy.bfill,../reference/api/pandas.core.groupby.DataFrameGroupBy.bfill
+generated/pandas.core.groupby.DataFrameGroupBy.boxplot,../reference/api/pandas.core.groupby.DataFrameGroupBy.boxplot
+generated/pandas.core.groupby.DataFrameGroupBy.corr,../reference/api/pandas.core.groupby.DataFrameGroupBy.corr
+generated/pandas.core.groupby.DataFrameGroupBy.corrwith,../reference/api/pandas.core.groupby.DataFrameGroupBy.corrwith
+generated/pandas.core.groupby.DataFrameGroupBy.count,../reference/api/pandas.core.groupby.DataFrameGroupBy.count
+generated/pandas.core.groupby.DataFrameGroupBy.cov,../reference/api/pandas.core.groupby.DataFrameGroupBy.cov
+generated/pandas.core.groupby.DataFrameGroupBy.cummax,../reference/api/pandas.core.groupby.DataFrameGroupBy.cummax
+generated/pandas.core.groupby.DataFrameGroupBy.cummin,../reference/api/pandas.core.groupby.DataFrameGroupBy.cummin
+generated/pandas.core.groupby.DataFrameGroupBy.cumprod,../reference/api/pandas.core.groupby.DataFrameGroupBy.cumprod
+generated/pandas.core.groupby.DataFrameGroupBy.cumsum,../reference/api/pandas.core.groupby.DataFrameGroupBy.cumsum
+generated/pandas.core.groupby.DataFrameGroupBy.describe,../reference/api/pandas.core.groupby.DataFrameGroupBy.describe
+generated/pandas.core.groupby.DataFrameGroupBy.diff,../reference/api/pandas.core.groupby.DataFrameGroupBy.diff
+generated/pandas.core.groupby.DataFrameGroupBy.ffill,../reference/api/pandas.core.groupby.DataFrameGroupBy.ffill
+generated/pandas.core.groupby.DataFrameGroupBy.fillna,../reference/api/pandas.core.groupby.DataFrameGroupBy.fillna
+generated/pandas.core.groupby.DataFrameGroupBy.filter,../reference/api/pandas.core.groupby.DataFrameGroupBy.filter
+generated/pandas.core.groupby.DataFrameGroupBy.hist,../reference/api/pandas.core.groupby.DataFrameGroupBy.hist
+generated/pandas.core.groupby.DataFrameGroupBy.idxmax,../reference/api/pandas.core.groupby.DataFrameGroupBy.idxmax
+generated/pandas.core.groupby.DataFrameGroupBy.idxmin,../reference/api/pandas.core.groupby.DataFrameGroupBy.idxmin
+generated/pandas.core.groupby.DataFrameGroupBy.mad,../reference/api/pandas.core.groupby.DataFrameGroupBy.mad
+generated/pandas.core.groupby.DataFrameGroupBy.pct_change,../reference/api/pandas.core.groupby.DataFrameGroupBy.pct_change
+generated/pandas.core.groupby.DataFrameGroupBy.plot,../reference/api/pandas.core.groupby.DataFrameGroupBy.plot
+generated/pandas.core.groupby.DataFrameGroupBy.quantile,../reference/api/pandas.core.groupby.DataFrameGroupBy.quantile
+generated/pandas.core.groupby.DataFrameGroupBy.rank,../reference/api/pandas.core.groupby.DataFrameGroupBy.rank
+generated/pandas.core.groupby.DataFrameGroupBy.resample,../reference/api/pandas.core.groupby.DataFrameGroupBy.resample
+generated/pandas.core.groupby.DataFrameGroupBy.shift,../reference/api/pandas.core.groupby.DataFrameGroupBy.shift
+generated/pandas.core.groupby.DataFrameGroupBy.size,../reference/api/pandas.core.groupby.DataFrameGroupBy.size
+generated/pandas.core.groupby.DataFrameGroupBy.skew,../reference/api/pandas.core.groupby.DataFrameGroupBy.skew
+generated/pandas.core.groupby.DataFrameGroupBy.take,../reference/api/pandas.core.groupby.DataFrameGroupBy.take
+generated/pandas.core.groupby.DataFrameGroupBy.tshift,../reference/api/pandas.core.groupby.DataFrameGroupBy.tshift
+generated/pandas.core.groupby.GroupBy.agg,../reference/api/pandas.core.groupby.GroupBy.agg
+generated/pandas.core.groupby.GroupBy.aggregate,../reference/api/pandas.core.groupby.GroupBy.aggregate
+generated/pandas.core.groupby.GroupBy.all,../reference/api/pandas.core.groupby.GroupBy.all
+generated/pandas.core.groupby.GroupBy.any,../reference/api/pandas.core.groupby.GroupBy.any
+generated/pandas.core.groupby.GroupBy.apply,../reference/api/pandas.core.groupby.GroupBy.apply
+generated/pandas.core.groupby.GroupBy.bfill,../reference/api/pandas.core.groupby.GroupBy.bfill
+generated/pandas.core.groupby.GroupBy.count,../reference/api/pandas.core.groupby.GroupBy.count
+generated/pandas.core.groupby.GroupBy.cumcount,../reference/api/pandas.core.groupby.GroupBy.cumcount
+generated/pandas.core.groupby.GroupBy.ffill,../reference/api/pandas.core.groupby.GroupBy.ffill
+generated/pandas.core.groupby.GroupBy.first,../reference/api/pandas.core.groupby.GroupBy.first
+generated/pandas.core.groupby.GroupBy.get_group,../reference/api/pandas.core.groupby.GroupBy.get_group
+generated/pandas.core.groupby.GroupBy.groups,../reference/api/pandas.core.groupby.GroupBy.groups
+generated/pandas.core.groupby.GroupBy.head,../reference/api/pandas.core.groupby.GroupBy.head
+generated/pandas.core.groupby.GroupBy.indices,../reference/api/pandas.core.groupby.GroupBy.indices
+generated/pandas.core.groupby.GroupBy.__iter__,../reference/api/pandas.core.groupby.GroupBy.__iter__
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+generated/pandas.core.groupby.GroupBy.max,../reference/api/pandas.core.groupby.GroupBy.max
+generated/pandas.core.groupby.GroupBy.mean,../reference/api/pandas.core.groupby.GroupBy.mean
+generated/pandas.core.groupby.GroupBy.median,../reference/api/pandas.core.groupby.GroupBy.median
+generated/pandas.core.groupby.GroupBy.min,../reference/api/pandas.core.groupby.GroupBy.min
+generated/pandas.core.groupby.GroupBy.ngroup,../reference/api/pandas.core.groupby.GroupBy.ngroup
+generated/pandas.core.groupby.GroupBy.nth,../reference/api/pandas.core.groupby.GroupBy.nth
+generated/pandas.core.groupby.GroupBy.ohlc,../reference/api/pandas.core.groupby.GroupBy.ohlc
+generated/pandas.core.groupby.GroupBy.pct_change,../reference/api/pandas.core.groupby.GroupBy.pct_change
+generated/pandas.core.groupby.GroupBy.pipe,../reference/api/pandas.core.groupby.GroupBy.pipe
+generated/pandas.core.groupby.GroupBy.prod,../reference/api/pandas.core.groupby.GroupBy.prod
+generated/pandas.core.groupby.GroupBy.rank,../reference/api/pandas.core.groupby.GroupBy.rank
+generated/pandas.core.groupby.GroupBy.sem,../reference/api/pandas.core.groupby.GroupBy.sem
+generated/pandas.core.groupby.GroupBy.size,../reference/api/pandas.core.groupby.GroupBy.size
+generated/pandas.core.groupby.GroupBy.std,../reference/api/pandas.core.groupby.GroupBy.std
+generated/pandas.core.groupby.GroupBy.sum,../reference/api/pandas.core.groupby.GroupBy.sum
+generated/pandas.core.groupby.GroupBy.tail,../reference/api/pandas.core.groupby.GroupBy.tail
+generated/pandas.core.groupby.GroupBy.transform,../reference/api/pandas.core.groupby.GroupBy.transform
+generated/pandas.core.groupby.GroupBy.var,../reference/api/pandas.core.groupby.GroupBy.var
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+generated/pandas.core.groupby.SeriesGroupBy.nunique,../reference/api/pandas.core.groupby.SeriesGroupBy.nunique
+generated/pandas.core.groupby.SeriesGroupBy.unique,../reference/api/pandas.core.groupby.SeriesGroupBy.unique
+generated/pandas.core.groupby.SeriesGroupBy.value_counts,../reference/api/pandas.core.groupby.SeriesGroupBy.value_counts
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+generated/pandas.core.resample.Resampler.apply,../reference/api/pandas.core.resample.Resampler.apply
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+generated/pandas.core.resample.Resampler.bfill,../reference/api/pandas.core.resample.Resampler.bfill
+generated/pandas.core.resample.Resampler.count,../reference/api/pandas.core.resample.Resampler.count
+generated/pandas.core.resample.Resampler.ffill,../reference/api/pandas.core.resample.Resampler.ffill
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+generated/pandas.core.resample.Resampler.groups,../reference/api/pandas.core.resample.Resampler.groups
+generated/pandas.core.resample.Resampler.indices,../reference/api/pandas.core.resample.Resampler.indices
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+generated/pandas.core.resample.Resampler.pipe,../reference/api/pandas.core.resample.Resampler.pipe
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+generated/pandas.core.resample.Resampler.sem,../reference/api/pandas.core.resample.Resampler.sem
+generated/pandas.core.resample.Resampler.size,../reference/api/pandas.core.resample.Resampler.size
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+generated/pandas.core.window.Rolling.corr,../reference/api/pandas.core.window.Rolling.corr
+generated/pandas.core.window.Rolling.count,../reference/api/pandas.core.window.Rolling.count
+generated/pandas.core.window.Rolling.cov,../reference/api/pandas.core.window.Rolling.cov
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+generated/pandas.core.window.Rolling.quantile,../reference/api/pandas.core.window.Rolling.quantile
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+generated/pandas.core.window.Window.mean,../reference/api/pandas.core.window.Window.mean
+generated/pandas.core.window.Window.sum,../reference/api/pandas.core.window.Window.sum
+generated/pandas.crosstab,../reference/api/pandas.crosstab
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+generated/pandas.DataFrame.add,../reference/api/pandas.DataFrame.add
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+generated/pandas.DataFrame.bool,../reference/api/pandas.DataFrame.bool
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+generated/pandas.DataFrame.convert_objects,../reference/api/pandas.DataFrame.convert_objects
+generated/pandas.DataFrame.copy,../reference/api/pandas.DataFrame.copy
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+generated/pandas.DataFrame.div,../reference/api/pandas.DataFrame.div
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+generated/pandas.DataFrame.first_valid_index,../reference/api/pandas.DataFrame.first_valid_index
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+generated/pandas.DataFrame.from_csv,../reference/api/pandas.DataFrame.from_csv
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+generated/pandas.DataFrame.get_ftype_counts,../reference/api/pandas.DataFrame.get_ftype_counts
+generated/pandas.DataFrame.get,../reference/api/pandas.DataFrame.get
+generated/pandas.DataFrame.get_value,../reference/api/pandas.DataFrame.get_value
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+generated/pandas.DataFrame,../reference/api/pandas.DataFrame
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+generated/pandas.DataFrame.index,../reference/api/pandas.DataFrame.index
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+generated/pandas.DataFrame.info,../reference/api/pandas.DataFrame.info
+generated/pandas.DataFrame.insert,../reference/api/pandas.DataFrame.insert
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+generated/pandas.DataFrame.iterrows,../reference/api/pandas.DataFrame.iterrows
+generated/pandas.DataFrame.itertuples,../reference/api/pandas.DataFrame.itertuples
+generated/pandas.DataFrame.ix,../reference/api/pandas.DataFrame.ix
+generated/pandas.DataFrame.join,../reference/api/pandas.DataFrame.join
+generated/pandas.DataFrame.keys,../reference/api/pandas.DataFrame.keys
+generated/pandas.DataFrame.kurt,../reference/api/pandas.DataFrame.kurt
+generated/pandas.DataFrame.kurtosis,../reference/api/pandas.DataFrame.kurtosis
+generated/pandas.DataFrame.last,../reference/api/pandas.DataFrame.last
+generated/pandas.DataFrame.last_valid_index,../reference/api/pandas.DataFrame.last_valid_index
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+generated/pandas.DataFrame.loc,../reference/api/pandas.DataFrame.loc
+generated/pandas.DataFrame.lookup,../reference/api/pandas.DataFrame.lookup
+generated/pandas.DataFrame.lt,../reference/api/pandas.DataFrame.lt
+generated/pandas.DataFrame.mad,../reference/api/pandas.DataFrame.mad
+generated/pandas.DataFrame.mask,../reference/api/pandas.DataFrame.mask
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+generated/pandas.DataFrame.melt,../reference/api/pandas.DataFrame.melt
+generated/pandas.DataFrame.memory_usage,../reference/api/pandas.DataFrame.memory_usage
+generated/pandas.DataFrame.merge,../reference/api/pandas.DataFrame.merge
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+generated/pandas.DataFrame.mode,../reference/api/pandas.DataFrame.mode
+generated/pandas.DataFrame.mod,../reference/api/pandas.DataFrame.mod
+generated/pandas.DataFrame.mul,../reference/api/pandas.DataFrame.mul
+generated/pandas.DataFrame.multiply,../reference/api/pandas.DataFrame.multiply
+generated/pandas.DataFrame.ndim,../reference/api/pandas.DataFrame.ndim
+generated/pandas.DataFrame.ne,../reference/api/pandas.DataFrame.ne
+generated/pandas.DataFrame.nlargest,../reference/api/pandas.DataFrame.nlargest
+generated/pandas.DataFrame.notna,../reference/api/pandas.DataFrame.notna
+generated/pandas.DataFrame.notnull,../reference/api/pandas.DataFrame.notnull
+generated/pandas.DataFrame.nsmallest,../reference/api/pandas.DataFrame.nsmallest
+generated/pandas.DataFrame.nunique,../reference/api/pandas.DataFrame.nunique
+generated/pandas.DataFrame.pct_change,../reference/api/pandas.DataFrame.pct_change
+generated/pandas.DataFrame.pipe,../reference/api/pandas.DataFrame.pipe
+generated/pandas.DataFrame.pivot,../reference/api/pandas.DataFrame.pivot
+generated/pandas.DataFrame.pivot_table,../reference/api/pandas.DataFrame.pivot_table
+generated/pandas.DataFrame.plot.barh,../reference/api/pandas.DataFrame.plot.barh
+generated/pandas.DataFrame.plot.bar,../reference/api/pandas.DataFrame.plot.bar
+generated/pandas.DataFrame.plot.box,../reference/api/pandas.DataFrame.plot.box
+generated/pandas.DataFrame.plot.density,../reference/api/pandas.DataFrame.plot.density
+generated/pandas.DataFrame.plot.hexbin,../reference/api/pandas.DataFrame.plot.hexbin
+generated/pandas.DataFrame.plot.hist,../reference/api/pandas.DataFrame.plot.hist
+generated/pandas.DataFrame.plot,../reference/api/pandas.DataFrame.plot
+generated/pandas.DataFrame.plot.kde,../reference/api/pandas.DataFrame.plot.kde
+generated/pandas.DataFrame.plot.line,../reference/api/pandas.DataFrame.plot.line
+generated/pandas.DataFrame.plot.pie,../reference/api/pandas.DataFrame.plot.pie
+generated/pandas.DataFrame.plot.scatter,../reference/api/pandas.DataFrame.plot.scatter
+generated/pandas.DataFrame.pop,../reference/api/pandas.DataFrame.pop
+generated/pandas.DataFrame.pow,../reference/api/pandas.DataFrame.pow
+generated/pandas.DataFrame.prod,../reference/api/pandas.DataFrame.prod
+generated/pandas.DataFrame.product,../reference/api/pandas.DataFrame.product
+generated/pandas.DataFrame.quantile,../reference/api/pandas.DataFrame.quantile
+generated/pandas.DataFrame.query,../reference/api/pandas.DataFrame.query
+generated/pandas.DataFrame.radd,../reference/api/pandas.DataFrame.radd
+generated/pandas.DataFrame.rank,../reference/api/pandas.DataFrame.rank
+generated/pandas.DataFrame.rdiv,../reference/api/pandas.DataFrame.rdiv
+generated/pandas.DataFrame.reindex_axis,../reference/api/pandas.DataFrame.reindex_axis
+generated/pandas.DataFrame.reindex,../reference/api/pandas.DataFrame.reindex
+generated/pandas.DataFrame.reindex_like,../reference/api/pandas.DataFrame.reindex_like
+generated/pandas.DataFrame.rename_axis,../reference/api/pandas.DataFrame.rename_axis
+generated/pandas.DataFrame.rename,../reference/api/pandas.DataFrame.rename
+generated/pandas.DataFrame.reorder_levels,../reference/api/pandas.DataFrame.reorder_levels
+generated/pandas.DataFrame.replace,../reference/api/pandas.DataFrame.replace
+generated/pandas.DataFrame.resample,../reference/api/pandas.DataFrame.resample
+generated/pandas.DataFrame.reset_index,../reference/api/pandas.DataFrame.reset_index
+generated/pandas.DataFrame.rfloordiv,../reference/api/pandas.DataFrame.rfloordiv
+generated/pandas.DataFrame.rmod,../reference/api/pandas.DataFrame.rmod
+generated/pandas.DataFrame.rmul,../reference/api/pandas.DataFrame.rmul
+generated/pandas.DataFrame.rolling,../reference/api/pandas.DataFrame.rolling
+generated/pandas.DataFrame.round,../reference/api/pandas.DataFrame.round
+generated/pandas.DataFrame.rpow,../reference/api/pandas.DataFrame.rpow
+generated/pandas.DataFrame.rsub,../reference/api/pandas.DataFrame.rsub
+generated/pandas.DataFrame.rtruediv,../reference/api/pandas.DataFrame.rtruediv
+generated/pandas.DataFrame.sample,../reference/api/pandas.DataFrame.sample
+generated/pandas.DataFrame.select_dtypes,../reference/api/pandas.DataFrame.select_dtypes
+generated/pandas.DataFrame.select,../reference/api/pandas.DataFrame.select
+generated/pandas.DataFrame.sem,../reference/api/pandas.DataFrame.sem
+generated/pandas.DataFrame.set_axis,../reference/api/pandas.DataFrame.set_axis
+generated/pandas.DataFrame.set_index,../reference/api/pandas.DataFrame.set_index
+generated/pandas.DataFrame.set_value,../reference/api/pandas.DataFrame.set_value
+generated/pandas.DataFrame.shape,../reference/api/pandas.DataFrame.shape
+generated/pandas.DataFrame.shift,../reference/api/pandas.DataFrame.shift
+generated/pandas.DataFrame.size,../reference/api/pandas.DataFrame.size
+generated/pandas.DataFrame.skew,../reference/api/pandas.DataFrame.skew
+generated/pandas.DataFrame.slice_shift,../reference/api/pandas.DataFrame.slice_shift
+generated/pandas.DataFrame.sort_index,../reference/api/pandas.DataFrame.sort_index
+generated/pandas.DataFrame.sort_values,../reference/api/pandas.DataFrame.sort_values
+generated/pandas.DataFrame.squeeze,../reference/api/pandas.DataFrame.squeeze
+generated/pandas.DataFrame.stack,../reference/api/pandas.DataFrame.stack
+generated/pandas.DataFrame.std,../reference/api/pandas.DataFrame.std
+generated/pandas.DataFrame.style,../reference/api/pandas.DataFrame.style
+generated/pandas.DataFrame.sub,../reference/api/pandas.DataFrame.sub
+generated/pandas.DataFrame.subtract,../reference/api/pandas.DataFrame.subtract
+generated/pandas.DataFrame.sum,../reference/api/pandas.DataFrame.sum
+generated/pandas.DataFrame.swapaxes,../reference/api/pandas.DataFrame.swapaxes
+generated/pandas.DataFrame.swaplevel,../reference/api/pandas.DataFrame.swaplevel
+generated/pandas.DataFrame.tail,../reference/api/pandas.DataFrame.tail
+generated/pandas.DataFrame.take,../reference/api/pandas.DataFrame.take
+generated/pandas.DataFrame.T,../reference/api/pandas.DataFrame.T
+generated/pandas.DataFrame.timetuple,../reference/api/pandas.DataFrame.timetuple
+generated/pandas.DataFrame.to_clipboard,../reference/api/pandas.DataFrame.to_clipboard
+generated/pandas.DataFrame.to_csv,../reference/api/pandas.DataFrame.to_csv
+generated/pandas.DataFrame.to_dense,../reference/api/pandas.DataFrame.to_dense
+generated/pandas.DataFrame.to_dict,../reference/api/pandas.DataFrame.to_dict
+generated/pandas.DataFrame.to_excel,../reference/api/pandas.DataFrame.to_excel
+generated/pandas.DataFrame.to_feather,../reference/api/pandas.DataFrame.to_feather
+generated/pandas.DataFrame.to_gbq,../reference/api/pandas.DataFrame.to_gbq
+generated/pandas.DataFrame.to_hdf,../reference/api/pandas.DataFrame.to_hdf
+generated/pandas.DataFrame.to,../reference/api/pandas.DataFrame.to
+generated/pandas.DataFrame.to_json,../reference/api/pandas.DataFrame.to_json
+generated/pandas.DataFrame.to_latex,../reference/api/pandas.DataFrame.to_latex
+generated/pandas.DataFrame.to_msgpack,../reference/api/pandas.DataFrame.to_msgpack
+generated/pandas.DataFrame.to_numpy,../reference/api/pandas.DataFrame.to_numpy
+generated/pandas.DataFrame.to_panel,../reference/api/pandas.DataFrame.to_panel
+generated/pandas.DataFrame.to_parquet,../reference/api/pandas.DataFrame.to_parquet
+generated/pandas.DataFrame.to_period,../reference/api/pandas.DataFrame.to_period
+generated/pandas.DataFrame.to_pickle,../reference/api/pandas.DataFrame.to_pickle
+generated/pandas.DataFrame.to_records,../reference/api/pandas.DataFrame.to_records
+generated/pandas.DataFrame.to_sparse,../reference/api/pandas.DataFrame.to_sparse
+generated/pandas.DataFrame.to_sql,../reference/api/pandas.DataFrame.to_sql
+generated/pandas.DataFrame.to_stata,../reference/api/pandas.DataFrame.to_stata
+generated/pandas.DataFrame.to_string,../reference/api/pandas.DataFrame.to_string
+generated/pandas.DataFrame.to_timestamp,../reference/api/pandas.DataFrame.to_timestamp
+generated/pandas.DataFrame.to_xarray,../reference/api/pandas.DataFrame.to_xarray
+generated/pandas.DataFrame.transform,../reference/api/pandas.DataFrame.transform
+generated/pandas.DataFrame.transpose,../reference/api/pandas.DataFrame.transpose
+generated/pandas.DataFrame.truediv,../reference/api/pandas.DataFrame.truediv
+generated/pandas.DataFrame.truncate,../reference/api/pandas.DataFrame.truncate
+generated/pandas.DataFrame.tshift,../reference/api/pandas.DataFrame.tshift
+generated/pandas.DataFrame.tz_convert,../reference/api/pandas.DataFrame.tz_convert
+generated/pandas.DataFrame.tz_localize,../reference/api/pandas.DataFrame.tz_localize
+generated/pandas.DataFrame.unstack,../reference/api/pandas.DataFrame.unstack
+generated/pandas.DataFrame.update,../reference/api/pandas.DataFrame.update
+generated/pandas.DataFrame.values,../reference/api/pandas.DataFrame.values
+generated/pandas.DataFrame.var,../reference/api/pandas.DataFrame.var
+generated/pandas.DataFrame.where,../reference/api/pandas.DataFrame.where
+generated/pandas.DataFrame.xs,../reference/api/pandas.DataFrame.xs
+generated/pandas.date_range,../reference/api/pandas.date_range
+generated/pandas.DatetimeIndex.ceil,../reference/api/pandas.DatetimeIndex.ceil
+generated/pandas.DatetimeIndex.date,../reference/api/pandas.DatetimeIndex.date
+generated/pandas.DatetimeIndex.day,../reference/api/pandas.DatetimeIndex.day
+generated/pandas.DatetimeIndex.day_name,../reference/api/pandas.DatetimeIndex.day_name
+generated/pandas.DatetimeIndex.dayofweek,../reference/api/pandas.DatetimeIndex.dayofweek
+generated/pandas.DatetimeIndex.dayofyear,../reference/api/pandas.DatetimeIndex.dayofyear
+generated/pandas.DatetimeIndex.floor,../reference/api/pandas.DatetimeIndex.floor
+generated/pandas.DatetimeIndex.freq,../reference/api/pandas.DatetimeIndex.freq
+generated/pandas.DatetimeIndex.freqstr,../reference/api/pandas.DatetimeIndex.freqstr
+generated/pandas.DatetimeIndex.hour,../reference/api/pandas.DatetimeIndex.hour
+generated/pandas.DatetimeIndex,../reference/api/pandas.DatetimeIndex
+generated/pandas.DatetimeIndex.indexer_at_time,../reference/api/pandas.DatetimeIndex.indexer_at_time
+generated/pandas.DatetimeIndex.indexer_between_time,../reference/api/pandas.DatetimeIndex.indexer_between_time
+generated/pandas.DatetimeIndex.inferred_freq,../reference/api/pandas.DatetimeIndex.inferred_freq
+generated/pandas.DatetimeIndex.is_leap_year,../reference/api/pandas.DatetimeIndex.is_leap_year
+generated/pandas.DatetimeIndex.is_month_end,../reference/api/pandas.DatetimeIndex.is_month_end
+generated/pandas.DatetimeIndex.is_month_start,../reference/api/pandas.DatetimeIndex.is_month_start
+generated/pandas.DatetimeIndex.is_quarter_end,../reference/api/pandas.DatetimeIndex.is_quarter_end
+generated/pandas.DatetimeIndex.is_quarter_start,../reference/api/pandas.DatetimeIndex.is_quarter_start
+generated/pandas.DatetimeIndex.is_year_end,../reference/api/pandas.DatetimeIndex.is_year_end
+generated/pandas.DatetimeIndex.is_year_start,../reference/api/pandas.DatetimeIndex.is_year_start
+generated/pandas.DatetimeIndex.microsecond,../reference/api/pandas.DatetimeIndex.microsecond
+generated/pandas.DatetimeIndex.minute,../reference/api/pandas.DatetimeIndex.minute
+generated/pandas.DatetimeIndex.month,../reference/api/pandas.DatetimeIndex.month
+generated/pandas.DatetimeIndex.month_name,../reference/api/pandas.DatetimeIndex.month_name
+generated/pandas.DatetimeIndex.nanosecond,../reference/api/pandas.DatetimeIndex.nanosecond
+generated/pandas.DatetimeIndex.normalize,../reference/api/pandas.DatetimeIndex.normalize
+generated/pandas.DatetimeIndex.quarter,../reference/api/pandas.DatetimeIndex.quarter
+generated/pandas.DatetimeIndex.round,../reference/api/pandas.DatetimeIndex.round
+generated/pandas.DatetimeIndex.second,../reference/api/pandas.DatetimeIndex.second
+generated/pandas.DatetimeIndex.snap,../reference/api/pandas.DatetimeIndex.snap
+generated/pandas.DatetimeIndex.strftime,../reference/api/pandas.DatetimeIndex.strftime
+generated/pandas.DatetimeIndex.time,../reference/api/pandas.DatetimeIndex.time
+generated/pandas.DatetimeIndex.timetz,../reference/api/pandas.DatetimeIndex.timetz
+generated/pandas.DatetimeIndex.to_frame,../reference/api/pandas.DatetimeIndex.to_frame
+generated/pandas.DatetimeIndex.to_perioddelta,../reference/api/pandas.DatetimeIndex.to_perioddelta
+generated/pandas.DatetimeIndex.to_period,../reference/api/pandas.DatetimeIndex.to_period
+generated/pandas.DatetimeIndex.to_pydatetime,../reference/api/pandas.DatetimeIndex.to_pydatetime
+generated/pandas.DatetimeIndex.to_series,../reference/api/pandas.DatetimeIndex.to_series
+generated/pandas.DatetimeIndex.tz_convert,../reference/api/pandas.DatetimeIndex.tz_convert
+generated/pandas.DatetimeIndex.tz,../reference/api/pandas.DatetimeIndex.tz
+generated/pandas.DatetimeIndex.tz_localize,../reference/api/pandas.DatetimeIndex.tz_localize
+generated/pandas.DatetimeIndex.weekday,../reference/api/pandas.DatetimeIndex.weekday
+generated/pandas.DatetimeIndex.week,../reference/api/pandas.DatetimeIndex.week
+generated/pandas.DatetimeIndex.weekofyear,../reference/api/pandas.DatetimeIndex.weekofyear
+generated/pandas.DatetimeIndex.year,../reference/api/pandas.DatetimeIndex.year
+generated/pandas.DatetimeTZDtype.base,../reference/api/pandas.DatetimeTZDtype.base
+generated/pandas.DatetimeTZDtype.construct_array_type,../reference/api/pandas.DatetimeTZDtype.construct_array_type
+generated/pandas.DatetimeTZDtype.construct_from_string,../reference/api/pandas.DatetimeTZDtype.construct_from_string
+generated/pandas.DatetimeTZDtype,../reference/api/pandas.DatetimeTZDtype
+generated/pandas.DatetimeTZDtype.isbuiltin,../reference/api/pandas.DatetimeTZDtype.isbuiltin
+generated/pandas.DatetimeTZDtype.is_dtype,../reference/api/pandas.DatetimeTZDtype.is_dtype
+generated/pandas.DatetimeTZDtype.isnative,../reference/api/pandas.DatetimeTZDtype.isnative
+generated/pandas.DatetimeTZDtype.itemsize,../reference/api/pandas.DatetimeTZDtype.itemsize
+generated/pandas.DatetimeTZDtype.kind,../reference/api/pandas.DatetimeTZDtype.kind
+generated/pandas.DatetimeTZDtype.name,../reference/api/pandas.DatetimeTZDtype.name
+generated/pandas.DatetimeTZDtype.names,../reference/api/pandas.DatetimeTZDtype.names
+generated/pandas.DatetimeTZDtype.na_value,../reference/api/pandas.DatetimeTZDtype.na_value
+generated/pandas.DatetimeTZDtype.num,../reference/api/pandas.DatetimeTZDtype.num
+generated/pandas.DatetimeTZDtype.reset_cache,../reference/api/pandas.DatetimeTZDtype.reset_cache
+generated/pandas.DatetimeTZDtype.shape,../reference/api/pandas.DatetimeTZDtype.shape
+generated/pandas.DatetimeTZDtype.str,../reference/api/pandas.DatetimeTZDtype.str
+generated/pandas.DatetimeTZDtype.subdtype,../reference/api/pandas.DatetimeTZDtype.subdtype
+generated/pandas.DatetimeTZDtype.tz,../reference/api/pandas.DatetimeTZDtype.tz
+generated/pandas.DatetimeTZDtype.unit,../reference/api/pandas.DatetimeTZDtype.unit
+generated/pandas.describe_option,../reference/api/pandas.describe_option
+generated/pandas.errors.DtypeWarning,../reference/api/pandas.errors.DtypeWarning
+generated/pandas.errors.EmptyDataError,../reference/api/pandas.errors.EmptyDataError
+generated/pandas.errors.OutOfBoundsDatetime,../reference/api/pandas.errors.OutOfBoundsDatetime
+generated/pandas.errors.ParserError,../reference/api/pandas.errors.ParserError
+generated/pandas.errors.ParserWarning,../reference/api/pandas.errors.ParserWarning
+generated/pandas.errors.PerformanceWarning,../reference/api/pandas.errors.PerformanceWarning
+generated/pandas.errors.UnsortedIndexError,../reference/api/pandas.errors.UnsortedIndexError
+generated/pandas.errors.UnsupportedFunctionCall,../reference/api/pandas.errors.UnsupportedFunctionCall
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+generated/pandas.ExcelWriter,../reference/api/pandas.ExcelWriter
+generated/pandas.factorize,../reference/api/pandas.factorize
+generated/pandas.Float64Index,../reference/api/pandas.Float64Index
+generated/pandas.get_dummies,../reference/api/pandas.get_dummies
+generated/pandas.get_option,../reference/api/pandas.get_option
+generated/pandas.Grouper,../reference/api/pandas.Grouper
+generated/pandas.HDFStore.append,../reference/api/pandas.HDFStore.append
+generated/pandas.HDFStore.get,../reference/api/pandas.HDFStore.get
+generated/pandas.HDFStore.groups,../reference/api/pandas.HDFStore.groups
+generated/pandas.HDFStore.info,../reference/api/pandas.HDFStore.info
+generated/pandas.HDFStore.keys,../reference/api/pandas.HDFStore.keys
+generated/pandas.HDFStore.put,../reference/api/pandas.HDFStore.put
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+generated/pandas.HDFStore.walk,../reference/api/pandas.HDFStore.walk
+generated/pandas.Index.all,../reference/api/pandas.Index.all
+generated/pandas.Index.any,../reference/api/pandas.Index.any
+generated/pandas.Index.append,../reference/api/pandas.Index.append
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+generated/pandas.Index.asof,../reference/api/pandas.Index.asof
+generated/pandas.Index.asof_locs,../reference/api/pandas.Index.asof_locs
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+generated/pandas.Index.base,../reference/api/pandas.Index.base
+generated/pandas.Index.contains,../reference/api/pandas.Index.contains
+generated/pandas.Index.copy,../reference/api/pandas.Index.copy
+generated/pandas.Index.data,../reference/api/pandas.Index.data
+generated/pandas.Index.delete,../reference/api/pandas.Index.delete
+generated/pandas.Index.difference,../reference/api/pandas.Index.difference
+generated/pandas.Index.drop_duplicates,../reference/api/pandas.Index.drop_duplicates
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+generated/pandas.Index.droplevel,../reference/api/pandas.Index.droplevel
+generated/pandas.Index.dropna,../reference/api/pandas.Index.dropna
+generated/pandas.Index.dtype,../reference/api/pandas.Index.dtype
+generated/pandas.Index.dtype_str,../reference/api/pandas.Index.dtype_str
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+generated/pandas.Index.empty,../reference/api/pandas.Index.empty
+generated/pandas.Index.equals,../reference/api/pandas.Index.equals
+generated/pandas.Index.factorize,../reference/api/pandas.Index.factorize
+generated/pandas.Index.fillna,../reference/api/pandas.Index.fillna
+generated/pandas.Index.flags,../reference/api/pandas.Index.flags
+generated/pandas.Index.format,../reference/api/pandas.Index.format
+generated/pandas.Index.get_duplicates,../reference/api/pandas.Index.get_duplicates
+generated/pandas.Index.get_indexer_for,../reference/api/pandas.Index.get_indexer_for
+generated/pandas.Index.get_indexer,../reference/api/pandas.Index.get_indexer
+generated/pandas.Index.get_indexer_non_unique,../reference/api/pandas.Index.get_indexer_non_unique
+generated/pandas.Index.get_level_values,../reference/api/pandas.Index.get_level_values
+generated/pandas.Index.get_loc,../reference/api/pandas.Index.get_loc
+generated/pandas.Index.get_slice_bound,../reference/api/pandas.Index.get_slice_bound
+generated/pandas.Index.get_value,../reference/api/pandas.Index.get_value
+generated/pandas.Index.get_values,../reference/api/pandas.Index.get_values
+generated/pandas.Index.groupby,../reference/api/pandas.Index.groupby
+generated/pandas.Index.has_duplicates,../reference/api/pandas.Index.has_duplicates
+generated/pandas.Index.hasnans,../reference/api/pandas.Index.hasnans
+generated/pandas.Index.holds_integer,../reference/api/pandas.Index.holds_integer
+generated/pandas.Index,../reference/api/pandas.Index
+generated/pandas.Index.identical,../reference/api/pandas.Index.identical
+generated/pandas.Index.inferred_type,../reference/api/pandas.Index.inferred_type
+generated/pandas.Index.insert,../reference/api/pandas.Index.insert
+generated/pandas.Index.intersection,../reference/api/pandas.Index.intersection
+generated/pandas.Index.is_all_dates,../reference/api/pandas.Index.is_all_dates
+generated/pandas.Index.is_boolean,../reference/api/pandas.Index.is_boolean
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+generated/pandas.Index.is_floating,../reference/api/pandas.Index.is_floating
+generated/pandas.Index.is_,../reference/api/pandas.Index.is_
+generated/pandas.Index.isin,../reference/api/pandas.Index.isin
+generated/pandas.Index.is_integer,../reference/api/pandas.Index.is_integer
+generated/pandas.Index.is_interval,../reference/api/pandas.Index.is_interval
+generated/pandas.Index.is_lexsorted_for_tuple,../reference/api/pandas.Index.is_lexsorted_for_tuple
+generated/pandas.Index.is_mixed,../reference/api/pandas.Index.is_mixed
+generated/pandas.Index.is_monotonic_decreasing,../reference/api/pandas.Index.is_monotonic_decreasing
+generated/pandas.Index.is_monotonic,../reference/api/pandas.Index.is_monotonic
+generated/pandas.Index.is_monotonic_increasing,../reference/api/pandas.Index.is_monotonic_increasing
+generated/pandas.Index.isna,../reference/api/pandas.Index.isna
+generated/pandas.Index.isnull,../reference/api/pandas.Index.isnull
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+generated/pandas.Panel.rsub,../reference/api/pandas.Panel.rsub
+generated/pandas.Panel.rtruediv,../reference/api/pandas.Panel.rtruediv
+generated/pandas.Panel.sample,../reference/api/pandas.Panel.sample
+generated/pandas.Panel.select,../reference/api/pandas.Panel.select
+generated/pandas.Panel.sem,../reference/api/pandas.Panel.sem
+generated/pandas.Panel.set_axis,../reference/api/pandas.Panel.set_axis
+generated/pandas.Panel.set_value,../reference/api/pandas.Panel.set_value
+generated/pandas.Panel.shape,../reference/api/pandas.Panel.shape
+generated/pandas.Panel.shift,../reference/api/pandas.Panel.shift
+generated/pandas.Panel.size,../reference/api/pandas.Panel.size
+generated/pandas.Panel.skew,../reference/api/pandas.Panel.skew
+generated/pandas.Panel.slice_shift,../reference/api/pandas.Panel.slice_shift
+generated/pandas.Panel.sort_index,../reference/api/pandas.Panel.sort_index
+generated/pandas.Panel.sort_values,../reference/api/pandas.Panel.sort_values
+generated/pandas.Panel.squeeze,../reference/api/pandas.Panel.squeeze
+generated/pandas.Panel.std,../reference/api/pandas.Panel.std
+generated/pandas.Panel.sub,../reference/api/pandas.Panel.sub
+generated/pandas.Panel.subtract,../reference/api/pandas.Panel.subtract
+generated/pandas.Panel.sum,../reference/api/pandas.Panel.sum
+generated/pandas.Panel.swapaxes,../reference/api/pandas.Panel.swapaxes
+generated/pandas.Panel.swaplevel,../reference/api/pandas.Panel.swaplevel
+generated/pandas.Panel.tail,../reference/api/pandas.Panel.tail
+generated/pandas.Panel.take,../reference/api/pandas.Panel.take
+generated/pandas.Panel.timetuple,../reference/api/pandas.Panel.timetuple
+generated/pandas.Panel.to_clipboard,../reference/api/pandas.Panel.to_clipboard
+generated/pandas.Panel.to_csv,../reference/api/pandas.Panel.to_csv
+generated/pandas.Panel.to_dense,../reference/api/pandas.Panel.to_dense
+generated/pandas.Panel.to_excel,../reference/api/pandas.Panel.to_excel
+generated/pandas.Panel.to_frame,../reference/api/pandas.Panel.to_frame
+generated/pandas.Panel.to_hdf,../reference/api/pandas.Panel.to_hdf
+generated/pandas.Panel.to_json,../reference/api/pandas.Panel.to_json
+generated/pandas.Panel.to_latex,../reference/api/pandas.Panel.to_latex
+generated/pandas.Panel.to_msgpack,../reference/api/pandas.Panel.to_msgpack
+generated/pandas.Panel.to_pickle,../reference/api/pandas.Panel.to_pickle
+generated/pandas.Panel.to_sparse,../reference/api/pandas.Panel.to_sparse
+generated/pandas.Panel.to_sql,../reference/api/pandas.Panel.to_sql
+generated/pandas.Panel.to_xarray,../reference/api/pandas.Panel.to_xarray
+generated/pandas.Panel.transform,../reference/api/pandas.Panel.transform
+generated/pandas.Panel.transpose,../reference/api/pandas.Panel.transpose
+generated/pandas.Panel.truediv,../reference/api/pandas.Panel.truediv
+generated/pandas.Panel.truncate,../reference/api/pandas.Panel.truncate
+generated/pandas.Panel.tshift,../reference/api/pandas.Panel.tshift
+generated/pandas.Panel.tz_convert,../reference/api/pandas.Panel.tz_convert
+generated/pandas.Panel.tz_localize,../reference/api/pandas.Panel.tz_localize
+generated/pandas.Panel.update,../reference/api/pandas.Panel.update
+generated/pandas.Panel.values,../reference/api/pandas.Panel.values
+generated/pandas.Panel.var,../reference/api/pandas.Panel.var
+generated/pandas.Panel.where,../reference/api/pandas.Panel.where
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+generated/pandas.Period.day,../reference/api/pandas.Period.day
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+generated/pandas.Period.freqstr,../reference/api/pandas.Period.freqstr
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+generated/pandas.PeriodIndex.day,../reference/api/pandas.PeriodIndex.day
+generated/pandas.PeriodIndex.dayofweek,../reference/api/pandas.PeriodIndex.dayofweek
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+generated/pandas.PeriodIndex.end_time,../reference/api/pandas.PeriodIndex.end_time
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+generated/pandas.PeriodIndex.start_time,../reference/api/pandas.PeriodIndex.start_time
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+generated/pandas.PeriodIndex.week,../reference/api/pandas.PeriodIndex.week
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+generated/pandas.Period.now,../reference/api/pandas.Period.now
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+generated/pandas.Period.quarter,../reference/api/pandas.Period.quarter
+generated/pandas.Period.qyear,../reference/api/pandas.Period.qyear
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+generated/pandas.Period.second,../reference/api/pandas.Period.second
+generated/pandas.Period.start_time,../reference/api/pandas.Period.start_time
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+generated/pandas.Period.weekday,../reference/api/pandas.Period.weekday
+generated/pandas.Period.week,../reference/api/pandas.Period.week
+generated/pandas.Period.weekofyear,../reference/api/pandas.Period.weekofyear
+generated/pandas.Period.year,../reference/api/pandas.Period.year
+generated/pandas.pivot,../reference/api/pandas.pivot
+generated/pandas.pivot_table,../reference/api/pandas.pivot_table
+generated/pandas.plotting.andrews_curves,../reference/api/pandas.plotting.andrews_curves
+generated/pandas.plotting.bootstrap_plot,../reference/api/pandas.plotting.bootstrap_plot
+generated/pandas.plotting.deregister_matplotlib_converters,../reference/api/pandas.plotting.deregister_matplotlib_converters
+generated/pandas.plotting.lag_plot,../reference/api/pandas.plotting.lag_plot
+generated/pandas.plotting.parallel_coordinates,../reference/api/pandas.plotting.parallel_coordinates
+generated/pandas.plotting.radviz,../reference/api/pandas.plotting.radviz
+generated/pandas.plotting.register_matplotlib_converters,../reference/api/pandas.plotting.register_matplotlib_converters
+generated/pandas.plotting.scatter_matrix,../reference/api/pandas.plotting.scatter_matrix
+generated/pandas.qcut,../reference/api/pandas.qcut
+generated/pandas.RangeIndex.from_range,../reference/api/pandas.RangeIndex.from_range
+generated/pandas.RangeIndex,../reference/api/pandas.RangeIndex
+generated/pandas.read_clipboard,../reference/api/pandas.read_clipboard
+generated/pandas.read_csv,../reference/api/pandas.read_csv
+generated/pandas.read_excel,../reference/api/pandas.read_excel
+generated/pandas.read_feather,../reference/api/pandas.read_feather
+generated/pandas.read_fwf,../reference/api/pandas.read_fwf
+generated/pandas.read_gbq,../reference/api/pandas.read_gbq
+generated/pandas.read_hdf,../reference/api/pandas.read_hdf
+generated/pandas.read,../reference/api/pandas.read
+generated/pandas.read_json,../reference/api/pandas.read_json
+generated/pandas.read_msgpack,../reference/api/pandas.read_msgpack
+generated/pandas.read_parquet,../reference/api/pandas.read_parquet
+generated/pandas.read_pickle,../reference/api/pandas.read_pickle
+generated/pandas.read_sas,../reference/api/pandas.read_sas
+generated/pandas.read_sql,../reference/api/pandas.read_sql
+generated/pandas.read_sql_query,../reference/api/pandas.read_sql_query
+generated/pandas.read_sql_table,../reference/api/pandas.read_sql_table
+generated/pandas.read_stata,../reference/api/pandas.read_stata
+generated/pandas.read_table,../reference/api/pandas.read_table
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+generated/pandas.Series.abs,../reference/api/pandas.Series.abs
+generated/pandas.Series.add,../reference/api/pandas.Series.add
+generated/pandas.Series.add_prefix,../reference/api/pandas.Series.add_prefix
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+generated/pandas.Series.agg,../reference/api/pandas.Series.agg
+generated/pandas.Series.aggregate,../reference/api/pandas.Series.aggregate
+generated/pandas.Series.align,../reference/api/pandas.Series.align
+generated/pandas.Series.all,../reference/api/pandas.Series.all
+generated/pandas.Series.any,../reference/api/pandas.Series.any
+generated/pandas.Series.append,../reference/api/pandas.Series.append
+generated/pandas.Series.apply,../reference/api/pandas.Series.apply
+generated/pandas.Series.argmax,../reference/api/pandas.Series.argmax
+generated/pandas.Series.argmin,../reference/api/pandas.Series.argmin
+generated/pandas.Series.argsort,../reference/api/pandas.Series.argsort
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+generated/pandas.Series.as_blocks,../reference/api/pandas.Series.as_blocks
+generated/pandas.Series.asfreq,../reference/api/pandas.Series.asfreq
+generated/pandas.Series.as_matrix,../reference/api/pandas.Series.as_matrix
+generated/pandas.Series.asobject,../reference/api/pandas.Series.asobject
+generated/pandas.Series.asof,../reference/api/pandas.Series.asof
+generated/pandas.Series.astype,../reference/api/pandas.Series.astype
+generated/pandas.Series.at,../reference/api/pandas.Series.at
+generated/pandas.Series.at_time,../reference/api/pandas.Series.at_time
+generated/pandas.Series.autocorr,../reference/api/pandas.Series.autocorr
+generated/pandas.Series.axes,../reference/api/pandas.Series.axes
+generated/pandas.Series.base,../reference/api/pandas.Series.base
+generated/pandas.Series.between,../reference/api/pandas.Series.between
+generated/pandas.Series.between_time,../reference/api/pandas.Series.between_time
+generated/pandas.Series.bfill,../reference/api/pandas.Series.bfill
+generated/pandas.Series.blocks,../reference/api/pandas.Series.blocks
+generated/pandas.Series.bool,../reference/api/pandas.Series.bool
+generated/pandas.Series.cat.add_categories,../reference/api/pandas.Series.cat.add_categories
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+generated/pandas.Series.cat.categories,../reference/api/pandas.Series.cat.categories
+generated/pandas.Series.cat.codes,../reference/api/pandas.Series.cat.codes
+generated/pandas.Series.cat,../reference/api/pandas.Series.cat
+generated/pandas.Series.cat.ordered,../reference/api/pandas.Series.cat.ordered
+generated/pandas.Series.cat.remove_categories,../reference/api/pandas.Series.cat.remove_categories
+generated/pandas.Series.cat.remove_unused_categories,../reference/api/pandas.Series.cat.remove_unused_categories
+generated/pandas.Series.cat.rename_categories,../reference/api/pandas.Series.cat.rename_categories
+generated/pandas.Series.cat.reorder_categories,../reference/api/pandas.Series.cat.reorder_categories
+generated/pandas.Series.cat.set_categories,../reference/api/pandas.Series.cat.set_categories
+generated/pandas.Series.clip,../reference/api/pandas.Series.clip
+generated/pandas.Series.clip_lower,../reference/api/pandas.Series.clip_lower
+generated/pandas.Series.clip_upper,../reference/api/pandas.Series.clip_upper
+generated/pandas.Series.combine_first,../reference/api/pandas.Series.combine_first
+generated/pandas.Series.combine,../reference/api/pandas.Series.combine
+generated/pandas.Series.compound,../reference/api/pandas.Series.compound
+generated/pandas.Series.compress,../reference/api/pandas.Series.compress
+generated/pandas.Series.convert_objects,../reference/api/pandas.Series.convert_objects
+generated/pandas.Series.copy,../reference/api/pandas.Series.copy
+generated/pandas.Series.corr,../reference/api/pandas.Series.corr
+generated/pandas.Series.count,../reference/api/pandas.Series.count
+generated/pandas.Series.cov,../reference/api/pandas.Series.cov
+generated/pandas.Series.cummax,../reference/api/pandas.Series.cummax
+generated/pandas.Series.cummin,../reference/api/pandas.Series.cummin
+generated/pandas.Series.cumprod,../reference/api/pandas.Series.cumprod
+generated/pandas.Series.cumsum,../reference/api/pandas.Series.cumsum
+generated/pandas.Series.data,../reference/api/pandas.Series.data
+generated/pandas.Series.describe,../reference/api/pandas.Series.describe
+generated/pandas.Series.diff,../reference/api/pandas.Series.diff
+generated/pandas.Series.div,../reference/api/pandas.Series.div
+generated/pandas.Series.divide,../reference/api/pandas.Series.divide
+generated/pandas.Series.divmod,../reference/api/pandas.Series.divmod
+generated/pandas.Series.dot,../reference/api/pandas.Series.dot
+generated/pandas.Series.drop_duplicates,../reference/api/pandas.Series.drop_duplicates
+generated/pandas.Series.drop,../reference/api/pandas.Series.drop
+generated/pandas.Series.droplevel,../reference/api/pandas.Series.droplevel
+generated/pandas.Series.dropna,../reference/api/pandas.Series.dropna
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+generated/pandas.Series.dt.date,../reference/api/pandas.Series.dt.date
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+generated/pandas.Series.dt.day_name,../reference/api/pandas.Series.dt.day_name
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+generated/pandas.Series.dt.is_month_start,../reference/api/pandas.Series.dt.is_month_start
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+generated/pandas.Series.dt.to_period,../reference/api/pandas.Series.dt.to_period
+generated/pandas.Series.dt.to_pydatetime,../reference/api/pandas.Series.dt.to_pydatetime
+generated/pandas.Series.dt.to_pytimedelta,../reference/api/pandas.Series.dt.to_pytimedelta
+generated/pandas.Series.dt.total_seconds,../reference/api/pandas.Series.dt.total_seconds
+generated/pandas.Series.dt.tz_convert,../reference/api/pandas.Series.dt.tz_convert
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+generated/pandas.Series.dt.week,../reference/api/pandas.Series.dt.week
+generated/pandas.Series.dt.weekofyear,../reference/api/pandas.Series.dt.weekofyear
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+generated/pandas.Series.dtype,../reference/api/pandas.Series.dtype
+generated/pandas.Series.dtypes,../reference/api/pandas.Series.dtypes
+generated/pandas.Series.duplicated,../reference/api/pandas.Series.duplicated
+generated/pandas.Series.empty,../reference/api/pandas.Series.empty
+generated/pandas.Series.eq,../reference/api/pandas.Series.eq
+generated/pandas.Series.equals,../reference/api/pandas.Series.equals
+generated/pandas.Series.ewm,../reference/api/pandas.Series.ewm
+generated/pandas.Series.expanding,../reference/api/pandas.Series.expanding
+generated/pandas.Series.factorize,../reference/api/pandas.Series.factorize
+generated/pandas.Series.ffill,../reference/api/pandas.Series.ffill
+generated/pandas.Series.fillna,../reference/api/pandas.Series.fillna
+generated/pandas.Series.filter,../reference/api/pandas.Series.filter
+generated/pandas.Series.first,../reference/api/pandas.Series.first
+generated/pandas.Series.first_valid_index,../reference/api/pandas.Series.first_valid_index
+generated/pandas.Series.flags,../reference/api/pandas.Series.flags
+generated/pandas.Series.floordiv,../reference/api/pandas.Series.floordiv
+generated/pandas.Series.from_array,../reference/api/pandas.Series.from_array
+generated/pandas.Series.from_csv,../reference/api/pandas.Series.from_csv
+generated/pandas.Series.ftype,../reference/api/pandas.Series.ftype
+generated/pandas.Series.ftypes,../reference/api/pandas.Series.ftypes
+generated/pandas.Series.ge,../reference/api/pandas.Series.ge
+generated/pandas.Series.get_dtype_counts,../reference/api/pandas.Series.get_dtype_counts
+generated/pandas.Series.get_ftype_counts,../reference/api/pandas.Series.get_ftype_counts
+generated/pandas.Series.get,../reference/api/pandas.Series.get
+generated/pandas.Series.get_value,../reference/api/pandas.Series.get_value
+generated/pandas.Series.get_values,../reference/api/pandas.Series.get_values
+generated/pandas.Series.groupby,../reference/api/pandas.Series.groupby
+generated/pandas.Series.gt,../reference/api/pandas.Series.gt
+generated/pandas.Series.hasnans,../reference/api/pandas.Series.hasnans
+generated/pandas.Series.head,../reference/api/pandas.Series.head
+generated/pandas.Series.hist,../reference/api/pandas.Series.hist
+generated/pandas.Series,../reference/api/pandas.Series
+generated/pandas.Series.iat,../reference/api/pandas.Series.iat
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+generated/pandas.Timestamp,../reference/api/pandas.Timestamp
+generated/pandas.Timestamp.is_leap_year,../reference/api/pandas.Timestamp.is_leap_year
+generated/pandas.Timestamp.is_month_end,../reference/api/pandas.Timestamp.is_month_end
+generated/pandas.Timestamp.is_month_start,../reference/api/pandas.Timestamp.is_month_start
+generated/pandas.Timestamp.isocalendar,../reference/api/pandas.Timestamp.isocalendar
+generated/pandas.Timestamp.isoformat,../reference/api/pandas.Timestamp.isoformat
+generated/pandas.Timestamp.isoweekday,../reference/api/pandas.Timestamp.isoweekday
+generated/pandas.Timestamp.is_quarter_end,../reference/api/pandas.Timestamp.is_quarter_end
+generated/pandas.Timestamp.is_quarter_start,../reference/api/pandas.Timestamp.is_quarter_start
+generated/pandas.Timestamp.is_year_end,../reference/api/pandas.Timestamp.is_year_end
+generated/pandas.Timestamp.is_year_start,../reference/api/pandas.Timestamp.is_year_start
+generated/pandas.Timestamp.max,../reference/api/pandas.Timestamp.max
+generated/pandas.Timestamp.microsecond,../reference/api/pandas.Timestamp.microsecond
+generated/pandas.Timestamp.min,../reference/api/pandas.Timestamp.min
+generated/pandas.Timestamp.minute,../reference/api/pandas.Timestamp.minute
+generated/pandas.Timestamp.month,../reference/api/pandas.Timestamp.month
+generated/pandas.Timestamp.month_name,../reference/api/pandas.Timestamp.month_name
+generated/pandas.Timestamp.nanosecond,../reference/api/pandas.Timestamp.nanosecond
+generated/pandas.Timestamp.normalize,../reference/api/pandas.Timestamp.normalize
+generated/pandas.Timestamp.now,../reference/api/pandas.Timestamp.now
+generated/pandas.Timestamp.quarter,../reference/api/pandas.Timestamp.quarter
+generated/pandas.Timestamp.replace,../reference/api/pandas.Timestamp.replace
+generated/pandas.Timestamp.resolution,../reference/api/pandas.Timestamp.resolution
+generated/pandas.Timestamp.round,../reference/api/pandas.Timestamp.round
+generated/pandas.Timestamp.second,../reference/api/pandas.Timestamp.second
+generated/pandas.Timestamp.strftime,../reference/api/pandas.Timestamp.strftime
+generated/pandas.Timestamp.strptime,../reference/api/pandas.Timestamp.strptime
+generated/pandas.Timestamp.time,../reference/api/pandas.Timestamp.time
+generated/pandas.Timestamp.timestamp,../reference/api/pandas.Timestamp.timestamp
+generated/pandas.Timestamp.timetuple,../reference/api/pandas.Timestamp.timetuple
+generated/pandas.Timestamp.timetz,../reference/api/pandas.Timestamp.timetz
+generated/pandas.Timestamp.to_datetime64,../reference/api/pandas.Timestamp.to_datetime64
+generated/pandas.Timestamp.today,../reference/api/pandas.Timestamp.today
+generated/pandas.Timestamp.to_julian_date,../reference/api/pandas.Timestamp.to_julian_date
+generated/pandas.Timestamp.toordinal,../reference/api/pandas.Timestamp.toordinal
+generated/pandas.Timestamp.to_period,../reference/api/pandas.Timestamp.to_period
+generated/pandas.Timestamp.to_pydatetime,../reference/api/pandas.Timestamp.to_pydatetime
+generated/pandas.Timestamp.tz_convert,../reference/api/pandas.Timestamp.tz_convert
+generated/pandas.Timestamp.tz,../reference/api/pandas.Timestamp.tz
+generated/pandas.Timestamp.tzinfo,../reference/api/pandas.Timestamp.tzinfo
+generated/pandas.Timestamp.tz_localize,../reference/api/pandas.Timestamp.tz_localize
+generated/pandas.Timestamp.tzname,../reference/api/pandas.Timestamp.tzname
+generated/pandas.Timestamp.utcfromtimestamp,../reference/api/pandas.Timestamp.utcfromtimestamp
+generated/pandas.Timestamp.utcnow,../reference/api/pandas.Timestamp.utcnow
+generated/pandas.Timestamp.utcoffset,../reference/api/pandas.Timestamp.utcoffset
+generated/pandas.Timestamp.utctimetuple,../reference/api/pandas.Timestamp.utctimetuple
+generated/pandas.Timestamp.value,../reference/api/pandas.Timestamp.value
+generated/pandas.Timestamp.weekday,../reference/api/pandas.Timestamp.weekday
+generated/pandas.Timestamp.weekday_name,../reference/api/pandas.Timestamp.weekday_name
+generated/pandas.Timestamp.week,../reference/api/pandas.Timestamp.week
+generated/pandas.Timestamp.weekofyear,../reference/api/pandas.Timestamp.weekofyear
+generated/pandas.Timestamp.year,../reference/api/pandas.Timestamp.year
+generated/pandas.to_datetime,../reference/api/pandas.to_datetime
+generated/pandas.to_numeric,../reference/api/pandas.to_numeric
+generated/pandas.to_timedelta,../reference/api/pandas.to_timedelta
+generated/pandas.tseries.frequencies.to_offset,../reference/api/pandas.tseries.frequencies.to_offset
+generated/pandas.unique,../reference/api/pandas.unique
+generated/pandas.util.hash_array,../reference/api/pandas.util.hash_array
+generated/pandas.util.hash_pandas_object,../reference/api/pandas.util.hash_pandas_object
+generated/pandas.wide_to_long,../reference/api/pandas.wide_to_long
diff --git a/doc/source/index.rst.template b/doc/source/index.rst.template
index ab51911a610e3..45ebbbc870ca3 100644
--- a/doc/source/index.rst.template
+++ b/doc/source/index.rst.template
@@ -35,7 +35,7 @@ See the :ref:`overview` for more detail about what's in the library.
{{ single_doc[:-4] }}
{% elif single_doc %}
.. autosummary::
- :toctree: api/generated/
+ :toctree: reference/api/
{{ single_doc }}
{% else -%}
@@ -51,7 +51,7 @@ See the :ref:`overview` for more detail about what's in the library.
ecosystem
{% endif -%}
{% if include_api -%}
- api/index
+ reference/index
{% endif -%}
{% if not single_doc -%}
development/index
diff --git a/doc/source/api/arrays.rst b/doc/source/reference/arrays.rst
similarity index 93%
rename from doc/source/api/arrays.rst
rename to doc/source/reference/arrays.rst
index 5ecc5181af22c..7281f4f748d6f 100644
--- a/doc/source/api/arrays.rst
+++ b/doc/source/reference/arrays.rst
@@ -31,7 +31,7 @@ The top-level :meth:`array` method can be used to create a new array, which may
stored in a :class:`Series`, :class:`Index`, or as a column in a :class:`DataFrame`.
.. autosummary::
- :toctree: generated/
+ :toctree: api/
array
@@ -48,14 +48,14 @@ or timezone-aware values.
scalar type for timezone-naive or timezone-aware datetime data.
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Timestamp
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Timestamp.asm8
Timestamp.day
@@ -91,7 +91,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Timestamp.astimezone
Timestamp.ceil
@@ -142,7 +142,7 @@ is used.
If the data are tz-aware, then every value in the array must have the same timezone.
.. autosummary::
- :toctree: generated/
+ :toctree: api/
arrays.DatetimeArray
DatetimeTZDtype
@@ -156,14 +156,14 @@ NumPy can natively represent timedeltas. Pandas provides :class:`Timedelta`
for symmetry with :class:`Timestamp`.
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Timedelta
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Timedelta.asm8
Timedelta.components
@@ -183,7 +183,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Timedelta.ceil
Timedelta.floor
@@ -196,7 +196,7 @@ Methods
A collection of timedeltas may be stored in a :class:`TimedeltaArray`.
.. autosummary::
- :toctree: generated/
+ :toctree: api/
arrays.TimedeltaArray
@@ -210,14 +210,14 @@ Pandas represents spans of times as :class:`Period` objects.
Period
------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Period
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Period.day
Period.dayofweek
@@ -244,7 +244,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Period.asfreq
Period.now
@@ -255,7 +255,7 @@ A collection of timedeltas may be stored in a :class:`arrays.PeriodArray`.
Every period in a ``PeriodArray`` must have the same ``freq``.
.. autosummary::
- :toctree: generated/
+ :toctree: api/
arrays.DatetimeArray
PeriodDtype
@@ -268,14 +268,14 @@ Interval Data
Arbitrary intervals can be represented as :class:`Interval` objects.
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Interval
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Interval.closed
Interval.closed_left
@@ -291,7 +291,7 @@ Properties
A collection of intervals may be stored in an :class:`IntervalArray`.
.. autosummary::
- :toctree: generated/
+ :toctree: api/
IntervalArray
IntervalDtype
@@ -305,7 +305,7 @@ Nullable Integer
Pandas provides this through :class:`arrays.IntegerArray`.
.. autosummary::
- :toctree: generated/
+ :toctree: api/
arrays.IntegerArray
Int8Dtype
@@ -327,13 +327,13 @@ limited, fixed set of values. The dtype of a ``Categorical`` can be described by
a :class:`pandas.api.types.CategoricalDtype`.
.. autosummary::
- :toctree: generated/
+ :toctree: api/
:template: autosummary/class_without_autosummary.rst
CategoricalDtype
.. autosummary::
- :toctree: generated/
+ :toctree: api/
CategoricalDtype.categories
CategoricalDtype.ordered
@@ -341,7 +341,7 @@ a :class:`pandas.api.types.CategoricalDtype`.
Categorical data can be stored in a :class:`pandas.Categorical`
.. autosummary::
- :toctree: generated/
+ :toctree: api/
:template: autosummary/class_without_autosummary.rst
Categorical
@@ -350,14 +350,14 @@ The alternative :meth:`Categorical.from_codes` constructor can be used when you
have the categories and integer codes already:
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Categorical.from_codes
The dtype information is available on the ``Categorical``
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Categorical.dtype
Categorical.categories
@@ -368,7 +368,7 @@ The dtype information is available on the ``Categorical``
the Categorical back to a NumPy array, so categories and order information is not preserved!
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Categorical.__array__
@@ -391,7 +391,7 @@ Data where a single value is repeated many times (e.g. ``0`` or ``NaN``) may
be stored efficiently as a :class:`SparseArray`.
.. autosummary::
- :toctree: generated/
+ :toctree: api/
SparseArray
SparseDtype
diff --git a/doc/source/api/extensions.rst b/doc/source/reference/extensions.rst
similarity index 95%
rename from doc/source/api/extensions.rst
rename to doc/source/reference/extensions.rst
index 3972354ff9651..6146e34fab274 100644
--- a/doc/source/api/extensions.rst
+++ b/doc/source/reference/extensions.rst
@@ -11,7 +11,7 @@ These are primarily intended for library authors looking to extend pandas
objects.
.. autosummary::
- :toctree: generated/
+ :toctree: api/
api.extensions.register_extension_dtype
api.extensions.register_dataframe_accessor
diff --git a/doc/source/api/frame.rst b/doc/source/reference/frame.rst
similarity index 93%
rename from doc/source/api/frame.rst
rename to doc/source/reference/frame.rst
index de16d59fe7c40..568acd5207bd1 100644
--- a/doc/source/api/frame.rst
+++ b/doc/source/reference/frame.rst
@@ -10,7 +10,7 @@ DataFrame
Constructor
~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
DataFrame
@@ -19,13 +19,13 @@ Attributes and underlying data
**Axes**
.. autosummary::
- :toctree: generated/
+ :toctree: api/
DataFrame.index
DataFrame.columns
.. autosummary::
- :toctree: generated/
+ :toctree: api/
DataFrame.dtypes
DataFrame.ftypes
@@ -45,7 +45,7 @@ Attributes and underlying data
Conversion
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
DataFrame.astype
DataFrame.convert_objects
@@ -58,7 +58,7 @@ Conversion
Indexing, iteration
~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
DataFrame.head
DataFrame.at
@@ -88,7 +88,7 @@ For more information on ``.at``, ``.iat``, ``.loc``, and
Binary operator functions
~~~~~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
DataFrame.add
DataFrame.sub
@@ -119,7 +119,7 @@ Binary operator functions
Function application, GroupBy & Window
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
DataFrame.apply
DataFrame.applymap
@@ -137,7 +137,7 @@ Function application, GroupBy & Window
Computations / Descriptive Stats
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
DataFrame.abs
DataFrame.all
@@ -181,7 +181,7 @@ Computations / Descriptive Stats
Reindexing / Selection / Label manipulation
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
DataFrame.add_prefix
DataFrame.add_suffix
@@ -217,7 +217,7 @@ Reindexing / Selection / Label manipulation
Missing data handling
~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
DataFrame.dropna
DataFrame.fillna
@@ -227,7 +227,7 @@ Missing data handling
Reshaping, sorting, transposing
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
DataFrame.droplevel
DataFrame.pivot
@@ -251,7 +251,7 @@ Reshaping, sorting, transposing
Combining / joining / merging
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
DataFrame.append
DataFrame.assign
@@ -262,7 +262,7 @@ Combining / joining / merging
Time series-related
~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
DataFrame.asfreq
DataFrame.asof
@@ -285,13 +285,13 @@ Plotting
specific plotting methods of the form ``DataFrame.plot.<kind>``.
.. autosummary::
- :toctree: generated/
+ :toctree: api/
:template: autosummary/accessor_callable.rst
DataFrame.plot
.. autosummary::
- :toctree: generated/
+ :toctree: api/
:template: autosummary/accessor_method.rst
DataFrame.plot.area
@@ -307,7 +307,7 @@ specific plotting methods of the form ``DataFrame.plot.<kind>``.
DataFrame.plot.scatter
.. autosummary::
- :toctree: generated/
+ :toctree: api/
DataFrame.boxplot
DataFrame.hist
@@ -315,7 +315,7 @@ specific plotting methods of the form ``DataFrame.plot.<kind>``.
Serialization / IO / Conversion
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
DataFrame.from_csv
DataFrame.from_dict
@@ -346,6 +346,6 @@ Serialization / IO / Conversion
Sparse
~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
SparseDataFrame.to_coo
diff --git a/doc/source/api/general_functions.rst b/doc/source/reference/general_functions.rst
similarity index 84%
rename from doc/source/api/general_functions.rst
rename to doc/source/reference/general_functions.rst
index cef5d8cac6abc..b5832cb8aa591 100644
--- a/doc/source/api/general_functions.rst
+++ b/doc/source/reference/general_functions.rst
@@ -10,7 +10,7 @@ General functions
Data manipulations
~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
melt
pivot
@@ -30,7 +30,7 @@ Data manipulations
Top-level missing data
~~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
isna
isnull
@@ -40,14 +40,14 @@ Top-level missing data
Top-level conversions
~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
to_numeric
Top-level dealing with datetimelike
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
to_datetime
to_timedelta
@@ -60,21 +60,21 @@ Top-level dealing with datetimelike
Top-level dealing with intervals
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
interval_range
Top-level evaluation
~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
eval
Hashing
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
util.hash_array
util.hash_pandas_object
@@ -82,6 +82,6 @@ Hashing
Testing
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
test
diff --git a/doc/source/api/general_utility_functions.rst b/doc/source/reference/general_utility_functions.rst
similarity index 93%
rename from doc/source/api/general_utility_functions.rst
rename to doc/source/reference/general_utility_functions.rst
index e151f8f57ed5e..9c69770c0f1b7 100644
--- a/doc/source/api/general_utility_functions.rst
+++ b/doc/source/reference/general_utility_functions.rst
@@ -10,7 +10,7 @@ General utility functions
Working with options
--------------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
describe_option
reset_option
@@ -21,7 +21,7 @@ Working with options
Testing functions
-----------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
testing.assert_frame_equal
testing.assert_series_equal
@@ -30,7 +30,7 @@ Testing functions
Exceptions and warnings
-----------------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
errors.DtypeWarning
errors.EmptyDataError
@@ -44,7 +44,7 @@ Exceptions and warnings
Data types related functionality
--------------------------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
api.types.union_categoricals
api.types.infer_dtype
@@ -53,7 +53,7 @@ Data types related functionality
Dtype introspection
~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
api.types.is_bool_dtype
api.types.is_categorical_dtype
@@ -81,7 +81,7 @@ Dtype introspection
Iterable introspection
~~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
api.types.is_dict_like
api.types.is_file_like
@@ -92,7 +92,7 @@ Iterable introspection
Scalar introspection
~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
api.types.is_bool
api.types.is_categorical
diff --git a/doc/source/api/groupby.rst b/doc/source/reference/groupby.rst
similarity index 94%
rename from doc/source/api/groupby.rst
rename to doc/source/reference/groupby.rst
index d67c7e0889522..6ed85ff2fac43 100644
--- a/doc/source/api/groupby.rst
+++ b/doc/source/reference/groupby.rst
@@ -12,7 +12,7 @@ GroupBy objects are returned by groupby calls: :func:`pandas.DataFrame.groupby`,
Indexing, iteration
-------------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
GroupBy.__iter__
GroupBy.groups
@@ -22,7 +22,7 @@ Indexing, iteration
.. currentmodule:: pandas
.. autosummary::
- :toctree: generated/
+ :toctree: api/
:template: autosummary/class_without_autosummary.rst
Grouper
@@ -32,7 +32,7 @@ Indexing, iteration
Function application
--------------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
GroupBy.apply
GroupBy.agg
@@ -43,7 +43,7 @@ Function application
Computations / Descriptive Stats
--------------------------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
GroupBy.all
GroupBy.any
@@ -78,7 +78,7 @@ axis argument, and often an argument indicating whether to restrict
application to columns of a specific data type.
.. autosummary::
- :toctree: generated/
+ :toctree: api/
DataFrameGroupBy.all
DataFrameGroupBy.any
@@ -113,7 +113,7 @@ application to columns of a specific data type.
The following methods are available only for ``SeriesGroupBy`` objects.
.. autosummary::
- :toctree: generated/
+ :toctree: api/
SeriesGroupBy.nlargest
SeriesGroupBy.nsmallest
@@ -126,7 +126,7 @@ The following methods are available only for ``SeriesGroupBy`` objects.
The following methods are available only for ``DataFrameGroupBy`` objects.
.. autosummary::
- :toctree: generated/
+ :toctree: api/
DataFrameGroupBy.corrwith
DataFrameGroupBy.boxplot
diff --git a/doc/source/api/index.rst b/doc/source/reference/index.rst
similarity index 56%
rename from doc/source/api/index.rst
rename to doc/source/reference/index.rst
index e4d118e278128..ef4676054473a 100644
--- a/doc/source/api/index.rst
+++ b/doc/source/reference/index.rst
@@ -44,31 +44,31 @@ public functions related to data types in pandas.
.. toctree::
:hidden:
- generated/pandas.DataFrame.blocks
- generated/pandas.DataFrame.as_matrix
- generated/pandas.DataFrame.ix
- generated/pandas.Index.asi8
- generated/pandas.Index.data
- generated/pandas.Index.flags
- generated/pandas.Index.holds_integer
- generated/pandas.Index.is_type_compatible
- generated/pandas.Index.nlevels
- generated/pandas.Index.sort
- generated/pandas.Panel.agg
- generated/pandas.Panel.aggregate
- generated/pandas.Panel.blocks
- generated/pandas.Panel.empty
- generated/pandas.Panel.is_copy
- generated/pandas.Panel.items
- generated/pandas.Panel.ix
- generated/pandas.Panel.major_axis
- generated/pandas.Panel.minor_axis
- generated/pandas.Series.asobject
- generated/pandas.Series.blocks
- generated/pandas.Series.from_array
- generated/pandas.Series.ix
- generated/pandas.Series.imag
- generated/pandas.Series.real
+ api/pandas.DataFrame.blocks
+ api/pandas.DataFrame.as_matrix
+ api/pandas.DataFrame.ix
+ api/pandas.Index.asi8
+ api/pandas.Index.data
+ api/pandas.Index.flags
+ api/pandas.Index.holds_integer
+ api/pandas.Index.is_type_compatible
+ api/pandas.Index.nlevels
+ api/pandas.Index.sort
+ api/pandas.Panel.agg
+ api/pandas.Panel.aggregate
+ api/pandas.Panel.blocks
+ api/pandas.Panel.empty
+ api/pandas.Panel.is_copy
+ api/pandas.Panel.items
+ api/pandas.Panel.ix
+ api/pandas.Panel.major_axis
+ api/pandas.Panel.minor_axis
+ api/pandas.Series.asobject
+ api/pandas.Series.blocks
+ api/pandas.Series.from_array
+ api/pandas.Series.ix
+ api/pandas.Series.imag
+ api/pandas.Series.real
.. Can't convince sphinx to generate toctree for this class attribute.
@@ -77,4 +77,4 @@ public functions related to data types in pandas.
.. toctree::
:hidden:
- generated/pandas.api.extensions.ExtensionDtype.na_value
+ api/pandas.api.extensions.ExtensionDtype.na_value
diff --git a/doc/source/api/indexing.rst b/doc/source/reference/indexing.rst
similarity index 91%
rename from doc/source/api/indexing.rst
rename to doc/source/reference/indexing.rst
index d27b05322c1f2..680cb7e3dac91 100644
--- a/doc/source/api/indexing.rst
+++ b/doc/source/reference/indexing.rst
@@ -15,14 +15,14 @@ that contain an index (Series/DataFrame) and those should most likely be
used before calling these methods directly.**
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Index
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Index.values
Index.is_monotonic
@@ -51,7 +51,7 @@ Properties
Modifying and Computations
~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Index.all
Index.any
@@ -90,7 +90,7 @@ Modifying and Computations
Compatibility with MultiIndex
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Index.set_names
Index.is_lexsorted_for_tuple
@@ -99,7 +99,7 @@ Compatibility with MultiIndex
Missing Values
~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Index.fillna
Index.dropna
@@ -109,7 +109,7 @@ Missing Values
Conversion
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Index.astype
Index.item
@@ -124,7 +124,7 @@ Conversion
Sorting
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Index.argsort
Index.searchsorted
@@ -133,14 +133,14 @@ Sorting
Time-specific operations
~~~~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Index.shift
Combining / joining / set operations
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Index.append
Index.join
@@ -152,7 +152,7 @@ Combining / joining / set operations
Selecting
~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Index.asof
Index.asof_locs
@@ -176,7 +176,7 @@ Selecting
Numeric Index
-------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
:template: autosummary/class_without_autosummary.rst
RangeIndex
@@ -188,7 +188,7 @@ Numeric Index
.. Separate block, since they aren't classes.
.. autosummary::
- :toctree: generated/
+ :toctree: api/
RangeIndex.from_range
@@ -197,7 +197,7 @@ Numeric Index
CategoricalIndex
----------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
:template: autosummary/class_without_autosummary.rst
CategoricalIndex
@@ -205,7 +205,7 @@ CategoricalIndex
Categorical Components
~~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
CategoricalIndex.codes
CategoricalIndex.categories
@@ -222,7 +222,7 @@ Categorical Components
Modifying and Computations
~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
CategoricalIndex.map
CategoricalIndex.equals
@@ -232,7 +232,7 @@ Modifying and Computations
IntervalIndex
-------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
:template: autosummary/class_without_autosummary.rst
IntervalIndex
@@ -240,7 +240,7 @@ IntervalIndex
IntervalIndex Components
~~~~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
IntervalIndex.from_arrays
IntervalIndex.from_tuples
@@ -265,20 +265,20 @@ IntervalIndex Components
MultiIndex
----------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
:template: autosummary/class_without_autosummary.rst
MultiIndex
.. autosummary::
- :toctree: generated/
+ :toctree: api/
IndexSlice
MultiIndex Constructors
~~~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
MultiIndex.from_arrays
MultiIndex.from_tuples
@@ -288,7 +288,7 @@ MultiIndex Constructors
MultiIndex Properties
~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
MultiIndex.names
MultiIndex.levels
@@ -299,7 +299,7 @@ MultiIndex Properties
MultiIndex Components
~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
MultiIndex.set_levels
MultiIndex.set_codes
@@ -316,7 +316,7 @@ MultiIndex Components
MultiIndex Selecting
~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
MultiIndex.get_loc
MultiIndex.get_loc_level
@@ -328,7 +328,7 @@ MultiIndex Selecting
DatetimeIndex
-------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
:template: autosummary/class_without_autosummary.rst
DatetimeIndex
@@ -336,7 +336,7 @@ DatetimeIndex
Time/Date Components
~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
DatetimeIndex.year
DatetimeIndex.month
@@ -370,7 +370,7 @@ Time/Date Components
Selecting
~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
DatetimeIndex.indexer_at_time
DatetimeIndex.indexer_between_time
@@ -379,7 +379,7 @@ Selecting
Time-specific operations
~~~~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
DatetimeIndex.normalize
DatetimeIndex.strftime
@@ -395,7 +395,7 @@ Time-specific operations
Conversion
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
DatetimeIndex.to_period
DatetimeIndex.to_perioddelta
@@ -406,7 +406,7 @@ Conversion
TimedeltaIndex
--------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
:template: autosummary/class_without_autosummary.rst
TimedeltaIndex
@@ -414,7 +414,7 @@ TimedeltaIndex
Components
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
TimedeltaIndex.days
TimedeltaIndex.seconds
@@ -426,7 +426,7 @@ Components
Conversion
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
TimedeltaIndex.to_pytimedelta
TimedeltaIndex.to_series
@@ -440,7 +440,7 @@ Conversion
PeriodIndex
-----------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
:template: autosummary/class_without_autosummary.rst
PeriodIndex
@@ -448,7 +448,7 @@ PeriodIndex
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
PeriodIndex.day
PeriodIndex.dayofweek
@@ -474,7 +474,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
PeriodIndex.asfreq
PeriodIndex.strftime
diff --git a/doc/source/api/io.rst b/doc/source/reference/io.rst
similarity index 78%
rename from doc/source/api/io.rst
rename to doc/source/reference/io.rst
index f2060b7c05413..9c776e3ff8a82 100644
--- a/doc/source/api/io.rst
+++ b/doc/source/reference/io.rst
@@ -10,14 +10,14 @@ Input/Output
Pickling
~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
read_pickle
Flat File
~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
read_table
read_csv
@@ -27,20 +27,20 @@ Flat File
Clipboard
~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
read_clipboard
Excel
~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
read_excel
ExcelFile.parse
.. autosummary::
- :toctree: generated/
+ :toctree: api/
:template: autosummary/class_without_autosummary.rst
ExcelWriter
@@ -48,14 +48,14 @@ Excel
JSON
~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
read_json
.. currentmodule:: pandas.io.json
.. autosummary::
- :toctree: generated/
+ :toctree: api/
json_normalize
build_table_schema
@@ -65,14 +65,14 @@ JSON
HTML
~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
read_html
HDFStore: PyTables (HDF5)
~~~~~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
read_hdf
HDFStore.put
@@ -87,28 +87,28 @@ HDFStore: PyTables (HDF5)
Feather
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
read_feather
Parquet
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
read_parquet
SAS
~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
read_sas
SQL
~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
read_sql_table
read_sql_query
@@ -117,21 +117,21 @@ SQL
Google BigQuery
~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
read_gbq
STATA
~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
read_stata
.. currentmodule:: pandas.io.stata
.. autosummary::
- :toctree: generated/
+ :toctree: api/
StataReader.data
StataReader.data_label
diff --git a/doc/source/api/offset_frequency.rst b/doc/source/reference/offset_frequency.rst
similarity index 84%
rename from doc/source/api/offset_frequency.rst
rename to doc/source/reference/offset_frequency.rst
index 42894fe8d7f2f..ccc1c7e171d22 100644
--- a/doc/source/api/offset_frequency.rst
+++ b/doc/source/reference/offset_frequency.rst
@@ -10,14 +10,14 @@ Date Offsets
DateOffset
----------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
DateOffset
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
DateOffset.freqstr
DateOffset.kwds
@@ -29,7 +29,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
DateOffset.apply
DateOffset.copy
@@ -39,14 +39,14 @@ Methods
BusinessDay
-----------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
BusinessDay
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
BusinessDay.freqstr
BusinessDay.kwds
@@ -58,7 +58,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
BusinessDay.apply
BusinessDay.apply_index
@@ -69,14 +69,14 @@ Methods
BusinessHour
------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
BusinessHour
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
BusinessHour.freqstr
BusinessHour.kwds
@@ -88,7 +88,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
BusinessHour.apply
BusinessHour.copy
@@ -98,14 +98,14 @@ Methods
CustomBusinessDay
-----------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
CustomBusinessDay
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
CustomBusinessDay.freqstr
CustomBusinessDay.kwds
@@ -117,7 +117,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
CustomBusinessDay.apply
CustomBusinessDay.copy
@@ -127,14 +127,14 @@ Methods
CustomBusinessHour
------------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
CustomBusinessHour
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
CustomBusinessHour.freqstr
CustomBusinessHour.kwds
@@ -146,7 +146,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
CustomBusinessHour.apply
CustomBusinessHour.copy
@@ -156,14 +156,14 @@ Methods
MonthOffset
-----------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
MonthOffset
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
MonthOffset.freqstr
MonthOffset.kwds
@@ -175,7 +175,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
MonthOffset.apply
MonthOffset.apply_index
@@ -186,14 +186,14 @@ Methods
MonthEnd
--------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
MonthEnd
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
MonthEnd.freqstr
MonthEnd.kwds
@@ -205,7 +205,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
MonthEnd.apply
MonthEnd.apply_index
@@ -216,14 +216,14 @@ Methods
MonthBegin
----------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
MonthBegin
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
MonthBegin.freqstr
MonthBegin.kwds
@@ -235,7 +235,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
MonthBegin.apply
MonthBegin.apply_index
@@ -246,14 +246,14 @@ Methods
BusinessMonthEnd
----------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
BusinessMonthEnd
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
BusinessMonthEnd.freqstr
BusinessMonthEnd.kwds
@@ -265,7 +265,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
BusinessMonthEnd.apply
BusinessMonthEnd.apply_index
@@ -276,14 +276,14 @@ Methods
BusinessMonthBegin
------------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
BusinessMonthBegin
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
BusinessMonthBegin.freqstr
BusinessMonthBegin.kwds
@@ -295,7 +295,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
BusinessMonthBegin.apply
BusinessMonthBegin.apply_index
@@ -306,14 +306,14 @@ Methods
CustomBusinessMonthEnd
----------------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
CustomBusinessMonthEnd
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
CustomBusinessMonthEnd.freqstr
CustomBusinessMonthEnd.kwds
@@ -326,7 +326,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
CustomBusinessMonthEnd.apply
CustomBusinessMonthEnd.copy
@@ -336,14 +336,14 @@ Methods
CustomBusinessMonthBegin
------------------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
CustomBusinessMonthBegin
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
CustomBusinessMonthBegin.freqstr
CustomBusinessMonthBegin.kwds
@@ -356,7 +356,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
CustomBusinessMonthBegin.apply
CustomBusinessMonthBegin.copy
@@ -366,14 +366,14 @@ Methods
SemiMonthOffset
---------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
SemiMonthOffset
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
SemiMonthOffset.freqstr
SemiMonthOffset.kwds
@@ -385,7 +385,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
SemiMonthOffset.apply
SemiMonthOffset.apply_index
@@ -396,14 +396,14 @@ Methods
SemiMonthEnd
------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
SemiMonthEnd
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
SemiMonthEnd.freqstr
SemiMonthEnd.kwds
@@ -415,7 +415,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
SemiMonthEnd.apply
SemiMonthEnd.apply_index
@@ -426,14 +426,14 @@ Methods
SemiMonthBegin
--------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
SemiMonthBegin
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
SemiMonthBegin.freqstr
SemiMonthBegin.kwds
@@ -445,7 +445,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
SemiMonthBegin.apply
SemiMonthBegin.apply_index
@@ -456,14 +456,14 @@ Methods
Week
----
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Week
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Week.freqstr
Week.kwds
@@ -475,7 +475,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Week.apply
Week.apply_index
@@ -486,14 +486,14 @@ Methods
WeekOfMonth
-----------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
WeekOfMonth
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
WeekOfMonth.freqstr
WeekOfMonth.kwds
@@ -505,7 +505,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
WeekOfMonth.apply
WeekOfMonth.copy
@@ -515,14 +515,14 @@ Methods
LastWeekOfMonth
---------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
LastWeekOfMonth
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
LastWeekOfMonth.freqstr
LastWeekOfMonth.kwds
@@ -534,7 +534,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
LastWeekOfMonth.apply
LastWeekOfMonth.copy
@@ -544,14 +544,14 @@ Methods
QuarterOffset
-------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
QuarterOffset
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
QuarterOffset.freqstr
QuarterOffset.kwds
@@ -563,7 +563,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
QuarterOffset.apply
QuarterOffset.apply_index
@@ -574,14 +574,14 @@ Methods
BQuarterEnd
-----------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
BQuarterEnd
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
BQuarterEnd.freqstr
BQuarterEnd.kwds
@@ -593,7 +593,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
BQuarterEnd.apply
BQuarterEnd.apply_index
@@ -604,14 +604,14 @@ Methods
BQuarterBegin
-------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
BQuarterBegin
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
BQuarterBegin.freqstr
BQuarterBegin.kwds
@@ -623,7 +623,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
BQuarterBegin.apply
BQuarterBegin.apply_index
@@ -634,14 +634,14 @@ Methods
QuarterEnd
----------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
QuarterEnd
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
QuarterEnd.freqstr
QuarterEnd.kwds
@@ -653,7 +653,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
QuarterEnd.apply
QuarterEnd.apply_index
@@ -664,14 +664,14 @@ Methods
QuarterBegin
------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
QuarterBegin
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
QuarterBegin.freqstr
QuarterBegin.kwds
@@ -683,7 +683,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
QuarterBegin.apply
QuarterBegin.apply_index
@@ -694,14 +694,14 @@ Methods
YearOffset
----------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
YearOffset
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
YearOffset.freqstr
YearOffset.kwds
@@ -713,7 +713,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
YearOffset.apply
YearOffset.apply_index
@@ -724,14 +724,14 @@ Methods
BYearEnd
--------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
BYearEnd
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
BYearEnd.freqstr
BYearEnd.kwds
@@ -743,7 +743,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
BYearEnd.apply
BYearEnd.apply_index
@@ -754,14 +754,14 @@ Methods
BYearBegin
----------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
BYearBegin
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
BYearBegin.freqstr
BYearBegin.kwds
@@ -773,7 +773,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
BYearBegin.apply
BYearBegin.apply_index
@@ -784,14 +784,14 @@ Methods
YearEnd
-------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
YearEnd
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
YearEnd.freqstr
YearEnd.kwds
@@ -803,7 +803,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
YearEnd.apply
YearEnd.apply_index
@@ -814,14 +814,14 @@ Methods
YearBegin
---------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
YearBegin
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
YearBegin.freqstr
YearBegin.kwds
@@ -833,7 +833,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
YearBegin.apply
YearBegin.apply_index
@@ -844,14 +844,14 @@ Methods
FY5253
------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
FY5253
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
FY5253.freqstr
FY5253.kwds
@@ -863,7 +863,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
FY5253.apply
FY5253.copy
@@ -875,14 +875,14 @@ Methods
FY5253Quarter
-------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
FY5253Quarter
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
FY5253Quarter.freqstr
FY5253Quarter.kwds
@@ -894,7 +894,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
FY5253Quarter.apply
FY5253Quarter.copy
@@ -906,14 +906,14 @@ Methods
Easter
------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Easter
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Easter.freqstr
Easter.kwds
@@ -925,7 +925,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Easter.apply
Easter.copy
@@ -935,14 +935,14 @@ Methods
Tick
----
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Tick
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Tick.delta
Tick.freqstr
@@ -955,7 +955,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Tick.copy
Tick.isAnchored
@@ -964,14 +964,14 @@ Methods
Day
---
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Day
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Day.delta
Day.freqstr
@@ -984,7 +984,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Day.copy
Day.isAnchored
@@ -993,14 +993,14 @@ Methods
Hour
----
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Hour
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Hour.delta
Hour.freqstr
@@ -1013,7 +1013,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Hour.copy
Hour.isAnchored
@@ -1022,14 +1022,14 @@ Methods
Minute
------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Minute
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Minute.delta
Minute.freqstr
@@ -1042,7 +1042,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Minute.copy
Minute.isAnchored
@@ -1051,14 +1051,14 @@ Methods
Second
------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Second
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Second.delta
Second.freqstr
@@ -1071,7 +1071,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Second.copy
Second.isAnchored
@@ -1080,14 +1080,14 @@ Methods
Milli
-----
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Milli
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Milli.delta
Milli.freqstr
@@ -1100,7 +1100,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Milli.copy
Milli.isAnchored
@@ -1109,14 +1109,14 @@ Methods
Micro
-----
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Micro
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Micro.delta
Micro.freqstr
@@ -1129,7 +1129,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Micro.copy
Micro.isAnchored
@@ -1138,14 +1138,14 @@ Methods
Nano
----
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Nano
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Nano.delta
Nano.freqstr
@@ -1158,7 +1158,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Nano.copy
Nano.isAnchored
@@ -1167,14 +1167,14 @@ Methods
BDay
----
.. autosummary::
- :toctree: generated/
+ :toctree: api/
BDay
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
BDay.base
BDay.freqstr
@@ -1188,7 +1188,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
BDay.apply
BDay.apply_index
@@ -1201,14 +1201,14 @@ Methods
BMonthEnd
---------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
BMonthEnd
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
BMonthEnd.base
BMonthEnd.freqstr
@@ -1221,7 +1221,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
BMonthEnd.apply
BMonthEnd.apply_index
@@ -1234,14 +1234,14 @@ Methods
BMonthBegin
-----------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
BMonthBegin
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
BMonthBegin.base
BMonthBegin.freqstr
@@ -1254,7 +1254,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
BMonthBegin.apply
BMonthBegin.apply_index
@@ -1267,14 +1267,14 @@ Methods
CBMonthEnd
----------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
CBMonthEnd
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
CBMonthEnd.base
CBMonthEnd.cbday_roll
@@ -1291,7 +1291,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
CBMonthEnd.apply
CBMonthEnd.apply_index
@@ -1304,14 +1304,14 @@ Methods
CBMonthBegin
------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
CBMonthBegin
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
CBMonthBegin.base
CBMonthBegin.cbday_roll
@@ -1328,7 +1328,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
CBMonthBegin.apply
CBMonthBegin.apply_index
@@ -1341,14 +1341,14 @@ Methods
CDay
----
.. autosummary::
- :toctree: generated/
+ :toctree: api/
CDay
Properties
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
CDay.base
CDay.freqstr
@@ -1362,7 +1362,7 @@ Properties
Methods
~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
CDay.apply
CDay.apply_index
@@ -1382,6 +1382,6 @@ Frequencies
.. _api.offsets:
.. autosummary::
- :toctree: generated/
+ :toctree: api/
to_offset
diff --git a/doc/source/api/panel.rst b/doc/source/reference/panel.rst
similarity index 90%
rename from doc/source/api/panel.rst
rename to doc/source/reference/panel.rst
index 4edcd22d2685d..39c8ba0828859 100644
--- a/doc/source/api/panel.rst
+++ b/doc/source/reference/panel.rst
@@ -10,7 +10,7 @@ Panel
Constructor
~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Panel
@@ -23,7 +23,7 @@ Properties and underlying data
* **minor_axis**: axis 2; the columns of each of the DataFrames
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Panel.values
Panel.axes
@@ -38,7 +38,7 @@ Properties and underlying data
Conversion
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Panel.astype
Panel.copy
@@ -48,7 +48,7 @@ Conversion
Getting and setting
~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Panel.get_value
Panel.set_value
@@ -56,7 +56,7 @@ Getting and setting
Indexing, iteration, slicing
~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Panel.at
Panel.iat
@@ -75,7 +75,7 @@ For more information on ``.at``, ``.iat``, ``.loc``, and
Binary operator functions
~~~~~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Panel.add
Panel.sub
@@ -103,7 +103,7 @@ Binary operator functions
Function application, GroupBy
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Panel.apply
Panel.groupby
@@ -113,7 +113,7 @@ Function application, GroupBy
Computations / Descriptive Stats
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Panel.abs
Panel.clip
@@ -139,7 +139,7 @@ Computations / Descriptive Stats
Reindexing / Selection / Label manipulation
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Panel.add_prefix
Panel.add_suffix
@@ -160,14 +160,14 @@ Reindexing / Selection / Label manipulation
Missing data handling
~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Panel.dropna
Reshaping, sorting, transposing
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Panel.sort_index
Panel.swaplevel
@@ -178,7 +178,7 @@ Reshaping, sorting, transposing
Combining / joining / merging
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Panel.join
Panel.update
@@ -186,7 +186,7 @@ Combining / joining / merging
Time series-related
~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Panel.asfreq
Panel.shift
@@ -197,7 +197,7 @@ Time series-related
Serialization / IO / Conversion
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Panel.from_dict
Panel.to_pickle
diff --git a/doc/source/api/plotting.rst b/doc/source/reference/plotting.rst
similarity index 93%
rename from doc/source/api/plotting.rst
rename to doc/source/reference/plotting.rst
index c4e6333ebda37..7615e1d20f5e2 100644
--- a/doc/source/api/plotting.rst
+++ b/doc/source/reference/plotting.rst
@@ -10,7 +10,7 @@ Plotting
The following functions are contained in the `pandas.plotting` module.
.. autosummary::
- :toctree: generated/
+ :toctree: api/
andrews_curves
bootstrap_plot
diff --git a/doc/source/api/resampling.rst b/doc/source/reference/resampling.rst
similarity index 91%
rename from doc/source/api/resampling.rst
rename to doc/source/reference/resampling.rst
index f5c6ccce3cdd7..2a52defa3c68f 100644
--- a/doc/source/api/resampling.rst
+++ b/doc/source/reference/resampling.rst
@@ -12,7 +12,7 @@ Resampler objects are returned by resample calls: :func:`pandas.DataFrame.resamp
Indexing, iteration
~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Resampler.__iter__
Resampler.groups
@@ -22,7 +22,7 @@ Indexing, iteration
Function application
~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Resampler.apply
Resampler.aggregate
@@ -32,7 +32,7 @@ Function application
Upsampling
~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Resampler.ffill
Resampler.backfill
@@ -46,7 +46,7 @@ Upsampling
Computations / Descriptive Stats
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Resampler.count
Resampler.nunique
diff --git a/doc/source/api/series.rst b/doc/source/reference/series.rst
similarity index 93%
rename from doc/source/api/series.rst
rename to doc/source/reference/series.rst
index aa43c8b643d44..a6ac40b5203bf 100644
--- a/doc/source/api/series.rst
+++ b/doc/source/reference/series.rst
@@ -10,7 +10,7 @@ Series
Constructor
-----------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Series
@@ -19,12 +19,12 @@ Attributes
**Axes**
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Series.index
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Series.array
Series.values
@@ -52,7 +52,7 @@ Attributes
Conversion
----------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Series.astype
Series.infer_objects
@@ -69,7 +69,7 @@ Conversion
Indexing, iteration
-------------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Series.get
Series.at
@@ -90,7 +90,7 @@ For more information on ``.at``, ``.iat``, ``.loc``, and
Binary operator functions
-------------------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Series.add
Series.sub
@@ -123,7 +123,7 @@ Binary operator functions
Function application, GroupBy & Window
--------------------------------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Series.apply
Series.agg
@@ -141,7 +141,7 @@ Function application, GroupBy & Window
Computations / Descriptive Stats
--------------------------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Series.abs
Series.all
@@ -192,7 +192,7 @@ Computations / Descriptive Stats
Reindexing / Selection / Label manipulation
-------------------------------------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Series.align
Series.drop
@@ -226,7 +226,7 @@ Reindexing / Selection / Label manipulation
Missing data handling
---------------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Series.isna
Series.notna
@@ -237,7 +237,7 @@ Missing data handling
Reshaping, sorting
------------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Series.argsort
Series.argmin
@@ -256,7 +256,7 @@ Reshaping, sorting
Combining / joining / merging
-----------------------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Series.append
Series.replace
@@ -265,7 +265,7 @@ Combining / joining / merging
Time series-related
-------------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Series.asfreq
Series.asof
@@ -309,7 +309,7 @@ Datetime Properties
^^^^^^^^^^^^^^^^^^^
.. autosummary::
- :toctree: generated/
+ :toctree: api/
:template: autosummary/accessor_attribute.rst
Series.dt.date
@@ -345,7 +345,7 @@ Datetime Methods
^^^^^^^^^^^^^^^^
.. autosummary::
- :toctree: generated/
+ :toctree: api/
:template: autosummary/accessor_method.rst
Series.dt.to_period
@@ -364,7 +364,7 @@ Period Properties
^^^^^^^^^^^^^^^^^
.. autosummary::
- :toctree: generated/
+ :toctree: api/
:template: autosummary/accessor_attribute.rst
Series.dt.qyear
@@ -375,7 +375,7 @@ Timedelta Properties
^^^^^^^^^^^^^^^^^^^^
.. autosummary::
- :toctree: generated/
+ :toctree: api/
:template: autosummary/accessor_attribute.rst
Series.dt.days
@@ -388,7 +388,7 @@ Timedelta Methods
^^^^^^^^^^^^^^^^^
.. autosummary::
- :toctree: generated/
+ :toctree: api/
:template: autosummary/accessor_method.rst
Series.dt.to_pytimedelta
@@ -405,7 +405,7 @@ strings and apply several methods to it. These can be accessed like
``Series.str.<function/property>``.
.. autosummary::
- :toctree: generated/
+ :toctree: api/
:template: autosummary/accessor_method.rst
Series.str.capitalize
@@ -467,7 +467,7 @@ strings and apply several methods to it. These can be accessed like
..
.. autosummary::
- :toctree: generated/
+ :toctree: api/
:template: autosummary/accessor.rst
Series.str
@@ -484,7 +484,7 @@ Categorical-dtype specific methods and attributes are available under
the ``Series.cat`` accessor.
.. autosummary::
- :toctree: generated/
+ :toctree: api/
:template: autosummary/accessor_attribute.rst
Series.cat.categories
@@ -492,7 +492,7 @@ the ``Series.cat`` accessor.
Series.cat.codes
.. autosummary::
- :toctree: generated/
+ :toctree: api/
:template: autosummary/accessor_method.rst
Series.cat.rename_categories
@@ -514,7 +514,7 @@ Sparse-dtype specific methods and attributes are provided under the
``Series.sparse`` accessor.
.. autosummary::
- :toctree: generated/
+ :toctree: api/
:template: autosummary/accessor_attribute.rst
Series.sparse.npoints
@@ -523,7 +523,7 @@ Sparse-dtype specific methods and attributes are provided under the
Series.sparse.sp_values
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Series.sparse.from_coo
Series.sparse.to_coo
@@ -535,13 +535,13 @@ Plotting
specific plotting methods of the form ``Series.plot.<kind>``.
.. autosummary::
- :toctree: generated/
+ :toctree: api/
:template: autosummary/accessor_callable.rst
Series.plot
.. autosummary::
- :toctree: generated/
+ :toctree: api/
:template: autosummary/accessor_method.rst
Series.plot.area
@@ -555,14 +555,14 @@ specific plotting methods of the form ``Series.plot.<kind>``.
Series.plot.pie
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Series.hist
Serialization / IO / Conversion
-------------------------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Series.to_pickle
Series.to_csv
@@ -585,7 +585,7 @@ Sparse
------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
SparseSeries.to_coo
SparseSeries.from_coo
diff --git a/doc/source/api/style.rst b/doc/source/reference/style.rst
similarity index 88%
rename from doc/source/api/style.rst
rename to doc/source/reference/style.rst
index 70913bbec410d..bd9635b41e343 100644
--- a/doc/source/api/style.rst
+++ b/doc/source/reference/style.rst
@@ -12,7 +12,7 @@ Style
Styler Constructor
------------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Styler
Styler.from_custom_template
@@ -20,7 +20,7 @@ Styler Constructor
Styler Properties
-----------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Styler.env
Styler.template
@@ -29,7 +29,7 @@ Styler Properties
Style Application
-----------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Styler.apply
Styler.applymap
@@ -47,7 +47,7 @@ Style Application
Builtin Styles
--------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Styler.highlight_max
Styler.highlight_min
@@ -58,7 +58,7 @@ Builtin Styles
Style Export and Import
-----------------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Styler.render
Styler.export
diff --git a/doc/source/api/window.rst b/doc/source/reference/window.rst
similarity index 95%
rename from doc/source/api/window.rst
rename to doc/source/reference/window.rst
index 3245f5f831688..9e1374a3bd8e4 100644
--- a/doc/source/api/window.rst
+++ b/doc/source/reference/window.rst
@@ -14,7 +14,7 @@ EWM objects are returned by ``.ewm`` calls: :func:`pandas.DataFrame.ewm`, :func:
Standard moving window functions
--------------------------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Rolling.count
Rolling.sum
@@ -39,7 +39,7 @@ Standard moving window functions
Standard expanding window functions
-----------------------------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
Expanding.count
Expanding.sum
@@ -60,7 +60,7 @@ Standard expanding window functions
Exponentially-weighted moving window functions
----------------------------------------------
.. autosummary::
- :toctree: generated/
+ :toctree: api/
EWM.mean
EWM.std
diff --git a/doc/source/user_guide/io.rst b/doc/source/user_guide/io.rst
index 0132392aacaff..58e1b2370c7c8 100644
--- a/doc/source/user_guide/io.rst
+++ b/doc/source/user_guide/io.rst
@@ -4850,7 +4850,7 @@ See also some :ref:`cookbook examples <cookbook.sql>` for some advanced strategi
The key functions are:
.. autosummary::
- :toctree: generated/
+ :toctree: ../reference/api/
read_sql_table
read_sql_query
diff --git a/scripts/validate_docstrings.py b/scripts/validate_docstrings.py
index 4e389aed2b0d2..bce33f7e78daa 100755
--- a/scripts/validate_docstrings.py
+++ b/scripts/validate_docstrings.py
@@ -796,7 +796,8 @@ def validate_all(prefix, ignore_deprecated=False):
seen = {}
# functions from the API docs
- api_doc_fnames = os.path.join(BASE_PATH, 'doc', 'source', 'api', '*.rst')
+ api_doc_fnames = os.path.join(
+ BASE_PATH, 'doc', 'source', 'reference', '*.rst')
api_items = []
for api_doc_fname in glob.glob(api_doc_fnames):
with open(api_doc_fname) as f:
From 0bc2d3e0bf81019ece6003113e8e2ef0e24382b4 Mon Sep 17 00:00:00 2001
From: Marc Garcia <garcia.marc@gmail.com>
Date: Fri, 25 Jan 2019 13:19:32 +0000
Subject: [PATCH 25/48] DOC: Making home page links more compact and clearer
(#24928)
---
doc/source/index.rst.template | 23 +++++++++--------------
1 file changed, 9 insertions(+), 14 deletions(-)
diff --git a/doc/source/index.rst.template b/doc/source/index.rst.template
index 45ebbbc870ca3..55b95868c01dd 100644
--- a/doc/source/index.rst.template
+++ b/doc/source/index.rst.template
@@ -1,26 +1,21 @@
.. pandas documentation master file, created by
+.. module:: pandas
+
*********************************************
pandas: powerful Python data analysis toolkit
*********************************************
-`PDF Version <pandas.pdf>`__
-
-`Zipped HTML <pandas.zip>`__
-
-.. module:: pandas
-
**Date**: |today| **Version**: |version|
-**Binary Installers:** https://pypi.org/project/pandas
-
-**Source Repository:** https://github.com/pandas-dev/pandas
-
-**Issues & Ideas:** https://github.com/pandas-dev/pandas/issues
-
-**Q&A Support:** https://stackoverflow.com/questions/tagged/pandas
+**Download documentation**: `PDF Version <pandas.pdf>`__ | `Zipped HTML <pandas.zip>`__
-**Developer Mailing List:** https://groups.google.com/forum/#!forum/pydata
+**Useful links**:
+`Binary Installers <https://pypi.org/project/pandas>`__ |
+`Source Repository <https://github.com/pandas-dev/pandas>`__ |
+`Issues & Ideas <https://github.com/pandas-dev/pandas/issues>`__ |
+`Q&A Support <https://stackoverflow.com/questions/tagged/pandas>`__ |
+`Mailing List <https://groups.google.com/forum/#!forum/pydata>`__
:mod:`pandas` is an open source, BSD-licensed library providing high-performance,
easy-to-use data structures and data analysis tools for the `Python <https://www.python.org/>`__
From 14b68eabb4b7750c04ccd3ed17247504aceae35a Mon Sep 17 00:00:00 2001
From: Tom Augspurger <TomAugspurger@users.noreply.github.com>
Date: Fri, 25 Jan 2019 08:23:07 -0600
Subject: [PATCH 26/48] DOC: 0.24 release date (#24930)
---
.gitignore | 2 +-
doc/source/whatsnew/v0.24.0.rst | 2 +-
2 files changed, 2 insertions(+), 2 deletions(-)
diff --git a/.gitignore b/.gitignore
index 9891883879cf1..816aff376fc83 100644
--- a/.gitignore
+++ b/.gitignore
@@ -101,6 +101,7 @@ asv_bench/pandas/
# Documentation generated files #
#################################
doc/source/generated
+doc/source/user_guide/styled.xlsx
doc/source/reference/api
doc/source/_static
doc/source/vbench
@@ -109,6 +110,5 @@ doc/source/index.rst
doc/build/html/index.html
# Windows specific leftover:
doc/tmp.sv
-doc/source/styled.xlsx
env/
doc/source/savefig/
diff --git a/doc/source/whatsnew/v0.24.0.rst b/doc/source/whatsnew/v0.24.0.rst
index f0f99d2def136..489d505cb8f67 100644
--- a/doc/source/whatsnew/v0.24.0.rst
+++ b/doc/source/whatsnew/v0.24.0.rst
@@ -1,6 +1,6 @@
.. _whatsnew_0240:
-What's New in 0.24.0 (January XX, 2019)
+What's New in 0.24.0 (January 25, 2019)
---------------------------------------
.. warning::
From 8a8a0830f5a021f7c8d272fabdfa699b4502edd3 Mon Sep 17 00:00:00 2001
From: Marc Garcia <garcia.marc@gmail.com>
Date: Fri, 25 Jan 2019 14:54:36 +0000
Subject: [PATCH 27/48] DOC: Adding version to the whatsnew section in the home
page (#24929)
---
doc/source/index.rst.template | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/doc/source/index.rst.template b/doc/source/index.rst.template
index 55b95868c01dd..51487c0d325b5 100644
--- a/doc/source/index.rst.template
+++ b/doc/source/index.rst.template
@@ -39,7 +39,7 @@ See the :ref:`overview` for more detail about what's in the library.
{% endif %}
{% if not single_doc -%}
- What's New <whatsnew/v0.24.0>
+ What's New in 0.24.0 <whatsnew/v0.24.0>
install
getting_started/index
user_guide/index
From c8aae3540e4d22d2581e66843740fba10e9ea0b1 Mon Sep 17 00:00:00 2001
From: Tom Augspurger <TomAugspurger@users.noreply.github.com>
Date: Fri, 25 Jan 2019 08:55:49 -0600
Subject: [PATCH 28/48] API: Remove IntervalArray from top-level (#24926)
---
doc/source/reference/arrays.rst | 4 ++--
doc/source/whatsnew/v0.24.0.rst | 4 ++--
pandas/core/api.py | 1 -
pandas/core/arrays/array_.py | 2 +-
pandas/core/arrays/interval.py | 29 +++++++++++++++--------------
pandas/core/indexes/interval.py | 23 ++++++++++++-----------
pandas/tests/api/test_api.py | 1 -
pandas/tests/arrays/test_array.py | 4 ++--
8 files changed, 34 insertions(+), 34 deletions(-)
diff --git a/doc/source/reference/arrays.rst b/doc/source/reference/arrays.rst
index 7281f4f748d6f..1dc74ad83b7e6 100644
--- a/doc/source/reference/arrays.rst
+++ b/doc/source/reference/arrays.rst
@@ -288,12 +288,12 @@ Properties
Interval.overlaps
Interval.right
-A collection of intervals may be stored in an :class:`IntervalArray`.
+A collection of intervals may be stored in an :class:`arrays.IntervalArray`.
.. autosummary::
:toctree: api/
- IntervalArray
+ arrays.IntervalArray
IntervalDtype
.. _api.arrays.integer_na:
diff --git a/doc/source/whatsnew/v0.24.0.rst b/doc/source/whatsnew/v0.24.0.rst
index 489d505cb8f67..fc963fce37a5b 100644
--- a/doc/source/whatsnew/v0.24.0.rst
+++ b/doc/source/whatsnew/v0.24.0.rst
@@ -225,7 +225,7 @@ from the ``Series``:
ser.array
pser.array
-These return an instance of :class:`IntervalArray` or :class:`arrays.PeriodArray`,
+These return an instance of :class:`arrays.IntervalArray` or :class:`arrays.PeriodArray`,
the new extension arrays that back interval and period data.
.. warning::
@@ -411,7 +411,7 @@ Other Enhancements
- :meth:`Categorical.from_codes` now can take a ``dtype`` parameter as an alternative to passing ``categories`` and ``ordered`` (:issue:`24398`).
- New attribute ``__git_version__`` will return git commit sha of current build (:issue:`21295`).
- Compatibility with Matplotlib 3.0 (:issue:`22790`).
-- Added :meth:`Interval.overlaps`, :meth:`IntervalArray.overlaps`, and :meth:`IntervalIndex.overlaps` for determining overlaps between interval-like objects (:issue:`21998`)
+- Added :meth:`Interval.overlaps`, :meth:`arrays.IntervalArray.overlaps`, and :meth:`IntervalIndex.overlaps` for determining overlaps between interval-like objects (:issue:`21998`)
- :func:`read_fwf` now accepts keyword ``infer_nrows`` (:issue:`15138`).
- :func:`~DataFrame.to_parquet` now supports writing a ``DataFrame`` as a directory of parquet files partitioned by a subset of the columns when ``engine = 'pyarrow'`` (:issue:`23283`)
- :meth:`Timestamp.tz_localize`, :meth:`DatetimeIndex.tz_localize`, and :meth:`Series.tz_localize` have gained the ``nonexistent`` argument for alternative handling of nonexistent times. See :ref:`timeseries.timezone_nonexistent` (:issue:`8917`, :issue:`24466`)
diff --git a/pandas/core/api.py b/pandas/core/api.py
index afc929c39086c..8c92287e212a6 100644
--- a/pandas/core/api.py
+++ b/pandas/core/api.py
@@ -4,7 +4,6 @@
import numpy as np
-from pandas.core.arrays import IntervalArray
from pandas.core.arrays.integer import (
Int8Dtype,
Int16Dtype,
diff --git a/pandas/core/arrays/array_.py b/pandas/core/arrays/array_.py
index c7be8e3f745c4..41d623c7efd9c 100644
--- a/pandas/core/arrays/array_.py
+++ b/pandas/core/arrays/array_.py
@@ -50,7 +50,7 @@ def array(data, # type: Sequence[object]
============================== =====================================
Scalar Type Array Type
============================== =====================================
- :class:`pandas.Interval` :class:`pandas.IntervalArray`
+ :class:`pandas.Interval` :class:`pandas.arrays.IntervalArray`
:class:`pandas.Period` :class:`pandas.arrays.PeriodArray`
:class:`datetime.datetime` :class:`pandas.arrays.DatetimeArray`
:class:`datetime.timedelta` :class:`pandas.arrays.TimedeltaArray`
diff --git a/pandas/core/arrays/interval.py b/pandas/core/arrays/interval.py
index 45470e03c041a..1e671c7bd956a 100644
--- a/pandas/core/arrays/interval.py
+++ b/pandas/core/arrays/interval.py
@@ -32,6 +32,7 @@
_shared_docs_kwargs = dict(
klass='IntervalArray',
+ qualname='arrays.IntervalArray',
name=''
)
@@ -115,7 +116,7 @@
A new ``IntervalArray`` can be constructed directly from an array-like of
``Interval`` objects:
- >>> pd.IntervalArray([pd.Interval(0, 1), pd.Interval(1, 5)])
+ >>> pd.arrays.IntervalArray([pd.Interval(0, 1), pd.Interval(1, 5)])
IntervalArray([(0, 1], (1, 5]],
closed='right',
dtype='interval[int64]')
@@ -248,8 +249,8 @@ def _from_factorized(cls, values, original):
Examples
--------
- >>> pd.%(klass)s.from_breaks([0, 1, 2, 3])
- %(klass)s([(0, 1], (1, 2], (2, 3]]
+ >>> pd.%(qualname)s.from_breaks([0, 1, 2, 3])
+ %(klass)s([(0, 1], (1, 2], (2, 3]],
closed='right',
dtype='interval[int64]')
"""
@@ -311,7 +312,7 @@ def from_breaks(cls, breaks, closed='right', copy=False, dtype=None):
Examples
--------
>>> %(klass)s.from_arrays([0, 1, 2], [1, 2, 3])
- %(klass)s([(0, 1], (1, 2], (2, 3]]
+ %(klass)s([(0, 1], (1, 2], (2, 3]],
closed='right',
dtype='interval[int64]')
"""
@@ -354,16 +355,16 @@ def from_arrays(cls, left, right, closed='right', copy=False, dtype=None):
Examples
--------
- >>> pd.%(klass)s.from_intervals([pd.Interval(0, 1),
+ >>> pd.%(qualname)s.from_intervals([pd.Interval(0, 1),
... pd.Interval(1, 2)])
- %(klass)s([(0, 1], (1, 2]]
+ %(klass)s([(0, 1], (1, 2]],
closed='right', dtype='interval[int64]')
The generic Index constructor work identically when it infers an array
of all intervals:
>>> pd.Index([pd.Interval(0, 1), pd.Interval(1, 2)])
- %(klass)s([(0, 1], (1, 2]]
+ %(klass)s([(0, 1], (1, 2]],
closed='right', dtype='interval[int64]')
"""
@@ -394,7 +395,7 @@ def from_arrays(cls, left, right, closed='right', copy=False, dtype=None):
Examples
--------
- >>> pd.%(klass)s.from_tuples([(0, 1), (1, 2)])
+ >>> pd.%(qualname)s.from_tuples([(0, 1), (1, 2)])
%(klass)s([(0, 1], (1, 2]],
closed='right', dtype='interval[int64]')
"""
@@ -891,13 +892,13 @@ def closed(self):
Examples
--------
- >>> index = pd.interval_range(0, 3)
- >>> index
- %(klass)s([(0, 1], (1, 2], (2, 3]]
+ >>> index = pd.interval_range(0, 3)
+ >>> index
+ IntervalIndex([(0, 1], (1, 2], (2, 3]],
closed='right',
dtype='interval[int64]')
- >>> index.set_closed('both')
- %(klass)s([[0, 1], [1, 2], [2, 3]]
+ >>> index.set_closed('both')
+ IntervalIndex([[0, 1], [1, 2], [2, 3]],
closed='both',
dtype='interval[int64]')
"""
@@ -1039,7 +1040,7 @@ def repeat(self, repeats, axis=None):
Examples
--------
- >>> intervals = pd.%(klass)s.from_tuples([(0, 1), (1, 3), (2, 4)])
+ >>> intervals = pd.%(qualname)s.from_tuples([(0, 1), (1, 3), (2, 4)])
>>> intervals
%(klass)s([(0, 1], (1, 3], (2, 4]],
closed='right',
diff --git a/pandas/core/indexes/interval.py b/pandas/core/indexes/interval.py
index 2a6044fb0a08b..0210560aaa21f 100644
--- a/pandas/core/indexes/interval.py
+++ b/pandas/core/indexes/interval.py
@@ -38,6 +38,7 @@
_index_doc_kwargs.update(
dict(klass='IntervalIndex',
+ qualname="IntervalIndex",
target_klass='IntervalIndex or list of Intervals',
name=textwrap.dedent("""\
name : object, optional
@@ -282,10 +283,10 @@ def contains(self, key):
examples="""
Examples
--------
- >>> idx = pd.IntervalIndex.from_arrays([0, np.nan, 2], [1, np.nan, 3])
- >>> idx.to_tuples()
+ >>> idx = pd.IntervalIndex.from_arrays([0, np.nan, 2], [1, np.nan, 3])
+ >>> idx.to_tuples()
Index([(0.0, 1.0), (nan, nan), (2.0, 3.0)], dtype='object')
- >>> idx.to_tuples(na_tuple=False)
+ >>> idx.to_tuples(na_tuple=False)
Index([(0.0, 1.0), nan, (2.0, 3.0)], dtype='object')""",
))
def to_tuples(self, na_tuple=True):
@@ -1201,15 +1202,15 @@ def interval_range(start=None, end=None, periods=None, freq=None,
Numeric ``start`` and ``end`` is supported.
>>> pd.interval_range(start=0, end=5)
- IntervalIndex([(0, 1], (1, 2], (2, 3], (3, 4], (4, 5]]
+ IntervalIndex([(0, 1], (1, 2], (2, 3], (3, 4], (4, 5]],
closed='right', dtype='interval[int64]')
Additionally, datetime-like input is also supported.
>>> pd.interval_range(start=pd.Timestamp('2017-01-01'),
- end=pd.Timestamp('2017-01-04'))
+ ... end=pd.Timestamp('2017-01-04'))
IntervalIndex([(2017-01-01, 2017-01-02], (2017-01-02, 2017-01-03],
- (2017-01-03, 2017-01-04]]
+ (2017-01-03, 2017-01-04]],
closed='right', dtype='interval[datetime64[ns]]')
The ``freq`` parameter specifies the frequency between the left and right.
@@ -1217,23 +1218,23 @@ def interval_range(start=None, end=None, periods=None, freq=None,
numeric ``start`` and ``end``, the frequency must also be numeric.
>>> pd.interval_range(start=0, periods=4, freq=1.5)
- IntervalIndex([(0.0, 1.5], (1.5, 3.0], (3.0, 4.5], (4.5, 6.0]]
+ IntervalIndex([(0.0, 1.5], (1.5, 3.0], (3.0, 4.5], (4.5, 6.0]],
closed='right', dtype='interval[float64]')
Similarly, for datetime-like ``start`` and ``end``, the frequency must be
convertible to a DateOffset.
>>> pd.interval_range(start=pd.Timestamp('2017-01-01'),
- periods=3, freq='MS')
+ ... periods=3, freq='MS')
IntervalIndex([(2017-01-01, 2017-02-01], (2017-02-01, 2017-03-01],
- (2017-03-01, 2017-04-01]]
+ (2017-03-01, 2017-04-01]],
closed='right', dtype='interval[datetime64[ns]]')
Specify ``start``, ``end``, and ``periods``; the frequency is generated
automatically (linearly spaced).
>>> pd.interval_range(start=0, end=6, periods=4)
- IntervalIndex([(0.0, 1.5], (1.5, 3.0], (3.0, 4.5], (4.5, 6.0]]
+ IntervalIndex([(0.0, 1.5], (1.5, 3.0], (3.0, 4.5], (4.5, 6.0]],
closed='right',
dtype='interval[float64]')
@@ -1241,7 +1242,7 @@ def interval_range(start=None, end=None, periods=None, freq=None,
intervals within the ``IntervalIndex`` are closed.
>>> pd.interval_range(end=5, periods=4, closed='both')
- IntervalIndex([[1, 2], [2, 3], [3, 4], [4, 5]]
+ IntervalIndex([[1, 2], [2, 3], [3, 4], [4, 5]],
closed='both', dtype='interval[int64]')
"""
start = com.maybe_box_datetimelike(start)
diff --git a/pandas/tests/api/test_api.py b/pandas/tests/api/test_api.py
index 07cf358c765b3..599ab9a3c5f7c 100644
--- a/pandas/tests/api/test_api.py
+++ b/pandas/tests/api/test_api.py
@@ -46,7 +46,6 @@ class TestPDApi(Base):
'Series', 'SparseArray', 'SparseDataFrame', 'SparseDtype',
'SparseSeries', 'Timedelta',
'TimedeltaIndex', 'Timestamp', 'Interval', 'IntervalIndex',
- 'IntervalArray',
'CategoricalDtype', 'PeriodDtype', 'IntervalDtype',
'DatetimeTZDtype',
'Int8Dtype', 'Int16Dtype', 'Int32Dtype', 'Int64Dtype',
diff --git a/pandas/tests/arrays/test_array.py b/pandas/tests/arrays/test_array.py
index 4a51fd63d963b..9fea1989e46df 100644
--- a/pandas/tests/arrays/test_array.py
+++ b/pandas/tests/arrays/test_array.py
@@ -74,7 +74,7 @@
# Interval
([pd.Interval(1, 2), pd.Interval(3, 4)], 'interval',
- pd.IntervalArray.from_tuples([(1, 2), (3, 4)])),
+ pd.arrays.IntervalArray.from_tuples([(1, 2), (3, 4)])),
# Sparse
([0, 1], 'Sparse[int64]', pd.SparseArray([0, 1], dtype='int64')),
@@ -129,7 +129,7 @@ def test_array_copy():
# interval
([pd.Interval(0, 1), pd.Interval(1, 2)],
- pd.IntervalArray.from_breaks([0, 1, 2])),
+ pd.arrays.IntervalArray.from_breaks([0, 1, 2])),
# datetime
([pd.Timestamp('2000',), pd.Timestamp('2001')],
From 83eb2428ceb6257042173582f3f436c2c887aa69 Mon Sep 17 00:00:00 2001
From: Tom Augspurger <tom.w.augspurger@gmail.com>
Date: Fri, 25 Jan 2019 09:32:26 -0600
Subject: [PATCH 29/48] RLS: 0.24.0
From 0c4113fa0906273007cc12a4bcadff85d943dc84 Mon Sep 17 00:00:00 2001
From: Tom Augspurger <tom.w.augspurger@gmail.com>
Date: Fri, 25 Jan 2019 15:30:08 -0600
Subject: [PATCH 30/48] DEV: Start 0.25 cycle
From d2fa4b42812093d147cd864ca366d6cccac2db30 Mon Sep 17 00:00:00 2001
From: gfyoung <gfyoung17+GitHub@gmail.com>
Date: Sat, 26 Jan 2019 00:01:00 -0800
Subject: [PATCH 31/48] DOC: State that we support scalars in to_numeric
(#24944)
We support it and test it already.
xref gh-24910.
---
pandas/core/tools/numeric.py | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/pandas/core/tools/numeric.py b/pandas/core/tools/numeric.py
index 803723dab46ff..79d8ee38637f9 100644
--- a/pandas/core/tools/numeric.py
+++ b/pandas/core/tools/numeric.py
@@ -21,7 +21,7 @@ def to_numeric(arg, errors='raise', downcast=None):
Parameters
----------
- arg : list, tuple, 1-d array, or Series
+ arg : scalar, list, tuple, 1-d array, or Series
errors : {'ignore', 'raise', 'coerce'}, default 'raise'
- If 'raise', then invalid parsing will raise an exception
- If 'coerce', then invalid parsing will be set as NaN
From 2626215ca5dd168ea311f117b988693cef437885 Mon Sep 17 00:00:00 2001
From: Roman Yurchak <rth.yurchak@pm.me>
Date: Sat, 26 Jan 2019 09:01:55 +0100
Subject: [PATCH 32/48] DOC: Minor what's new fix (#24933)
---
doc/source/whatsnew/v0.24.0.rst | 5 +++--
1 file changed, 3 insertions(+), 2 deletions(-)
diff --git a/doc/source/whatsnew/v0.24.0.rst b/doc/source/whatsnew/v0.24.0.rst
index fc963fce37a5b..16319a3b83ca4 100644
--- a/doc/source/whatsnew/v0.24.0.rst
+++ b/doc/source/whatsnew/v0.24.0.rst
@@ -6,7 +6,8 @@ What's New in 0.24.0 (January 25, 2019)
.. warning::
The 0.24.x series of releases will be the last to support Python 2. Future feature
- releases will support Python 3 only. See :ref:`install.dropping-27` for more.
+ releases will support Python 3 only. See :ref:`install.dropping-27` for more
+ details.
{{ header }}
@@ -244,7 +245,7 @@ the new extension arrays that back interval and period data.
Joining with two multi-indexes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-:func:`DataFrame.merge` and :func:`DataFrame.join` can now be used to join multi-indexed ``Dataframe`` instances on the overlaping index levels (:issue:`6360`)
+:func:`DataFrame.merge` and :func:`DataFrame.join` can now be used to join multi-indexed ``Dataframe`` instances on the overlapping index levels (:issue:`6360`)
See the :ref:`Merge, join, and concatenate
<merging.Join_with_two_multi_indexes>` documentation section.
From c1cad5dedde5872b0b677e42c43e69aa336e034b Mon Sep 17 00:00:00 2001
From: Mike Cramblett <35242616+mike-cramblett@users.noreply.github.com>
Date: Sat, 26 Jan 2019 06:49:30 -0800
Subject: [PATCH 33/48] TST: GH#23922 Add missing match params to pytest.raises
(#24937)
---
pandas/tests/arithmetic/test_datetime64.py | 230 +++++++++++----------
1 file changed, 124 insertions(+), 106 deletions(-)
diff --git a/pandas/tests/arithmetic/test_datetime64.py b/pandas/tests/arithmetic/test_datetime64.py
index f97a1651163e8..405dc0805a285 100644
--- a/pandas/tests/arithmetic/test_datetime64.py
+++ b/pandas/tests/arithmetic/test_datetime64.py
@@ -124,14 +124,14 @@ def test_comparison_invalid(self, box_with_array):
result = x != y
expected = tm.box_expected([True] * 5, xbox)
tm.assert_equal(result, expected)
-
- with pytest.raises(TypeError):
+ msg = 'Invalid comparison between'
+ with pytest.raises(TypeError, match=msg):
x >= y
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
x > y
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
x < y
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
x <= y
@pytest.mark.parametrize('data', [
@@ -327,9 +327,10 @@ def test_comparison_tzawareness_compat(self, op):
# raise
naive_series = Series(dr)
aware_series = Series(dz)
- with pytest.raises(TypeError):
+ msg = 'Cannot compare tz-naive and tz-aware'
+ with pytest.raises(TypeError, match=msg):
op(dz, naive_series)
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
op(dr, aware_series)
# TODO: implement _assert_tzawareness_compat for the reverse
@@ -428,14 +429,14 @@ def test_dti_cmp_null_scalar_inequality(self, tz_naive_fixture, other,
dti = pd.date_range('2016-01-01', periods=2, tz=tz)
# FIXME: ValueError with transpose
dtarr = tm.box_expected(dti, box_with_array, transpose=False)
-
- with pytest.raises(TypeError):
+ msg = 'Invalid comparison between'
+ with pytest.raises(TypeError, match=msg):
dtarr < other
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
dtarr <= other
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
dtarr > other
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
dtarr >= other
@pytest.mark.parametrize('dtype', [None, object])
@@ -584,22 +585,23 @@ def test_comparison_tzawareness_compat(self, op, box_with_array):
dr = tm.box_expected(dr, box_with_array, transpose=False)
dz = tm.box_expected(dz, box_with_array, transpose=False)
- with pytest.raises(TypeError):
+ msg = 'Cannot compare tz-naive and tz-aware'
+ with pytest.raises(TypeError, match=msg):
op(dr, dz)
if box_with_array is not pd.DataFrame:
# DataFrame op is invalid until transpose bug is fixed
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
op(dr, list(dz))
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
op(dr, np.array(list(dz), dtype=object))
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
op(dz, dr)
if box_with_array is not pd.DataFrame:
# DataFrame op is invalid until transpose bug is fixed
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
op(dz, list(dr))
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
op(dz, np.array(list(dr), dtype=object))
# Check that there isn't a problem aware-aware and naive-naive do not
@@ -617,15 +619,15 @@ def test_comparison_tzawareness_compat(self, op, box_with_array):
ts_tz = pd.Timestamp('2000-03-14 01:59', tz='Europe/Amsterdam')
assert_all(dr > ts)
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
op(dr, ts_tz)
assert_all(dz > ts_tz)
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
op(dz, ts)
# GH#12601: Check comparison against Timestamps and DatetimeIndex
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
op(ts, dz)
@pytest.mark.parametrize('op', [operator.eq, operator.ne,
@@ -641,10 +643,10 @@ def test_scalar_comparison_tzawareness(self, op, other, tz_aware_fixture,
# FIXME: ValueError with transpose
dtarr = tm.box_expected(dti, box_with_array, transpose=False)
-
- with pytest.raises(TypeError):
+ msg = 'Cannot compare tz-naive and tz-aware'
+ with pytest.raises(TypeError, match=msg):
op(dtarr, other)
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
op(other, dtarr)
@pytest.mark.parametrize('op', [operator.eq, operator.ne,
@@ -714,14 +716,14 @@ def test_dt64arr_cmp_scalar_invalid(self, other, tz_naive_fixture,
expected = np.array([True] * 10)
expected = tm.box_expected(expected, xbox, transpose=False)
tm.assert_equal(result, expected)
-
- with pytest.raises(TypeError):
+ msg = 'Invalid comparison between'
+ with pytest.raises(TypeError, match=msg):
rng < other
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
rng <= other
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
rng > other
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
rng >= other
def test_dti_cmp_list(self):
@@ -749,14 +751,14 @@ def test_dti_cmp_tdi_tzawareness(self, other):
result = dti != other
expected = np.array([True] * 10)
tm.assert_numpy_array_equal(result, expected)
-
- with pytest.raises(TypeError):
+ msg = 'Invalid comparison between'
+ with pytest.raises(TypeError, match=msg):
dti < other
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
dti <= other
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
dti > other
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
dti >= other
def test_dti_cmp_object_dtype(self):
@@ -770,7 +772,8 @@ def test_dti_cmp_object_dtype(self):
tm.assert_numpy_array_equal(result, expected)
other = dti.tz_localize(None)
- with pytest.raises(TypeError):
+ msg = 'Cannot compare tz-naive and tz-aware'
+ with pytest.raises(TypeError, match=msg):
# tzawareness failure
dti != other
@@ -778,8 +781,8 @@ def test_dti_cmp_object_dtype(self):
result = dti == other
expected = np.array([True] * 5 + [False] * 5)
tm.assert_numpy_array_equal(result, expected)
-
- with pytest.raises(TypeError):
+ msg = "Cannot compare type"
+ with pytest.raises(TypeError, match=msg):
dti >= other
@@ -898,7 +901,8 @@ def test_dt64arr_add_sub_td64_nat(self, box_with_array, tz_naive_fixture):
tm.assert_equal(result, expected)
result = obj - other
tm.assert_equal(result, expected)
- with pytest.raises(TypeError):
+ msg = 'cannot subtract'
+ with pytest.raises(TypeError, match=msg):
other - obj
def test_dt64arr_add_sub_td64ndarray(self, tz_naive_fixture,
@@ -927,8 +931,8 @@ def test_dt64arr_add_sub_td64ndarray(self, tz_naive_fixture,
result = dtarr - tdarr
tm.assert_equal(result, expected)
-
- with pytest.raises(TypeError):
+ msg = 'cannot subtract'
+ with pytest.raises(TypeError, match=msg):
tdarr - dtarr
# -----------------------------------------------------------------
@@ -1028,10 +1032,10 @@ def test_dt64arr_aware_sub_dt64ndarray_raises(self, tz_aware_fixture,
dt64vals = dti.values
dtarr = tm.box_expected(dti, box_with_array)
-
- with pytest.raises(TypeError):
+ msg = 'DatetimeArray subtraction must have the same timezones or'
+ with pytest.raises(TypeError, match=msg):
dtarr - dt64vals
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
dt64vals - dtarr
# -------------------------------------------------------------
@@ -1048,17 +1052,17 @@ def test_dt64arr_add_dt64ndarray_raises(self, tz_naive_fixture,
dt64vals = dti.values
dtarr = tm.box_expected(dti, box_with_array)
-
- with pytest.raises(TypeError):
+ msg = 'cannot add'
+ with pytest.raises(TypeError, match=msg):
dtarr + dt64vals
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
dt64vals + dtarr
def test_dt64arr_add_timestamp_raises(self, box_with_array):
# GH#22163 ensure DataFrame doesn't cast Timestamp to i8
idx = DatetimeIndex(['2011-01-01', '2011-01-02'])
idx = tm.box_expected(idx, box_with_array)
- msg = "cannot add"
+ msg = 'cannot add'
with pytest.raises(TypeError, match=msg):
idx + Timestamp('2011-01-01')
with pytest.raises(TypeError, match=msg):
@@ -1071,13 +1075,14 @@ def test_dt64arr_add_timestamp_raises(self, box_with_array):
def test_dt64arr_add_sub_float(self, other, box_with_array):
dti = DatetimeIndex(['2011-01-01', '2011-01-02'], freq='D')
dtarr = tm.box_expected(dti, box_with_array)
- with pytest.raises(TypeError):
+ msg = '|'.join(['unsupported operand type', 'cannot (add|subtract)'])
+ with pytest.raises(TypeError, match=msg):
dtarr + other
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
other + dtarr
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
dtarr - other
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
other - dtarr
@pytest.mark.parametrize('pi_freq', ['D', 'W', 'Q', 'H'])
@@ -1090,14 +1095,15 @@ def test_dt64arr_add_sub_parr(self, dti_freq, pi_freq,
dtarr = tm.box_expected(dti, box_with_array)
parr = tm.box_expected(pi, box_with_array2)
-
- with pytest.raises(TypeError):
+ msg = '|'.join(['cannot (add|subtract)', 'unsupported operand',
+ 'descriptor.*requires', 'ufunc.*cannot use operands'])
+ with pytest.raises(TypeError, match=msg):
dtarr + parr
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
parr + dtarr
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
dtarr - parr
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
parr - dtarr
@pytest.mark.parametrize('dti_freq', [None, 'D'])
@@ -1108,14 +1114,14 @@ def test_dt64arr_add_sub_period_scalar(self, dti_freq, box_with_array):
idx = pd.DatetimeIndex(['2011-01-01', '2011-01-02'], freq=dti_freq)
dtarr = tm.box_expected(idx, box_with_array)
-
- with pytest.raises(TypeError):
+ msg = '|'.join(['unsupported operand type', 'cannot (add|subtract)'])
+ with pytest.raises(TypeError, match=msg):
dtarr + per
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
per + dtarr
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
dtarr - per
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
per - dtarr
@@ -1156,8 +1162,8 @@ def test_dt64arr_series_sub_tick_DateOffset(self, box_with_array):
result2 = -pd.offsets.Second(5) + ser
tm.assert_equal(result2, expected)
-
- with pytest.raises(TypeError):
+ msg = "bad operand type for unary"
+ with pytest.raises(TypeError, match=msg):
pd.offsets.Second(5) - ser
@pytest.mark.parametrize('cls_name', ['Day', 'Hour', 'Minute', 'Second',
@@ -1239,8 +1245,8 @@ def test_dt64arr_add_sub_relativedelta_offsets(self, box_with_array):
expected = DatetimeIndex([x - off for x in vec_items])
expected = tm.box_expected(expected, box_with_array)
tm.assert_equal(expected, vec - off)
-
- with pytest.raises(TypeError):
+ msg = "bad operand type for unary"
+ with pytest.raises(TypeError, match=msg):
off - vec
# -------------------------------------------------------------
@@ -1320,8 +1326,8 @@ def test_dt64arr_add_sub_DateOffsets(self, box_with_array,
expected = DatetimeIndex([offset + x for x in vec_items])
expected = tm.box_expected(expected, box_with_array)
tm.assert_equal(expected, offset + vec)
-
- with pytest.raises(TypeError):
+ msg = "bad operand type for unary"
+ with pytest.raises(TypeError, match=msg):
offset - vec
def test_dt64arr_add_sub_DateOffset(self, box_with_array):
@@ -1440,13 +1446,14 @@ def test_dt64_series_arith_overflow(self):
td = pd.Timedelta('20000 Days')
dti = pd.date_range('1949-09-30', freq='100Y', periods=4)
ser = pd.Series(dti)
- with pytest.raises(OverflowError):
+ msg = 'Overflow in int64 addition'
+ with pytest.raises(OverflowError, match=msg):
ser - dt
- with pytest.raises(OverflowError):
+ with pytest.raises(OverflowError, match=msg):
dt - ser
- with pytest.raises(OverflowError):
+ with pytest.raises(OverflowError, match=msg):
ser + td
- with pytest.raises(OverflowError):
+ with pytest.raises(OverflowError, match=msg):
td + ser
ser.iloc[-1] = pd.NaT
@@ -1480,9 +1487,9 @@ def test_datetimeindex_sub_timestamp_overflow(self):
tspos.to_pydatetime(),
tspos.to_datetime64().astype('datetime64[ns]'),
tspos.to_datetime64().astype('datetime64[D]')]
-
+ msg = 'Overflow in int64 addition'
for variant in ts_neg_variants:
- with pytest.raises(OverflowError):
+ with pytest.raises(OverflowError, match=msg):
dtimax - variant
expected = pd.Timestamp.max.value - tspos.value
@@ -1496,7 +1503,7 @@ def test_datetimeindex_sub_timestamp_overflow(self):
assert res[1].value == expected
for variant in ts_pos_variants:
- with pytest.raises(OverflowError):
+ with pytest.raises(OverflowError, match=msg):
dtimin - variant
def test_datetimeindex_sub_datetimeindex_overflow(self):
@@ -1515,22 +1522,22 @@ def test_datetimeindex_sub_datetimeindex_overflow(self):
expected = pd.Timestamp.min.value - ts_neg[1].value
result = dtimin - ts_neg
assert result[1].value == expected
-
- with pytest.raises(OverflowError):
+ msg = 'Overflow in int64 addition'
+ with pytest.raises(OverflowError, match=msg):
dtimax - ts_neg
- with pytest.raises(OverflowError):
+ with pytest.raises(OverflowError, match=msg):
dtimin - ts_pos
# Edge cases
tmin = pd.to_datetime([pd.Timestamp.min])
t1 = tmin + pd.Timedelta.max + pd.Timedelta('1us')
- with pytest.raises(OverflowError):
+ with pytest.raises(OverflowError, match=msg):
t1 - tmin
tmax = pd.to_datetime([pd.Timestamp.max])
t2 = tmax + pd.Timedelta.min - pd.Timedelta('1us')
- with pytest.raises(OverflowError):
+ with pytest.raises(OverflowError, match=msg):
tmax - t2
@@ -1543,7 +1550,8 @@ def test_empty_series_add_sub(self):
tm.assert_series_equal(a, a + b)
tm.assert_series_equal(a, a - b)
tm.assert_series_equal(a, b + a)
- with pytest.raises(TypeError):
+ msg = 'cannot subtract'
+ with pytest.raises(TypeError, match=msg):
b - a
def test_operators_datetimelike(self):
@@ -1688,12 +1696,13 @@ def test_datetime64_ops_nat(self):
# subtraction
tm.assert_series_equal(-NaT + datetime_series,
nat_series_dtype_timestamp)
- with pytest.raises(TypeError):
+ msg = 'Unary negative expects'
+ with pytest.raises(TypeError, match=msg):
-single_nat_dtype_datetime + datetime_series
tm.assert_series_equal(-NaT + nat_series_dtype_timestamp,
nat_series_dtype_timestamp)
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
-single_nat_dtype_datetime + nat_series_dtype_timestamp
# addition
@@ -1718,15 +1727,16 @@ def test_datetime64_ops_nat(self):
@pytest.mark.parametrize('one', [1, 1.0, np.array(1)])
def test_dt64_mul_div_numeric_invalid(self, one, dt64_series):
# multiplication
- with pytest.raises(TypeError):
+ msg = 'cannot perform .* with this index type'
+ with pytest.raises(TypeError, match=msg):
dt64_series * one
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
one * dt64_series
# division
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
dt64_series / one
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
one / dt64_series
@pytest.mark.parametrize('op', ['__add__', '__radd__',
@@ -1740,13 +1750,17 @@ def test_dt64_series_add_intlike(self, tz, op):
other = Series([20, 30, 40], dtype='uint8')
method = getattr(ser, op)
- with pytest.raises(TypeError):
+ msg = '|'.join(['incompatible type for a .* operation',
+ 'cannot evaluate a numeric op',
+ 'ufunc .* cannot use operands',
+ 'cannot (add|subtract)'])
+ with pytest.raises(TypeError, match=msg):
method(1)
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
method(other)
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
method(other.values)
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
method(pd.Index(other))
# -------------------------------------------------------------
@@ -1783,13 +1797,14 @@ def test_operators_datetimelike_with_timezones(self):
result = dt1 - td1[0]
exp = (dt1.dt.tz_localize(None) - td1[0]).dt.tz_localize(tz)
tm.assert_series_equal(result, exp)
- with pytest.raises(TypeError):
+ msg = "bad operand type for unary"
+ with pytest.raises(TypeError, match=msg):
td1[0] - dt1
result = dt2 - td2[0]
exp = (dt2.dt.tz_localize(None) - td2[0]).dt.tz_localize(tz)
tm.assert_series_equal(result, exp)
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
td2[0] - dt2
result = dt1 + td1
@@ -1807,10 +1822,10 @@ def test_operators_datetimelike_with_timezones(self):
result = dt2 - td2
exp = (dt2.dt.tz_localize(None) - td2).dt.tz_localize(tz)
tm.assert_series_equal(result, exp)
-
- with pytest.raises(TypeError):
+ msg = 'cannot (add|subtract)'
+ with pytest.raises(TypeError, match=msg):
td1 - dt1
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
td2 - dt2
@@ -1909,13 +1924,15 @@ def test_dti_add_intarray_no_freq(self, int_holder):
# GH#19959
dti = pd.DatetimeIndex(['2016-01-01', 'NaT', '2017-04-05 06:07:08'])
other = int_holder([9, 4, -1])
- with pytest.raises(NullFrequencyError):
+ nfmsg = 'Cannot shift with no freq'
+ tmsg = 'cannot subtract DatetimeArray from'
+ with pytest.raises(NullFrequencyError, match=nfmsg):
dti + other
- with pytest.raises(NullFrequencyError):
+ with pytest.raises(NullFrequencyError, match=nfmsg):
other + dti
- with pytest.raises(NullFrequencyError):
+ with pytest.raises(NullFrequencyError, match=nfmsg):
dti - other
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=tmsg):
other - dti
# -------------------------------------------------------------
@@ -2057,14 +2074,14 @@ def test_sub_dti_dti(self):
result = dti_tz - dti_tz
tm.assert_index_equal(result, expected)
-
- with pytest.raises(TypeError):
+ msg = 'DatetimeArray subtraction must have the same timezones or'
+ with pytest.raises(TypeError, match=msg):
dti_tz - dti
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
dti - dti_tz
- with pytest.raises(TypeError):
+ with pytest.raises(TypeError, match=msg):
dti_tz - dti_tz2
# isub
@@ -2074,7 +2091,8 @@ def test_sub_dti_dti(self):
# different length raises ValueError
dti1 = date_range('20130101', periods=3)
dti2 = date_range('20130101', periods=4)
- with pytest.raises(ValueError):
+ msg = 'cannot add indices of unequal length'
+ with pytest.raises(ValueError, match=msg):
dti1 - dti2
# NaN propagation
@@ -2148,8 +2166,8 @@ def test_ops_nat_mixed_datetime64_timedelta64(self):
tm.assert_series_equal(-single_nat_dtype_timedelta +
nat_series_dtype_timestamp,
nat_series_dtype_timestamp)
-
- with pytest.raises(TypeError):
+ msg = 'cannot subtract a datelike'
+ with pytest.raises(TypeError, match=msg):
timedelta_series - single_nat_dtype_datetime
# addition
From dd7afa0561001db0b458ba314505a1e95706a9bf Mon Sep 17 00:00:00 2001
From: Alexander Ponomaroff
<33966871+alexander-ponomaroff@users.noreply.github.com>
Date: Sat, 26 Jan 2019 09:50:49 -0500
Subject: [PATCH 34/48] Add tests for NaT when performing dt.to_period (#24921)
---
pandas/tests/series/test_period.py | 9 +++++++++
1 file changed, 9 insertions(+)
diff --git a/pandas/tests/series/test_period.py b/pandas/tests/series/test_period.py
index 0a86bb0b67797..7e0feb418e8df 100644
--- a/pandas/tests/series/test_period.py
+++ b/pandas/tests/series/test_period.py
@@ -164,3 +164,12 @@ def test_end_time_timevalues(self, input_vals):
result = s.dt.end_time
expected = s.apply(lambda x: x.end_time)
tm.assert_series_equal(result, expected)
+
+ @pytest.mark.parametrize('input_vals', [
+ ('2001'), ('NaT')
+ ])
+ def test_to_period(self, input_vals):
+ # GH 21205
+ expected = Series([input_vals], dtype='Period[D]')
+ result = Series([input_vals], dtype='datetime64[ns]').dt.to_period('D')
+ tm.assert_series_equal(result, expected)
From b641963e0dcf42d6051f0467ac6d52b974801898 Mon Sep 17 00:00:00 2001
From: h-vetinari <33685575+h-vetinari@users.noreply.github.com>
Date: Sat, 26 Jan 2019 15:53:58 +0100
Subject: [PATCH 35/48] DOC: switch headline whatsnew to 0.25 (#24941)
---
doc/source/index.rst.template | 2 +-
doc/source/whatsnew/v0.25.0.rst | 7 +++++--
2 files changed, 6 insertions(+), 3 deletions(-)
diff --git a/doc/source/index.rst.template b/doc/source/index.rst.template
index 51487c0d325b5..d04e9194e71dc 100644
--- a/doc/source/index.rst.template
+++ b/doc/source/index.rst.template
@@ -39,7 +39,7 @@ See the :ref:`overview` for more detail about what's in the library.
{% endif %}
{% if not single_doc -%}
- What's New in 0.24.0 <whatsnew/v0.24.0>
+ What's New in 0.25.0 <whatsnew/v0.25.0>
install
getting_started/index
user_guide/index
diff --git a/doc/source/whatsnew/v0.25.0.rst b/doc/source/whatsnew/v0.25.0.rst
index fac42dbd9c7c8..5129449e4fdf3 100644
--- a/doc/source/whatsnew/v0.25.0.rst
+++ b/doc/source/whatsnew/v0.25.0.rst
@@ -1,10 +1,13 @@
-:orphan:
-
.. _whatsnew_0250:
What's New in 0.25.0 (April XX, 2019)
-------------------------------------
+.. warning::
+
+ Starting with the 0.25.x series of releases, pandas only supports Python 3.5 and higher.
+ See :ref:`install.dropping-27` for more details.
+
{{ header }}
These are the changes in pandas 0.25.0. See :ref:`release` for a full changelog
From 41166c650f733079e8012161aeca189ecfa62919 Mon Sep 17 00:00:00 2001
From: Justin Zheng <justinzhengbc@gmail.com>
Date: Sat, 26 Jan 2019 06:58:07 -0800
Subject: [PATCH 36/48] BUG-24212 fix regression in #24897 (#24916)
---
doc/source/whatsnew/v0.24.1.rst | 3 ++
pandas/core/reshape/merge.py | 45 ++++++++++++++++++++++--
pandas/tests/reshape/merge/test_merge.py | 31 ++++++++--------
3 files changed, 60 insertions(+), 19 deletions(-)
diff --git a/doc/source/whatsnew/v0.24.1.rst b/doc/source/whatsnew/v0.24.1.rst
index ee4b7ab62b31a..3ac2ed73ea53f 100644
--- a/doc/source/whatsnew/v0.24.1.rst
+++ b/doc/source/whatsnew/v0.24.1.rst
@@ -63,6 +63,9 @@ Bug Fixes
-
-
+**Reshaping**
+
+- Bug in :func:`merge` when merging by index name would sometimes result in an incorrectly numbered index (:issue:`24212`)
**Other**
diff --git a/pandas/core/reshape/merge.py b/pandas/core/reshape/merge.py
index e11847d2b8ce2..1dd19a7c1514e 100644
--- a/pandas/core/reshape/merge.py
+++ b/pandas/core/reshape/merge.py
@@ -757,13 +757,21 @@ def _get_join_info(self):
if self.right_index:
if len(self.left) > 0:
- join_index = self.left.index.take(left_indexer)
+ join_index = self._create_join_index(self.left.index,
+ self.right.index,
+ left_indexer,
+ right_indexer,
+ how='right')
else:
join_index = self.right.index.take(right_indexer)
left_indexer = np.array([-1] * len(join_index))
elif self.left_index:
if len(self.right) > 0:
- join_index = self.right.index.take(right_indexer)
+ join_index = self._create_join_index(self.right.index,
+ self.left.index,
+ right_indexer,
+ left_indexer,
+ how='left')
else:
join_index = self.left.index.take(left_indexer)
right_indexer = np.array([-1] * len(join_index))
@@ -774,6 +782,39 @@ def _get_join_info(self):
join_index = join_index.astype(object)
return join_index, left_indexer, right_indexer
+ def _create_join_index(self, index, other_index, indexer,
+ other_indexer, how='left'):
+ """
+ Create a join index by rearranging one index to match another
+
+ Parameters
+ ----------
+ index: Index being rearranged
+ other_index: Index used to supply values not found in index
+ indexer: how to rearrange index
+ how: replacement is only necessary if indexer based on other_index
+
+ Returns
+ -------
+ join_index
+ """
+ join_index = index.take(indexer)
+ if (self.how in (how, 'outer') and
+ not isinstance(other_index, MultiIndex)):
+ # if final index requires values in other_index but not target
+ # index, indexer may hold missing (-1) values, causing Index.take
+ # to take the final value in target index
+ mask = indexer == -1
+ if np.any(mask):
+ # if values missing (-1) from target index,
+ # take from other_index instead
+ join_list = join_index.to_numpy()
+ other_list = other_index.take(other_indexer).to_numpy()
+ join_list[mask] = other_list[mask]
+ join_index = Index(join_list, dtype=join_index.dtype,
+ name=join_index.name)
+ return join_index
+
def _get_merge_keys(self):
"""
Note: has side effects (copy/delete key columns)
diff --git a/pandas/tests/reshape/merge/test_merge.py b/pandas/tests/reshape/merge/test_merge.py
index f0a3ddc8ce8a4..c17c301968269 100644
--- a/pandas/tests/reshape/merge/test_merge.py
+++ b/pandas/tests/reshape/merge/test_merge.py
@@ -939,25 +939,22 @@ def test_merge_two_empty_df_no_division_error(self):
with np.errstate(divide='raise'):
merge(a, a, on=('a', 'b'))
- @pytest.mark.parametrize('how', ['left', 'outer'])
- @pytest.mark.xfail(reason="GH-24897")
+ @pytest.mark.parametrize('how', ['right', 'outer'])
def test_merge_on_index_with_more_values(self, how):
# GH 24212
- # pd.merge gets [-1, -1, 0, 1] as right_indexer, ensure that -1 is
- # interpreted as a missing value instead of the last element
- df1 = pd.DataFrame([[1, 2], [2, 4], [3, 6], [4, 8]],
- columns=['a', 'b'])
- df2 = pd.DataFrame([[3, 30], [4, 40]],
- columns=['a', 'c'])
- df1.set_index('a', drop=False, inplace=True)
- df2.set_index('a', inplace=True)
- result = pd.merge(df1, df2, left_index=True, right_on='a', how=how)
- expected = pd.DataFrame([[1, 2, np.nan],
- [2, 4, np.nan],
- [3, 6, 30.0],
- [4, 8, 40.0]],
- columns=['a', 'b', 'c'])
- expected.set_index('a', drop=False, inplace=True)
+ # pd.merge gets [0, 1, 2, -1, -1, -1] as left_indexer, ensure that
+ # -1 is interpreted as a missing value instead of the last element
+ df1 = pd.DataFrame({'a': [1, 2, 3], 'key': [0, 2, 2]})
+ df2 = pd.DataFrame({'b': [1, 2, 3, 4, 5]})
+ result = df1.merge(df2, left_on='key', right_index=True, how=how)
+ expected = pd.DataFrame([[1.0, 0, 1],
+ [2.0, 2, 3],
+ [3.0, 2, 3],
+ [np.nan, 1, 2],
+ [np.nan, 3, 4],
+ [np.nan, 4, 5]],
+ columns=['a', 'key', 'b'])
+ expected.set_index(Int64Index([0, 1, 2, 1, 3, 4]), inplace=True)
assert_frame_equal(result, expected)
def test_merge_right_index_right(self):
From 69a2c54ef4c3df06104a0528b2d59a5b7521b23f Mon Sep 17 00:00:00 2001
From: Christopher Whelan <topherwhelan@gmail.com>
Date: Sat, 26 Jan 2019 07:08:50 -0800
Subject: [PATCH 37/48] CLN: reduce overhead in setup for categoricals
benchmarks in asv (#24913)
---
asv_bench/benchmarks/categoricals.py | 19 +++++++++++++------
1 file changed, 13 insertions(+), 6 deletions(-)
diff --git a/asv_bench/benchmarks/categoricals.py b/asv_bench/benchmarks/categoricals.py
index e5dab0cb066aa..4b5b2848f7e0f 100644
--- a/asv_bench/benchmarks/categoricals.py
+++ b/asv_bench/benchmarks/categoricals.py
@@ -223,12 +223,19 @@ class CategoricalSlicing(object):
def setup(self, index):
N = 10**6
- values = list('a' * N + 'b' * N + 'c' * N)
- indices = {
- 'monotonic_incr': pd.Categorical(values),
- 'monotonic_decr': pd.Categorical(reversed(values)),
- 'non_monotonic': pd.Categorical(list('abc' * N))}
- self.data = indices[index]
+ categories = ['a', 'b', 'c']
+ values = [0] * N + [1] * N + [2] * N
+ if index == 'monotonic_incr':
+ self.data = pd.Categorical.from_codes(values,
+ categories=categories)
+ elif index == 'monotonic_decr':
+ self.data = pd.Categorical.from_codes(list(reversed(values)),
+ categories=categories)
+ elif index == 'non_monotonic':
+ self.data = pd.Categorical.from_codes([0, 1, 2] * N,
+ categories=categories)
+ else:
+ raise ValueError('Invalid index param: {}'.format(index))
self.scalar = 10000
self.list = list(range(10000))
From 95415406d191eb5b0886ae107a7d01f0ef39b019 Mon Sep 17 00:00:00 2001
From: William Ayd <william.ayd@icloud.com>
Date: Sat, 26 Jan 2019 07:34:46 -0800
Subject: [PATCH 38/48] Excel Reader Refactor - Base Class Introduction
(#24829)
---
pandas/io/excel.py | 235 +++++++++++++++++++++++++--------------------
1 file changed, 133 insertions(+), 102 deletions(-)
diff --git a/pandas/io/excel.py b/pandas/io/excel.py
index 3a7c39ec65309..3d85ae7fd1f46 100644
--- a/pandas/io/excel.py
+++ b/pandas/io/excel.py
@@ -375,60 +375,25 @@ def read_excel(io,
**kwds)
-class _XlrdReader(object):
-
- def __init__(self, filepath_or_buffer):
- """Reader using xlrd engine.
-
- Parameters
- ----------
- filepath_or_buffer : string, path object or Workbook
- Object to be parsed.
- """
- err_msg = "Install xlrd >= 1.0.0 for Excel support"
-
- try:
- import xlrd
- except ImportError:
- raise ImportError(err_msg)
- else:
- if xlrd.__VERSION__ < LooseVersion("1.0.0"):
- raise ImportError(err_msg +
- ". Current version " + xlrd.__VERSION__)
+@add_metaclass(abc.ABCMeta)
+class _BaseExcelReader(object):
- # If filepath_or_buffer is a url, want to keep the data as bytes so
- # can't pass to get_filepath_or_buffer()
- if _is_url(filepath_or_buffer):
- filepath_or_buffer = _urlopen(filepath_or_buffer)
- elif not isinstance(filepath_or_buffer, (ExcelFile, xlrd.Book)):
- filepath_or_buffer, _, _, _ = get_filepath_or_buffer(
- filepath_or_buffer)
+ @property
+ @abc.abstractmethod
+ def sheet_names(self):
+ pass
- if isinstance(filepath_or_buffer, xlrd.Book):
- self.book = filepath_or_buffer
- elif not isinstance(filepath_or_buffer, xlrd.Book) and hasattr(
- filepath_or_buffer, "read"):
- # N.B. xlrd.Book has a read attribute too
- if hasattr(filepath_or_buffer, 'seek'):
- try:
- # GH 19779
- filepath_or_buffer.seek(0)
- except UnsupportedOperation:
- # HTTPResponse does not support seek()
- # GH 20434
- pass
+ @abc.abstractmethod
+ def get_sheet_by_name(self, name):
+ pass
- data = filepath_or_buffer.read()
- self.book = xlrd.open_workbook(file_contents=data)
- elif isinstance(filepath_or_buffer, compat.string_types):
- self.book = xlrd.open_workbook(filepath_or_buffer)
- else:
- raise ValueError('Must explicitly set engine if not passing in'
- ' buffer or path for io.')
+ @abc.abstractmethod
+ def get_sheet_by_index(self, index):
+ pass
- @property
- def sheet_names(self):
- return self.book.sheet_names()
+ @abc.abstractmethod
+ def get_sheet_data(self, sheet, convert_float):
+ pass
def parse(self,
sheet_name=0,
@@ -455,48 +420,6 @@ def parse(self,
_validate_header_arg(header)
- from xlrd import (xldate, XL_CELL_DATE,
- XL_CELL_ERROR, XL_CELL_BOOLEAN,
- XL_CELL_NUMBER)
-
- epoch1904 = self.book.datemode
-
- def _parse_cell(cell_contents, cell_typ):
- """converts the contents of the cell into a pandas
- appropriate object"""
-
- if cell_typ == XL_CELL_DATE:
-
- # Use the newer xlrd datetime handling.
- try:
- cell_contents = xldate.xldate_as_datetime(
- cell_contents, epoch1904)
- except OverflowError:
- return cell_contents
-
- # Excel doesn't distinguish between dates and time,
- # so we treat dates on the epoch as times only.
- # Also, Excel supports 1900 and 1904 epochs.
- year = (cell_contents.timetuple())[0:3]
- if ((not epoch1904 and year == (1899, 12, 31)) or
- (epoch1904 and year == (1904, 1, 1))):
- cell_contents = time(cell_contents.hour,
- cell_contents.minute,
- cell_contents.second,
- cell_contents.microsecond)
-
- elif cell_typ == XL_CELL_ERROR:
- cell_contents = np.nan
- elif cell_typ == XL_CELL_BOOLEAN:
- cell_contents = bool(cell_contents)
- elif convert_float and cell_typ == XL_CELL_NUMBER:
- # GH5394 - Excel 'numbers' are always floats
- # it's a minimal perf hit and less surprising
- val = int(cell_contents)
- if val == cell_contents:
- cell_contents = val
- return cell_contents
-
ret_dict = False
# Keep sheetname to maintain backwards compatibility.
@@ -504,7 +427,7 @@ def _parse_cell(cell_contents, cell_typ):
sheets = sheet_name
ret_dict = True
elif sheet_name is None:
- sheets = self.book.sheet_names()
+ sheets = self.sheet_names
ret_dict = True
else:
sheets = [sheet_name]
@@ -519,19 +442,13 @@ def _parse_cell(cell_contents, cell_typ):
print("Reading sheet {sheet}".format(sheet=asheetname))
if isinstance(asheetname, compat.string_types):
- sheet = self.book.sheet_by_name(asheetname)
+ sheet = self.get_sheet_by_name(asheetname)
else: # assume an integer if not a string
- sheet = self.book.sheet_by_index(asheetname)
+ sheet = self.get_sheet_by_index(asheetname)
- data = []
+ data = self.get_sheet_data(sheet, convert_float)
usecols = _maybe_convert_usecols(usecols)
- for i in range(sheet.nrows):
- row = [_parse_cell(value, typ)
- for value, typ in zip(sheet.row_values(i),
- sheet.row_types(i))]
- data.append(row)
-
if sheet.nrows == 0:
output[asheetname] = DataFrame()
continue
@@ -620,6 +537,120 @@ def _parse_cell(cell_contents, cell_typ):
return output[asheetname]
+class _XlrdReader(_BaseExcelReader):
+
+ def __init__(self, filepath_or_buffer):
+ """Reader using xlrd engine.
+
+ Parameters
+ ----------
+ filepath_or_buffer : string, path object or Workbook
+ Object to be parsed.
+ """
+ err_msg = "Install xlrd >= 1.0.0 for Excel support"
+
+ try:
+ import xlrd
+ except ImportError:
+ raise ImportError(err_msg)
+ else:
+ if xlrd.__VERSION__ < LooseVersion("1.0.0"):
+ raise ImportError(err_msg +
+ ". Current version " + xlrd.__VERSION__)
+
+ # If filepath_or_buffer is a url, want to keep the data as bytes so
+ # can't pass to get_filepath_or_buffer()
+ if _is_url(filepath_or_buffer):
+ filepath_or_buffer = _urlopen(filepath_or_buffer)
+ elif not isinstance(filepath_or_buffer, (ExcelFile, xlrd.Book)):
+ filepath_or_buffer, _, _, _ = get_filepath_or_buffer(
+ filepath_or_buffer)
+
+ if isinstance(filepath_or_buffer, xlrd.Book):
+ self.book = filepath_or_buffer
+ elif hasattr(filepath_or_buffer, "read"):
+ # N.B. xlrd.Book has a read attribute too
+ if hasattr(filepath_or_buffer, 'seek'):
+ try:
+ # GH 19779
+ filepath_or_buffer.seek(0)
+ except UnsupportedOperation:
+ # HTTPResponse does not support seek()
+ # GH 20434
+ pass
+
+ data = filepath_or_buffer.read()
+ self.book = xlrd.open_workbook(file_contents=data)
+ elif isinstance(filepath_or_buffer, compat.string_types):
+ self.book = xlrd.open_workbook(filepath_or_buffer)
+ else:
+ raise ValueError('Must explicitly set engine if not passing in'
+ ' buffer or path for io.')
+
+ @property
+ def sheet_names(self):
+ return self.book.sheet_names()
+
+ def get_sheet_by_name(self, name):
+ return self.book.sheet_by_name(name)
+
+ def get_sheet_by_index(self, index):
+ return self.book.sheet_by_index(index)
+
+ def get_sheet_data(self, sheet, convert_float):
+ from xlrd import (xldate, XL_CELL_DATE,
+ XL_CELL_ERROR, XL_CELL_BOOLEAN,
+ XL_CELL_NUMBER)
+
+ epoch1904 = self.book.datemode
+
+ def _parse_cell(cell_contents, cell_typ):
+ """converts the contents of the cell into a pandas
+ appropriate object"""
+
+ if cell_typ == XL_CELL_DATE:
+
+ # Use the newer xlrd datetime handling.
+ try:
+ cell_contents = xldate.xldate_as_datetime(
+ cell_contents, epoch1904)
+ except OverflowError:
+ return cell_contents
+
+ # Excel doesn't distinguish between dates and time,
+ # so we treat dates on the epoch as times only.
+ # Also, Excel supports 1900 and 1904 epochs.
+ year = (cell_contents.timetuple())[0:3]
+ if ((not epoch1904 and year == (1899, 12, 31)) or
+ (epoch1904 and year == (1904, 1, 1))):
+ cell_contents = time(cell_contents.hour,
+ cell_contents.minute,
+ cell_contents.second,
+ cell_contents.microsecond)
+
+ elif cell_typ == XL_CELL_ERROR:
+ cell_contents = np.nan
+ elif cell_typ == XL_CELL_BOOLEAN:
+ cell_contents = bool(cell_contents)
+ elif convert_float and cell_typ == XL_CELL_NUMBER:
+ # GH5394 - Excel 'numbers' are always floats
+ # it's a minimal perf hit and less surprising
+ val = int(cell_contents)
+ if val == cell_contents:
+ cell_contents = val
+ return cell_contents
+
+ data = []
+
+ for i in range(sheet.nrows):
+ row = [_parse_cell(value, typ)
+ for value, typ in zip(sheet.row_values(i),
+ sheet.row_types(i))]
+ data.append(row)
+
+ return data
+
+
class ExcelFile(object):
"""
Class for parsing tabular excel sheets into DataFrame objects.
From 37a224d216e8d49a05681e2c87482bd8e67385fc Mon Sep 17 00:00:00 2001
From: gfyoung <gfyoung17+GitHub@gmail.com>
Date: Sat, 26 Jan 2019 07:42:22 -0800
Subject: [PATCH 39/48] TST/REF: Add pytest idiom to test_numeric.py (#24946)
---
pandas/tests/tools/test_numeric.py | 875 +++++++++++++++--------------
1 file changed, 450 insertions(+), 425 deletions(-)
diff --git a/pandas/tests/tools/test_numeric.py b/pandas/tests/tools/test_numeric.py
index 537881f3a5e85..3822170d884aa 100644
--- a/pandas/tests/tools/test_numeric.py
+++ b/pandas/tests/tools/test_numeric.py
@@ -5,436 +5,461 @@
import pytest
import pandas as pd
-from pandas import to_numeric
+from pandas import DataFrame, Index, Series, to_numeric
from pandas.util import testing as tm
-class TestToNumeric(object):
-
- def test_empty(self):
- # see gh-16302
- s = pd.Series([], dtype=object)
-
- res = to_numeric(s)
- expected = pd.Series([], dtype=np.int64)
-
- tm.assert_series_equal(res, expected)
-
- # Original issue example
- res = to_numeric(s, errors='coerce', downcast='integer')
- expected = pd.Series([], dtype=np.int8)
-
- tm.assert_series_equal(res, expected)
-
- def test_series(self):
- s = pd.Series(['1', '-3.14', '7'])
- res = to_numeric(s)
- expected = pd.Series([1, -3.14, 7])
- tm.assert_series_equal(res, expected)
-
- s = pd.Series(['1', '-3.14', 7])
- res = to_numeric(s)
- tm.assert_series_equal(res, expected)
-
- def test_series_numeric(self):
- s = pd.Series([1, 3, 4, 5], index=list('ABCD'), name='XXX')
- res = to_numeric(s)
- tm.assert_series_equal(res, s)
-
- s = pd.Series([1., 3., 4., 5.], index=list('ABCD'), name='XXX')
- res = to_numeric(s)
- tm.assert_series_equal(res, s)
-
- # bool is regarded as numeric
- s = pd.Series([True, False, True, True],
- index=list('ABCD'), name='XXX')
- res = to_numeric(s)
- tm.assert_series_equal(res, s)
-
- def test_error(self):
- s = pd.Series([1, -3.14, 'apple'])
- msg = 'Unable to parse string "apple" at position 2'
- with pytest.raises(ValueError, match=msg):
- to_numeric(s, errors='raise')
-
- res = to_numeric(s, errors='ignore')
- expected = pd.Series([1, -3.14, 'apple'])
- tm.assert_series_equal(res, expected)
-
- res = to_numeric(s, errors='coerce')
- expected = pd.Series([1, -3.14, np.nan])
- tm.assert_series_equal(res, expected)
-
- s = pd.Series(['orange', 1, -3.14, 'apple'])
- msg = 'Unable to parse string "orange" at position 0'
- with pytest.raises(ValueError, match=msg):
- to_numeric(s, errors='raise')
-
- def test_error_seen_bool(self):
- s = pd.Series([True, False, 'apple'])
- msg = 'Unable to parse string "apple" at position 2'
- with pytest.raises(ValueError, match=msg):
- to_numeric(s, errors='raise')
-
- res = to_numeric(s, errors='ignore')
- expected = pd.Series([True, False, 'apple'])
- tm.assert_series_equal(res, expected)
-
- # coerces to float
- res = to_numeric(s, errors='coerce')
- expected = pd.Series([1., 0., np.nan])
- tm.assert_series_equal(res, expected)
-
- def test_list(self):
- s = ['1', '-3.14', '7']
- res = to_numeric(s)
- expected = np.array([1, -3.14, 7])
- tm.assert_numpy_array_equal(res, expected)
-
- def test_list_numeric(self):
- s = [1, 3, 4, 5]
- res = to_numeric(s)
- tm.assert_numpy_array_equal(res, np.array(s, dtype=np.int64))
-
- s = [1., 3., 4., 5.]
- res = to_numeric(s)
- tm.assert_numpy_array_equal(res, np.array(s))
-
- # bool is regarded as numeric
- s = [True, False, True, True]
- res = to_numeric(s)
- tm.assert_numpy_array_equal(res, np.array(s))
-
- def test_numeric(self):
- s = pd.Series([1, -3.14, 7], dtype='O')
- res = to_numeric(s)
- expected = pd.Series([1, -3.14, 7])
- tm.assert_series_equal(res, expected)
-
- s = pd.Series([1, -3.14, 7])
- res = to_numeric(s)
- tm.assert_series_equal(res, expected)
-
- # GH 14827
- df = pd.DataFrame(dict(
- a=[1.2, decimal.Decimal(3.14), decimal.Decimal("infinity"), '0.1'],
- b=[1.0, 2.0, 3.0, 4.0],
- ))
- expected = pd.DataFrame(dict(
- a=[1.2, 3.14, np.inf, 0.1],
- b=[1.0, 2.0, 3.0, 4.0],
- ))
-
- # Test to_numeric over one column
- df_copy = df.copy()
- df_copy['a'] = df_copy['a'].apply(to_numeric)
- tm.assert_frame_equal(df_copy, expected)
-
- # Test to_numeric over multiple columns
- df_copy = df.copy()
- df_copy[['a', 'b']] = df_copy[['a', 'b']].apply(to_numeric)
- tm.assert_frame_equal(df_copy, expected)
-
- def test_numeric_lists_and_arrays(self):
- # Test to_numeric with embedded lists and arrays
- df = pd.DataFrame(dict(
- a=[[decimal.Decimal(3.14), 1.0], decimal.Decimal(1.6), 0.1]
- ))
- df['a'] = df['a'].apply(to_numeric)
- expected = pd.DataFrame(dict(
- a=[[3.14, 1.0], 1.6, 0.1],
- ))
- tm.assert_frame_equal(df, expected)
-
- df = pd.DataFrame(dict(
- a=[np.array([decimal.Decimal(3.14), 1.0]), 0.1]
- ))
- df['a'] = df['a'].apply(to_numeric)
- expected = pd.DataFrame(dict(
- a=[[3.14, 1.0], 0.1],
- ))
- tm.assert_frame_equal(df, expected)
-
- def test_all_nan(self):
- s = pd.Series(['a', 'b', 'c'])
- res = to_numeric(s, errors='coerce')
- expected = pd.Series([np.nan, np.nan, np.nan])
- tm.assert_series_equal(res, expected)
-
- @pytest.mark.parametrize("errors", [None, "ignore", "raise", "coerce"])
- def test_type_check(self, errors):
- # see gh-11776
- df = pd.DataFrame({"a": [1, -3.14, 7], "b": ["4", "5", "6"]})
- kwargs = dict(errors=errors) if errors is not None else dict()
- error_ctx = pytest.raises(TypeError, match="1-d array")
-
- with error_ctx:
- to_numeric(df, **kwargs)
-
- def test_scalar(self):
- assert pd.to_numeric(1) == 1
- assert pd.to_numeric(1.1) == 1.1
-
- assert pd.to_numeric('1') == 1
- assert pd.to_numeric('1.1') == 1.1
-
- with pytest.raises(ValueError):
- to_numeric('XX', errors='raise')
-
- assert to_numeric('XX', errors='ignore') == 'XX'
- assert np.isnan(to_numeric('XX', errors='coerce'))
-
- def test_numeric_dtypes(self):
- idx = pd.Index([1, 2, 3], name='xxx')
- res = pd.to_numeric(idx)
- tm.assert_index_equal(res, idx)
-
- res = pd.to_numeric(pd.Series(idx, name='xxx'))
- tm.assert_series_equal(res, pd.Series(idx, name='xxx'))
-
- res = pd.to_numeric(idx.values)
- tm.assert_numpy_array_equal(res, idx.values)
-
- idx = pd.Index([1., np.nan, 3., np.nan], name='xxx')
- res = pd.to_numeric(idx)
- tm.assert_index_equal(res, idx)
-
- res = pd.to_numeric(pd.Series(idx, name='xxx'))
- tm.assert_series_equal(res, pd.Series(idx, name='xxx'))
-
- res = pd.to_numeric(idx.values)
- tm.assert_numpy_array_equal(res, idx.values)
-
- def test_str(self):
- idx = pd.Index(['1', '2', '3'], name='xxx')
- exp = np.array([1, 2, 3], dtype='int64')
- res = pd.to_numeric(idx)
- tm.assert_index_equal(res, pd.Index(exp, name='xxx'))
-
- res = pd.to_numeric(pd.Series(idx, name='xxx'))
- tm.assert_series_equal(res, pd.Series(exp, name='xxx'))
-
- res = pd.to_numeric(idx.values)
- tm.assert_numpy_array_equal(res, exp)
-
- idx = pd.Index(['1.5', '2.7', '3.4'], name='xxx')
- exp = np.array([1.5, 2.7, 3.4])
- res = pd.to_numeric(idx)
- tm.assert_index_equal(res, pd.Index(exp, name='xxx'))
-
- res = pd.to_numeric(pd.Series(idx, name='xxx'))
- tm.assert_series_equal(res, pd.Series(exp, name='xxx'))
-
- res = pd.to_numeric(idx.values)
- tm.assert_numpy_array_equal(res, exp)
-
- def test_datetime_like(self, tz_naive_fixture):
- idx = pd.date_range("20130101", periods=3,
- tz=tz_naive_fixture, name="xxx")
- res = pd.to_numeric(idx)
- tm.assert_index_equal(res, pd.Index(idx.asi8, name="xxx"))
-
- res = pd.to_numeric(pd.Series(idx, name="xxx"))
- tm.assert_series_equal(res, pd.Series(idx.asi8, name="xxx"))
-
- res = pd.to_numeric(idx.values)
- tm.assert_numpy_array_equal(res, idx.asi8)
-
- def test_timedelta(self):
- idx = pd.timedelta_range('1 days', periods=3, freq='D', name='xxx')
- res = pd.to_numeric(idx)
- tm.assert_index_equal(res, pd.Index(idx.asi8, name='xxx'))
-
- res = pd.to_numeric(pd.Series(idx, name='xxx'))
- tm.assert_series_equal(res, pd.Series(idx.asi8, name='xxx'))
-
- res = pd.to_numeric(idx.values)
- tm.assert_numpy_array_equal(res, idx.asi8)
-
- def test_period(self):
- idx = pd.period_range('2011-01', periods=3, freq='M', name='xxx')
- res = pd.to_numeric(idx)
- tm.assert_index_equal(res, pd.Index(idx.asi8, name='xxx'))
-
- # TODO: enable when we can support native PeriodDtype
- # res = pd.to_numeric(pd.Series(idx, name='xxx'))
- # tm.assert_series_equal(res, pd.Series(idx.asi8, name='xxx'))
-
- def test_non_hashable(self):
- # Test for Bug #13324
- s = pd.Series([[10.0, 2], 1.0, 'apple'])
- res = pd.to_numeric(s, errors='coerce')
- tm.assert_series_equal(res, pd.Series([np.nan, 1.0, np.nan]))
-
- res = pd.to_numeric(s, errors='ignore')
- tm.assert_series_equal(res, pd.Series([[10.0, 2], 1.0, 'apple']))
-
- with pytest.raises(TypeError, match="Invalid object type"):
- pd.to_numeric(s)
-
- @pytest.mark.parametrize("data", [
- ["1", 2, 3],
- [1, 2, 3],
- np.array(["1970-01-02", "1970-01-03",
- "1970-01-04"], dtype="datetime64[D]")
- ])
- def test_downcast_basic(self, data):
- # see gh-13352
- invalid_downcast = "unsigned-integer"
- msg = "invalid downcasting method provided"
-
- with pytest.raises(ValueError, match=msg):
- pd.to_numeric(data, downcast=invalid_downcast)
-
- expected = np.array([1, 2, 3], dtype=np.int64)
-
- # Basic function tests.
- res = pd.to_numeric(data)
- tm.assert_numpy_array_equal(res, expected)
-
- res = pd.to_numeric(data, downcast=None)
- tm.assert_numpy_array_equal(res, expected)
-
- # Basic dtype support.
- smallest_uint_dtype = np.dtype(np.typecodes["UnsignedInteger"][0])
-
- # Support below np.float32 is rare and far between.
- float_32_char = np.dtype(np.float32).char
- smallest_float_dtype = float_32_char
-
- expected = np.array([1, 2, 3], dtype=smallest_uint_dtype)
- res = pd.to_numeric(data, downcast="unsigned")
- tm.assert_numpy_array_equal(res, expected)
-
- expected = np.array([1, 2, 3], dtype=smallest_float_dtype)
- res = pd.to_numeric(data, downcast="float")
- tm.assert_numpy_array_equal(res, expected)
-
- @pytest.mark.parametrize("signed_downcast", ["integer", "signed"])
- @pytest.mark.parametrize("data", [
- ["1", 2, 3],
- [1, 2, 3],
- np.array(["1970-01-02", "1970-01-03",
- "1970-01-04"], dtype="datetime64[D]")
- ])
- def test_signed_downcast(self, data, signed_downcast):
- # see gh-13352
- smallest_int_dtype = np.dtype(np.typecodes["Integer"][0])
- expected = np.array([1, 2, 3], dtype=smallest_int_dtype)
-
- res = pd.to_numeric(data, downcast=signed_downcast)
- tm.assert_numpy_array_equal(res, expected)
-
- def test_ignore_downcast_invalid_data(self):
- # If we can't successfully cast the given
- # data to a numeric dtype, do not bother
- # with the downcast parameter.
- data = ["foo", 2, 3]
- expected = np.array(data, dtype=object)
-
- res = pd.to_numeric(data, errors="ignore",
- downcast="unsigned")
- tm.assert_numpy_array_equal(res, expected)
-
- def test_ignore_downcast_neg_to_unsigned(self):
- # Cannot cast to an unsigned integer
- # because we have a negative number.
- data = ["-1", 2, 3]
- expected = np.array([-1, 2, 3], dtype=np.int64)
-
- res = pd.to_numeric(data, downcast="unsigned")
- tm.assert_numpy_array_equal(res, expected)
-
- @pytest.mark.parametrize("downcast", ["integer", "signed", "unsigned"])
- @pytest.mark.parametrize("data,expected", [
- (["1.1", 2, 3],
- np.array([1.1, 2, 3], dtype=np.float64)),
- ([10000.0, 20000, 3000, 40000.36, 50000, 50000.00],
- np.array([10000.0, 20000, 3000,
- 40000.36, 50000, 50000.00], dtype=np.float64))
- ])
- def test_ignore_downcast_cannot_convert_float(
- self, data, expected, downcast):
- # Cannot cast to an integer (signed or unsigned)
- # because we have a float number.
- res = pd.to_numeric(data, downcast=downcast)
- tm.assert_numpy_array_equal(res, expected)
-
- @pytest.mark.parametrize("downcast,expected_dtype", [
- ("integer", np.int16),
- ("signed", np.int16),
- ("unsigned", np.uint16)
- ])
- def test_downcast_not8bit(self, downcast, expected_dtype):
- # the smallest integer dtype need not be np.(u)int8
- data = ["256", 257, 258]
-
- expected = np.array([256, 257, 258], dtype=expected_dtype)
- res = pd.to_numeric(data, downcast=downcast)
- tm.assert_numpy_array_equal(res, expected)
-
- @pytest.mark.parametrize("dtype,downcast,min_max", [
- ("int8", "integer", [iinfo(np.int8).min,
- iinfo(np.int8).max]),
- ("int16", "integer", [iinfo(np.int16).min,
- iinfo(np.int16).max]),
- ('int32', "integer", [iinfo(np.int32).min,
- iinfo(np.int32).max]),
- ('int64', "integer", [iinfo(np.int64).min,
- iinfo(np.int64).max]),
- ('uint8', "unsigned", [iinfo(np.uint8).min,
- iinfo(np.uint8).max]),
- ('uint16', "unsigned", [iinfo(np.uint16).min,
- iinfo(np.uint16).max]),
- ('uint32', "unsigned", [iinfo(np.uint32).min,
- iinfo(np.uint32).max]),
- ('uint64', "unsigned", [iinfo(np.uint64).min,
- iinfo(np.uint64).max]),
- ('int16', "integer", [iinfo(np.int8).min,
- iinfo(np.int8).max + 1]),
- ('int32', "integer", [iinfo(np.int16).min,
- iinfo(np.int16).max + 1]),
- ('int64', "integer", [iinfo(np.int32).min,
- iinfo(np.int32).max + 1]),
- ('int16', "integer", [iinfo(np.int8).min - 1,
- iinfo(np.int16).max]),
- ('int32', "integer", [iinfo(np.int16).min - 1,
- iinfo(np.int32).max]),
- ('int64', "integer", [iinfo(np.int32).min - 1,
- iinfo(np.int64).max]),
- ('uint16', "unsigned", [iinfo(np.uint8).min,
- iinfo(np.uint8).max + 1]),
- ('uint32', "unsigned", [iinfo(np.uint16).min,
- iinfo(np.uint16).max + 1]),
- ('uint64', "unsigned", [iinfo(np.uint32).min,
- iinfo(np.uint32).max + 1])
- ])
- def test_downcast_limits(self, dtype, downcast, min_max):
- # see gh-14404: test the limits of each downcast.
- series = pd.to_numeric(pd.Series(min_max), downcast=downcast)
- assert series.dtype == dtype
-
- def test_coerce_uint64_conflict(self):
- # see gh-17007 and gh-17125
- #
- # Still returns float despite the uint64-nan conflict,
- # which would normally force the casting to object.
- df = pd.DataFrame({"a": [200, 300, "", "NaN", 30000000000000000000]})
- expected = pd.Series([200, 300, np.nan, np.nan,
- 30000000000000000000], dtype=float, name="a")
- result = to_numeric(df["a"], errors="coerce")
+@pytest.mark.parametrize("input_kwargs,result_kwargs", [
+ (dict(), dict(dtype=np.int64)),
+ (dict(errors="coerce", downcast="integer"), dict(dtype=np.int8))
+])
+def test_empty(input_kwargs, result_kwargs):
+ # see gh-16302
+ ser = Series([], dtype=object)
+ result = to_numeric(ser, **input_kwargs)
+
+ expected = Series([], **result_kwargs)
+ tm.assert_series_equal(result, expected)
+
+
+@pytest.mark.parametrize("last_val", ["7", 7])
+def test_series(last_val):
+ ser = Series(["1", "-3.14", last_val])
+ result = to_numeric(ser)
+
+ expected = Series([1, -3.14, 7])
+ tm.assert_series_equal(result, expected)
+
+
+@pytest.mark.parametrize("data", [
+ [1, 3, 4, 5],
+ [1., 3., 4., 5.],
+
+ # Bool is regarded as numeric.
+ [True, False, True, True]
+])
+def test_series_numeric(data):
+ ser = Series(data, index=list("ABCD"), name="EFG")
+
+ result = to_numeric(ser)
+ tm.assert_series_equal(result, ser)
+
+
+@pytest.mark.parametrize("data,msg", [
+ ([1, -3.14, "apple"],
+ 'Unable to parse string "apple" at position 2'),
+ (["orange", 1, -3.14, "apple"],
+ 'Unable to parse string "orange" at position 0')
+])
+def test_error(data, msg):
+ ser = Series(data)
+
+ with pytest.raises(ValueError, match=msg):
+ to_numeric(ser, errors="raise")
+
+
+@pytest.mark.parametrize("errors,exp_data", [
+ ("ignore", [1, -3.14, "apple"]),
+ ("coerce", [1, -3.14, np.nan])
+])
+def test_ignore_error(errors, exp_data):
+ ser = Series([1, -3.14, "apple"])
+ result = to_numeric(ser, errors=errors)
+
+ expected = Series(exp_data)
+ tm.assert_series_equal(result, expected)
+
+
+@pytest.mark.parametrize("errors,exp", [
+ ("raise", 'Unable to parse string "apple" at position 2'),
+ ("ignore", [True, False, "apple"]),
+
+ # Coerces to float.
+ ("coerce", [1., 0., np.nan])
+])
+def test_bool_handling(errors, exp):
+ ser = Series([True, False, "apple"])
+
+ if isinstance(exp, str):
+ with pytest.raises(ValueError, match=exp):
+ to_numeric(ser, errors=errors)
+ else:
+ result = to_numeric(ser, errors=errors)
+ expected = Series(exp)
+
tm.assert_series_equal(result, expected)
- s = pd.Series(["12345678901234567890", "1234567890", "ITEM"])
- expected = pd.Series([12345678901234567890,
- 1234567890, np.nan], dtype=float)
- result = to_numeric(s, errors="coerce")
+
+def test_list():
+ ser = ["1", "-3.14", "7"]
+ res = to_numeric(ser)
+
+ expected = np.array([1, -3.14, 7])
+ tm.assert_numpy_array_equal(res, expected)
+
+
+@pytest.mark.parametrize("data,arr_kwargs", [
+ ([1, 3, 4, 5], dict(dtype=np.int64)),
+ ([1., 3., 4., 5.], dict()),
+
+ # Boolean is regarded as numeric.
+ ([True, False, True, True], dict())
+])
+def test_list_numeric(data, arr_kwargs):
+ result = to_numeric(data)
+ expected = np.array(data, **arr_kwargs)
+ tm.assert_numpy_array_equal(result, expected)
+
+
+@pytest.mark.parametrize("kwargs", [
+ dict(dtype="O"), dict()
+])
+def test_numeric(kwargs):
+ data = [1, -3.14, 7]
+
+ ser = Series(data, **kwargs)
+ result = to_numeric(ser)
+
+ expected = Series(data)
+ tm.assert_series_equal(result, expected)
+
+
+@pytest.mark.parametrize("columns", [
+ # One column.
+ "a",
+
+ # Multiple columns.
+ ["a", "b"]
+])
+def test_numeric_df_columns(columns):
+ # see gh-14827
+ df = DataFrame(dict(
+ a=[1.2, decimal.Decimal(3.14), decimal.Decimal("infinity"), "0.1"],
+ b=[1.0, 2.0, 3.0, 4.0],
+ ))
+
+ expected = DataFrame(dict(
+ a=[1.2, 3.14, np.inf, 0.1],
+ b=[1.0, 2.0, 3.0, 4.0],
+ ))
+
+ df_copy = df.copy()
+ df_copy[columns] = df_copy[columns].apply(to_numeric)
+
+ tm.assert_frame_equal(df_copy, expected)
+
+
+@pytest.mark.parametrize("data,exp_data", [
+ ([[decimal.Decimal(3.14), 1.0], decimal.Decimal(1.6), 0.1],
+ [[3.14, 1.0], 1.6, 0.1]),
+ ([np.array([decimal.Decimal(3.14), 1.0]), 0.1],
+ [[3.14, 1.0], 0.1])
+])
+def test_numeric_embedded_arr_likes(data, exp_data):
+ # Test to_numeric with embedded lists and arrays
+ df = DataFrame(dict(a=data))
+ df["a"] = df["a"].apply(to_numeric)
+
+ expected = DataFrame(dict(a=exp_data))
+ tm.assert_frame_equal(df, expected)
+
+
+def test_all_nan():
+ ser = Series(["a", "b", "c"])
+ result = to_numeric(ser, errors="coerce")
+
+ expected = Series([np.nan, np.nan, np.nan])
+ tm.assert_series_equal(result, expected)
+
+
+@pytest.mark.parametrize("errors", [None, "ignore", "raise", "coerce"])
+def test_type_check(errors):
+ # see gh-11776
+ df = DataFrame({"a": [1, -3.14, 7], "b": ["4", "5", "6"]})
+ kwargs = dict(errors=errors) if errors is not None else dict()
+ error_ctx = pytest.raises(TypeError, match="1-d array")
+
+ with error_ctx:
+ to_numeric(df, **kwargs)
+
+
+@pytest.mark.parametrize("val", [
+ 1, 1.1, "1", "1.1", -1.5, "-1.5"
+])
+def test_scalar(val):
+ assert to_numeric(val) == float(val)
+
+
+@pytest.mark.parametrize("errors,checker", [
+ ("raise", 'Unable to parse string "fail" at position 0'),
+ ("ignore", lambda x: x == "fail"),
+ ("coerce", lambda x: np.isnan(x))
+])
+def test_scalar_fail(errors, checker):
+ scalar = "fail"
+
+ if isinstance(checker, str):
+ with pytest.raises(ValueError, match=checker):
+ to_numeric(scalar, errors=errors)
+ else:
+ assert checker(to_numeric(scalar, errors=errors))
+
+
+@pytest.fixture(params=[
+ (lambda x: Index(x, name="idx"), tm.assert_index_equal),
+ (lambda x: Series(x, name="ser"), tm.assert_series_equal),
+ (lambda x: np.array(Index(x).values), tm.assert_numpy_array_equal)
+])
+def transform_assert_equal(request):
+ return request.param
+
+
+@pytest.mark.parametrize("data", [
+ [1, 2, 3],
+ [1., np.nan, 3, np.nan]
+])
+def test_numeric_dtypes(data, transform_assert_equal):
+ transform, assert_equal = transform_assert_equal
+ data = transform(data)
+
+ result = to_numeric(data)
+ assert_equal(result, data)
+
+
+@pytest.mark.parametrize("data,exp", [
+ (["1", "2", "3"], np.array([1, 2, 3], dtype="int64")),
+ (["1.5", "2.7", "3.4"], np.array([1.5, 2.7, 3.4]))
+])
+def test_str(data, exp, transform_assert_equal):
+ transform, assert_equal = transform_assert_equal
+ result = to_numeric(transform(data))
+
+ expected = transform(exp)
+ assert_equal(result, expected)
+
+
+def test_datetime_like(tz_naive_fixture, transform_assert_equal):
+ transform, assert_equal = transform_assert_equal
+ idx = pd.date_range("20130101", periods=3, tz=tz_naive_fixture)
+
+ result = to_numeric(transform(idx))
+ expected = transform(idx.asi8)
+ assert_equal(result, expected)
+
+
+def test_timedelta(transform_assert_equal):
+ transform, assert_equal = transform_assert_equal
+ idx = pd.timedelta_range("1 days", periods=3, freq="D")
+
+ result = to_numeric(transform(idx))
+ expected = transform(idx.asi8)
+ assert_equal(result, expected)
+
+
+def test_period(transform_assert_equal):
+ transform, assert_equal = transform_assert_equal
+
+ idx = pd.period_range("2011-01", periods=3, freq="M", name="")
+ inp = transform(idx)
+
+ if isinstance(inp, Index):
+ result = to_numeric(inp)
+ expected = transform(idx.asi8)
+ assert_equal(result, expected)
+ else:
+ # TODO: PeriodDtype, so support it in to_numeric.
+ pytest.skip("Missing PeriodDtype support in to_numeric")
+
+
+@pytest.mark.parametrize("errors,expected", [
+ ("raise", "Invalid object type at position 0"),
+ ("ignore", Series([[10.0, 2], 1.0, "apple"])),
+ ("coerce", Series([np.nan, 1.0, np.nan]))
+])
+def test_non_hashable(errors, expected):
+ # see gh-13324
+ ser = Series([[10.0, 2], 1.0, "apple"])
+
+ if isinstance(expected, str):
+ with pytest.raises(TypeError, match=expected):
+ to_numeric(ser, errors=errors)
+ else:
+ result = to_numeric(ser, errors=errors)
tm.assert_series_equal(result, expected)
- # For completeness, check against "ignore" and "raise"
- result = to_numeric(s, errors="ignore")
- tm.assert_series_equal(result, s)
- msg = "Unable to parse string"
- with pytest.raises(ValueError, match=msg):
- to_numeric(s, errors="raise")
+def test_downcast_invalid_cast():
+ # see gh-13352
+ data = ["1", 2, 3]
+ invalid_downcast = "unsigned-integer"
+ msg = "invalid downcasting method provided"
+
+ with pytest.raises(ValueError, match=msg):
+ to_numeric(data, downcast=invalid_downcast)
+
+
+@pytest.mark.parametrize("data", [
+ ["1", 2, 3],
+ [1, 2, 3],
+ np.array(["1970-01-02", "1970-01-03",
+ "1970-01-04"], dtype="datetime64[D]")
+])
+@pytest.mark.parametrize("kwargs,exp_dtype", [
+ # Basic function tests.
+ (dict(), np.int64),
+ (dict(downcast=None), np.int64),
+
+ # Support below np.float32 is rare and far between.
+ (dict(downcast="float"), np.dtype(np.float32).char),
+
+ # Basic dtype support.
+ (dict(downcast="unsigned"), np.dtype(np.typecodes["UnsignedInteger"][0]))
+])
+def test_downcast_basic(data, kwargs, exp_dtype):
+ # see gh-13352
+ result = to_numeric(data, **kwargs)
+ expected = np.array([1, 2, 3], dtype=exp_dtype)
+ tm.assert_numpy_array_equal(result, expected)
+
+
+@pytest.mark.parametrize("signed_downcast", ["integer", "signed"])
+@pytest.mark.parametrize("data", [
+ ["1", 2, 3],
+ [1, 2, 3],
+ np.array(["1970-01-02", "1970-01-03",
+ "1970-01-04"], dtype="datetime64[D]")
+])
+def test_signed_downcast(data, signed_downcast):
+ # see gh-13352
+ smallest_int_dtype = np.dtype(np.typecodes["Integer"][0])
+ expected = np.array([1, 2, 3], dtype=smallest_int_dtype)
+
+ res = to_numeric(data, downcast=signed_downcast)
+ tm.assert_numpy_array_equal(res, expected)
+
+
+def test_ignore_downcast_invalid_data():
+ # If we can't successfully cast the given
+ # data to a numeric dtype, do not bother
+ # with the downcast parameter.
+ data = ["foo", 2, 3]
+ expected = np.array(data, dtype=object)
+
+ res = to_numeric(data, errors="ignore",
+ downcast="unsigned")
+ tm.assert_numpy_array_equal(res, expected)
+
+
+def test_ignore_downcast_neg_to_unsigned():
+ # Cannot cast to an unsigned integer
+ # because we have a negative number.
+ data = ["-1", 2, 3]
+ expected = np.array([-1, 2, 3], dtype=np.int64)
+
+ res = to_numeric(data, downcast="unsigned")
+ tm.assert_numpy_array_equal(res, expected)
+
+
+@pytest.mark.parametrize("downcast", ["integer", "signed", "unsigned"])
+@pytest.mark.parametrize("data,expected", [
+ (["1.1", 2, 3],
+ np.array([1.1, 2, 3], dtype=np.float64)),
+ ([10000.0, 20000, 3000, 40000.36, 50000, 50000.00],
+ np.array([10000.0, 20000, 3000,
+ 40000.36, 50000, 50000.00], dtype=np.float64))
+])
+def test_ignore_downcast_cannot_convert_float(data, expected, downcast):
+ # Cannot cast to an integer (signed or unsigned)
+ # because we have a float number.
+ res = to_numeric(data, downcast=downcast)
+ tm.assert_numpy_array_equal(res, expected)
+
+
+@pytest.mark.parametrize("downcast,expected_dtype", [
+ ("integer", np.int16),
+ ("signed", np.int16),
+ ("unsigned", np.uint16)
+])
+def test_downcast_not8bit(downcast, expected_dtype):
+ # the smallest integer dtype need not be np.(u)int8
+ data = ["256", 257, 258]
+
+ expected = np.array([256, 257, 258], dtype=expected_dtype)
+ res = to_numeric(data, downcast=downcast)
+ tm.assert_numpy_array_equal(res, expected)
+
+
+@pytest.mark.parametrize("dtype,downcast,min_max", [
+ ("int8", "integer", [iinfo(np.int8).min,
+ iinfo(np.int8).max]),
+ ("int16", "integer", [iinfo(np.int16).min,
+ iinfo(np.int16).max]),
+ ("int32", "integer", [iinfo(np.int32).min,
+ iinfo(np.int32).max]),
+ ("int64", "integer", [iinfo(np.int64).min,
+ iinfo(np.int64).max]),
+ ("uint8", "unsigned", [iinfo(np.uint8).min,
+ iinfo(np.uint8).max]),
+ ("uint16", "unsigned", [iinfo(np.uint16).min,
+ iinfo(np.uint16).max]),
+ ("uint32", "unsigned", [iinfo(np.uint32).min,
+ iinfo(np.uint32).max]),
+ ("uint64", "unsigned", [iinfo(np.uint64).min,
+ iinfo(np.uint64).max]),
+ ("int16", "integer", [iinfo(np.int8).min,
+ iinfo(np.int8).max + 1]),
+ ("int32", "integer", [iinfo(np.int16).min,
+ iinfo(np.int16).max + 1]),
+ ("int64", "integer", [iinfo(np.int32).min,
+ iinfo(np.int32).max + 1]),
+ ("int16", "integer", [iinfo(np.int8).min - 1,
+ iinfo(np.int16).max]),
+ ("int32", "integer", [iinfo(np.int16).min - 1,
+ iinfo(np.int32).max]),
+ ("int64", "integer", [iinfo(np.int32).min - 1,
+ iinfo(np.int64).max]),
+ ("uint16", "unsigned", [iinfo(np.uint8).min,
+ iinfo(np.uint8).max + 1]),
+ ("uint32", "unsigned", [iinfo(np.uint16).min,
+ iinfo(np.uint16).max + 1]),
+ ("uint64", "unsigned", [iinfo(np.uint32).min,
+ iinfo(np.uint32).max + 1])
+])
+def test_downcast_limits(dtype, downcast, min_max):
+ # see gh-14404: test the limits of each downcast.
+ series = to_numeric(Series(min_max), downcast=downcast)
+ assert series.dtype == dtype
+
+
+@pytest.mark.parametrize("data,exp_data", [
+ ([200, 300, "", "NaN", 30000000000000000000],
+ [200, 300, np.nan, np.nan, 30000000000000000000]),
+ (["12345678901234567890", "1234567890", "ITEM"],
+ [12345678901234567890, 1234567890, np.nan])
+])
+def test_coerce_uint64_conflict(data, exp_data):
+ # see gh-17007 and gh-17125
+ #
+ # Still returns float despite the uint64-nan conflict,
+ # which would normally force the casting to object.
+ result = to_numeric(Series(data), errors="coerce")
+ expected = Series(exp_data, dtype=float)
+ tm.assert_series_equal(result, expected)
+
+
+@pytest.mark.parametrize("errors,exp", [
+ ("ignore", Series(["12345678901234567890", "1234567890", "ITEM"])),
+ ("raise", "Unable to parse string")
+])
+def test_non_coerce_uint64_conflict(errors, exp):
+ # see gh-17007 and gh-17125
+ #
+ # For completeness.
+ ser = Series(["12345678901234567890", "1234567890", "ITEM"])
+
+ if isinstance(exp, str):
+ with pytest.raises(ValueError, match=exp):
+ to_numeric(ser, errors=errors)
+ else:
+ result = to_numeric(ser, errors=errors)
+ tm.assert_series_equal(result, ser)
From 602eda47da1f560252ba4bf386875a68e561452c Mon Sep 17 00:00:00 2001
From: jbrockmendel <jbrockmendel@gmail.com>
Date: Sat, 26 Jan 2019 09:47:32 -0800
Subject: [PATCH 40/48] BLD: silence npy_no_deprecated warnings with
numpy>=1.16.0 (#24864)
---
setup.py | 5 +++++
1 file changed, 5 insertions(+)
diff --git a/setup.py b/setup.py
index ed2d905f4358b..4bf040b8c8e20 100755
--- a/setup.py
+++ b/setup.py
@@ -457,6 +457,11 @@ def run(self):
directives['linetrace'] = True
macros = [('CYTHON_TRACE', '1'), ('CYTHON_TRACE_NOGIL', '1')]
+# in numpy>=1.16.0, silence build warnings about deprecated API usage
+# we can't do anything about these warnings because they stem from
+# cython+numpy version mismatches.
+macros.append(('NPY_NO_DEPRECATED_API', '0'))
+
# ----------------------------------------------------------------------
# Specification of Dependencies
From 95f8dca47723192ddeed5a2f198d0521c687c9aa Mon Sep 17 00:00:00 2001
From: Noam Hershtig <noamher@users.noreply.github.com>
Date: Sat, 26 Jan 2019 19:48:41 +0200
Subject: [PATCH 41/48] CLN: Refactor cython to use memory views (#24932)
---
pandas/_libs/algos.pyx | 26 +++---
pandas/_libs/groupby_helper.pxi.in | 92 +++++++++++-----------
pandas/_libs/hashtable.pyx | 18 +++--
pandas/_libs/hashtable_class_helper.pxi.in | 2 +-
pandas/_libs/internals.pyx | 7 +-
pandas/_libs/join.pyx | 46 +++++------
pandas/_libs/lib.pyx | 47 +++++------
pandas/_libs/missing.pyx | 7 +-
pandas/_libs/parsers.pyx | 23 +++---
pandas/_libs/reduction.pyx | 2 +-
pandas/_libs/skiplist.pyx | 19 +++--
pandas/_libs/sparse_op_helper.pxi.in | 20 ++---
pandas/_libs/tslibs/conversion.pyx | 2 +-
pandas/_libs/tslibs/fields.pyx | 2 +-
pandas/_libs/tslibs/parsing.pyx | 5 +-
pandas/_libs/tslibs/period.pyx | 7 +-
pandas/_libs/tslibs/resolution.pyx | 19 ++---
pandas/_libs/window.pyx | 13 +--
pandas/io/msgpack/_packer.pyx | 38 ++++-----
pandas/io/msgpack/_unpacker.pyx | 48 +++++------
pandas/io/sas/sas.pyx | 11 +--
21 files changed, 240 insertions(+), 214 deletions(-)
diff --git a/pandas/_libs/algos.pyx b/pandas/_libs/algos.pyx
index b3c519ab99b6e..663411ad984c2 100644
--- a/pandas/_libs/algos.pyx
+++ b/pandas/_libs/algos.pyx
@@ -76,7 +76,7 @@ class NegInfinity(object):
@cython.wraparound(False)
@cython.boundscheck(False)
-cpdef ndarray[int64_t, ndim=1] unique_deltas(ndarray[int64_t] arr):
+cpdef ndarray[int64_t, ndim=1] unique_deltas(const int64_t[:] arr):
"""
Efficiently find the unique first-differences of the given array.
@@ -150,7 +150,7 @@ def is_lexsorted(list_of_arrays: list) -> bint:
@cython.boundscheck(False)
@cython.wraparound(False)
-def groupsort_indexer(ndarray[int64_t] index, Py_ssize_t ngroups):
+def groupsort_indexer(const int64_t[:] index, Py_ssize_t ngroups):
"""
compute a 1-d indexer that is an ordering of the passed index,
ordered by the groups. This is a reverse of the label
@@ -230,7 +230,7 @@ def kth_smallest(numeric[:] a, Py_ssize_t k) -> numeric:
@cython.boundscheck(False)
@cython.wraparound(False)
-def nancorr(ndarray[float64_t, ndim=2] mat, bint cov=0, minp=None):
+def nancorr(const float64_t[:, :] mat, bint cov=0, minp=None):
cdef:
Py_ssize_t i, j, xi, yi, N, K
bint minpv
@@ -294,7 +294,7 @@ def nancorr(ndarray[float64_t, ndim=2] mat, bint cov=0, minp=None):
@cython.boundscheck(False)
@cython.wraparound(False)
-def nancorr_spearman(ndarray[float64_t, ndim=2] mat, Py_ssize_t minp=1):
+def nancorr_spearman(const float64_t[:, :] mat, Py_ssize_t minp=1):
cdef:
Py_ssize_t i, j, xi, yi, N, K
ndarray[float64_t, ndim=2] result
@@ -435,8 +435,8 @@ def pad(ndarray[algos_t] old, ndarray[algos_t] new, limit=None):
@cython.boundscheck(False)
@cython.wraparound(False)
-def pad_inplace(ndarray[algos_t] values,
- ndarray[uint8_t, cast=True] mask,
+def pad_inplace(algos_t[:] values,
+ const uint8_t[:] mask,
limit=None):
cdef:
Py_ssize_t i, N
@@ -472,8 +472,8 @@ def pad_inplace(ndarray[algos_t] values,
@cython.boundscheck(False)
@cython.wraparound(False)
-def pad_2d_inplace(ndarray[algos_t, ndim=2] values,
- ndarray[uint8_t, ndim=2] mask,
+def pad_2d_inplace(algos_t[:, :] values,
+ const uint8_t[:, :] mask,
limit=None):
cdef:
Py_ssize_t i, j, N, K
@@ -602,8 +602,8 @@ def backfill(ndarray[algos_t] old, ndarray[algos_t] new, limit=None):
@cython.boundscheck(False)
@cython.wraparound(False)
-def backfill_inplace(ndarray[algos_t] values,
- ndarray[uint8_t, cast=True] mask,
+def backfill_inplace(algos_t[:] values,
+ const uint8_t[:] mask,
limit=None):
cdef:
Py_ssize_t i, N
@@ -639,8 +639,8 @@ def backfill_inplace(ndarray[algos_t] values,
@cython.boundscheck(False)
@cython.wraparound(False)
-def backfill_2d_inplace(ndarray[algos_t, ndim=2] values,
- ndarray[uint8_t, ndim=2] mask,
+def backfill_2d_inplace(algos_t[:, :] values,
+ const uint8_t[:, :] mask,
limit=None):
cdef:
Py_ssize_t i, j, N, K
@@ -678,7 +678,7 @@ def backfill_2d_inplace(ndarray[algos_t, ndim=2] values,
@cython.wraparound(False)
@cython.boundscheck(False)
-def arrmap(ndarray[algos_t] index, object func):
+def arrmap(algos_t[:] index, object func):
cdef:
Py_ssize_t length = index.shape[0]
Py_ssize_t i = 0
diff --git a/pandas/_libs/groupby_helper.pxi.in b/pandas/_libs/groupby_helper.pxi.in
index abac9f147848e..858039f038d02 100644
--- a/pandas/_libs/groupby_helper.pxi.in
+++ b/pandas/_libs/groupby_helper.pxi.in
@@ -29,10 +29,10 @@ def get_dispatch(dtypes):
@cython.wraparound(False)
@cython.boundscheck(False)
-def group_add_{{name}}(ndarray[{{c_type}}, ndim=2] out,
- ndarray[int64_t] counts,
- ndarray[{{c_type}}, ndim=2] values,
- ndarray[int64_t] labels,
+def group_add_{{name}}({{c_type}}[:, :] out,
+ int64_t[:] counts,
+ {{c_type}}[:, :] values,
+ const int64_t[:] labels,
Py_ssize_t min_count=0):
"""
Only aggregates on axis=0
@@ -76,10 +76,10 @@ def group_add_{{name}}(ndarray[{{c_type}}, ndim=2] out,
@cython.wraparound(False)
@cython.boundscheck(False)
-def group_prod_{{name}}(ndarray[{{c_type}}, ndim=2] out,
- ndarray[int64_t] counts,
- ndarray[{{c_type}}, ndim=2] values,
- ndarray[int64_t] labels,
+def group_prod_{{name}}({{c_type}}[:, :] out,
+ int64_t[:] counts,
+ {{c_type}}[:, :] values,
+ const int64_t[:] labels,
Py_ssize_t min_count=0):
"""
Only aggregates on axis=0
@@ -123,10 +123,10 @@ def group_prod_{{name}}(ndarray[{{c_type}}, ndim=2] out,
@cython.wraparound(False)
@cython.boundscheck(False)
@cython.cdivision(True)
-def group_var_{{name}}(ndarray[{{c_type}}, ndim=2] out,
- ndarray[int64_t] counts,
- ndarray[{{c_type}}, ndim=2] values,
- ndarray[int64_t] labels,
+def group_var_{{name}}({{c_type}}[:, :] out,
+ int64_t[:] counts,
+ {{c_type}}[:, :] values,
+ const int64_t[:] labels,
Py_ssize_t min_count=-1):
cdef:
Py_ssize_t i, j, N, K, lab, ncounts = len(counts)
@@ -175,10 +175,10 @@ def group_var_{{name}}(ndarray[{{c_type}}, ndim=2] out,
@cython.wraparound(False)
@cython.boundscheck(False)
-def group_mean_{{name}}(ndarray[{{c_type}}, ndim=2] out,
- ndarray[int64_t] counts,
- ndarray[{{c_type}}, ndim=2] values,
- ndarray[int64_t] labels,
+def group_mean_{{name}}({{c_type}}[:, :] out,
+ int64_t[:] counts,
+ {{c_type}}[:, :] values,
+ const int64_t[:] labels,
Py_ssize_t min_count=-1):
cdef:
Py_ssize_t i, j, N, K, lab, ncounts = len(counts)
@@ -220,11 +220,11 @@ def group_mean_{{name}}(ndarray[{{c_type}}, ndim=2] out,
@cython.wraparound(False)
@cython.boundscheck(False)
-def group_ohlc_{{name}}(ndarray[{{c_type}}, ndim=2] out,
- ndarray[int64_t] counts,
- ndarray[{{c_type}}, ndim=2] values,
- ndarray[int64_t] labels,
- Py_ssize_t min_count=-1):
+def group_ohlc_{{name}}({{c_type}}[:, :] out,
+ int64_t[:] counts,
+ {{c_type}}[:, :] values,
+ const int64_t[:] labels,
+ Py_ssize_t min_count=-1):
"""
Only aggregates on axis=0
"""
@@ -293,10 +293,10 @@ def get_dispatch(dtypes):
@cython.wraparound(False)
@cython.boundscheck(False)
-def group_last_{{name}}(ndarray[{{c_type}}, ndim=2] out,
- ndarray[int64_t] counts,
- ndarray[{{c_type}}, ndim=2] values,
- ndarray[int64_t] labels,
+def group_last_{{name}}({{c_type}}[:, :] out,
+ int64_t[:] counts,
+ {{c_type}}[:, :] values,
+ const int64_t[:] labels,
Py_ssize_t min_count=-1):
"""
Only aggregates on axis=0
@@ -350,10 +350,10 @@ def group_last_{{name}}(ndarray[{{c_type}}, ndim=2] out,
@cython.wraparound(False)
@cython.boundscheck(False)
-def group_nth_{{name}}(ndarray[{{c_type}}, ndim=2] out,
- ndarray[int64_t] counts,
- ndarray[{{c_type}}, ndim=2] values,
- ndarray[int64_t] labels, int64_t rank,
+def group_nth_{{name}}({{c_type}}[:, :] out,
+ int64_t[:] counts,
+ {{c_type}}[:, :] values,
+ const int64_t[:] labels, int64_t rank,
Py_ssize_t min_count=-1):
"""
Only aggregates on axis=0
@@ -411,9 +411,9 @@ def group_nth_{{name}}(ndarray[{{c_type}}, ndim=2] out,
@cython.boundscheck(False)
@cython.wraparound(False)
-def group_rank_{{name}}(ndarray[float64_t, ndim=2] out,
- ndarray[{{c_type}}, ndim=2] values,
- ndarray[int64_t] labels,
+def group_rank_{{name}}(float64_t[:, :] out,
+ {{c_type}}[:, :] values,
+ const int64_t[:] labels,
bint is_datetimelike, object ties_method,
bint ascending, bint pct, object na_option):
"""
@@ -606,10 +606,10 @@ ctypedef fused groupby_t:
@cython.wraparound(False)
@cython.boundscheck(False)
-def group_max(ndarray[groupby_t, ndim=2] out,
- ndarray[int64_t] counts,
- ndarray[groupby_t, ndim=2] values,
- ndarray[int64_t] labels,
+def group_max(groupby_t[:, :] out,
+ int64_t[:] counts,
+ groupby_t[:, :] values,
+ const int64_t[:] labels,
Py_ssize_t min_count=-1):
"""
Only aggregates on axis=0
@@ -669,10 +669,10 @@ def group_max(ndarray[groupby_t, ndim=2] out,
@cython.wraparound(False)
@cython.boundscheck(False)
-def group_min(ndarray[groupby_t, ndim=2] out,
- ndarray[int64_t] counts,
- ndarray[groupby_t, ndim=2] values,
- ndarray[int64_t] labels,
+def group_min(groupby_t[:, :] out,
+ int64_t[:] counts,
+ groupby_t[:, :] values,
+ const int64_t[:] labels,
Py_ssize_t min_count=-1):
"""
Only aggregates on axis=0
@@ -731,9 +731,9 @@ def group_min(ndarray[groupby_t, ndim=2] out,
@cython.boundscheck(False)
@cython.wraparound(False)
-def group_cummin(ndarray[groupby_t, ndim=2] out,
- ndarray[groupby_t, ndim=2] values,
- ndarray[int64_t] labels,
+def group_cummin(groupby_t[:, :] out,
+ groupby_t[:, :] values,
+ const int64_t[:] labels,
bint is_datetimelike):
"""
Only transforms on axis=0
@@ -779,9 +779,9 @@ def group_cummin(ndarray[groupby_t, ndim=2] out,
@cython.boundscheck(False)
@cython.wraparound(False)
-def group_cummax(ndarray[groupby_t, ndim=2] out,
- ndarray[groupby_t, ndim=2] values,
- ndarray[int64_t] labels,
+def group_cummax(groupby_t[:, :] out,
+ groupby_t[:, :] values,
+ const int64_t[:] labels,
bint is_datetimelike):
"""
Only transforms on axis=0
diff --git a/pandas/_libs/hashtable.pyx b/pandas/_libs/hashtable.pyx
index 47fa5932290af..8d0c451ad0ab8 100644
--- a/pandas/_libs/hashtable.pyx
+++ b/pandas/_libs/hashtable.pyx
@@ -52,9 +52,10 @@ include "hashtable_class_helper.pxi"
include "hashtable_func_helper.pxi"
cdef class Factorizer:
- cdef public PyObjectHashTable table
- cdef public ObjectVector uniques
- cdef public Py_ssize_t count
+ cdef public:
+ PyObjectHashTable table
+ ObjectVector uniques
+ Py_ssize_t count
def __init__(self, size_hint):
self.table = PyObjectHashTable(size_hint)
@@ -96,9 +97,10 @@ cdef class Factorizer:
cdef class Int64Factorizer:
- cdef public Int64HashTable table
- cdef public Int64Vector uniques
- cdef public Py_ssize_t count
+ cdef public:
+ Int64HashTable table
+ Int64Vector uniques
+ Py_ssize_t count
def __init__(self, size_hint):
self.table = Int64HashTable(size_hint)
@@ -140,7 +142,7 @@ cdef class Int64Factorizer:
@cython.wraparound(False)
@cython.boundscheck(False)
-def unique_label_indices(ndarray[int64_t, ndim=1] labels):
+def unique_label_indices(const int64_t[:] labels):
"""
indices of the first occurrences of the unique labels
*excluding* -1. equivalent to:
@@ -168,6 +170,6 @@ def unique_label_indices(ndarray[int64_t, ndim=1] labels):
kh_destroy_int64(table)
arr = idx.to_array()
- arr = arr[labels[arr].argsort()]
+ arr = arr[np.asarray(labels)[arr].argsort()]
return arr[1:] if arr.size != 0 and labels[arr[0]] == -1 else arr
diff --git a/pandas/_libs/hashtable_class_helper.pxi.in b/pandas/_libs/hashtable_class_helper.pxi.in
index eac35588b6fc3..3644928d8dedc 100644
--- a/pandas/_libs/hashtable_class_helper.pxi.in
+++ b/pandas/_libs/hashtable_class_helper.pxi.in
@@ -322,7 +322,7 @@ cdef class {{name}}HashTable(HashTable):
self.table.vals[k] = <Py_ssize_t>values[i]
@cython.boundscheck(False)
- def map_locations(self, ndarray[{{dtype}}_t, ndim=1] values):
+ def map_locations(self, const {{dtype}}_t[:] values):
cdef:
Py_ssize_t i, n = len(values)
int ret = 0
diff --git a/pandas/_libs/internals.pyx b/pandas/_libs/internals.pyx
index 72a1cf16f96b6..f23d2666b4bf4 100644
--- a/pandas/_libs/internals.pyx
+++ b/pandas/_libs/internals.pyx
@@ -23,10 +23,11 @@ from pandas._libs.algos import ensure_int64
cdef class BlockPlacement:
# __slots__ = '_as_slice', '_as_array', '_len'
- cdef slice _as_slice
- cdef object _as_array
+ cdef:
+ slice _as_slice
+ object _as_array
- cdef bint _has_slice, _has_array, _is_known_slice_like
+ bint _has_slice, _has_array, _is_known_slice_like
def __init__(self, val):
cdef:
diff --git a/pandas/_libs/join.pyx b/pandas/_libs/join.pyx
index e4440ac3d9fd8..503867058b3c8 100644
--- a/pandas/_libs/join.pyx
+++ b/pandas/_libs/join.pyx
@@ -14,7 +14,7 @@ from pandas._libs.algos import groupsort_indexer, ensure_platform_int
from pandas.core.algorithms import take_nd
-def inner_join(ndarray[int64_t] left, ndarray[int64_t] right,
+def inner_join(const int64_t[:] left, const int64_t[:] right,
Py_ssize_t max_groups):
cdef:
Py_ssize_t i, j, k, count = 0
@@ -65,7 +65,7 @@ def inner_join(ndarray[int64_t] left, ndarray[int64_t] right,
_get_result_indexer(right_sorter, right_indexer))
-def left_outer_join(ndarray[int64_t] left, ndarray[int64_t] right,
+def left_outer_join(const int64_t[:] left, const int64_t[:] right,
Py_ssize_t max_groups, sort=True):
cdef:
Py_ssize_t i, j, k, count = 0
@@ -139,7 +139,7 @@ def left_outer_join(ndarray[int64_t] left, ndarray[int64_t] right,
return left_indexer, right_indexer
-def full_outer_join(ndarray[int64_t] left, ndarray[int64_t] right,
+def full_outer_join(const int64_t[:] left, const int64_t[:] right,
Py_ssize_t max_groups):
cdef:
Py_ssize_t i, j, k, count = 0
@@ -213,7 +213,7 @@ def _get_result_indexer(sorter, indexer):
return res
-def ffill_indexer(ndarray[int64_t] indexer):
+def ffill_indexer(const int64_t[:] indexer):
cdef:
Py_ssize_t i, n = len(indexer)
ndarray[int64_t] result
@@ -252,7 +252,7 @@ ctypedef fused join_t:
@cython.wraparound(False)
@cython.boundscheck(False)
-def left_join_indexer_unique(ndarray[join_t] left, ndarray[join_t] right):
+def left_join_indexer_unique(join_t[:] left, join_t[:] right):
cdef:
Py_ssize_t i, j, nleft, nright
ndarray[int64_t] indexer
@@ -677,10 +677,10 @@ ctypedef fused by_t:
uint64_t
-def asof_join_backward_on_X_by_Y(ndarray[asof_t] left_values,
- ndarray[asof_t] right_values,
- ndarray[by_t] left_by_values,
- ndarray[by_t] right_by_values,
+def asof_join_backward_on_X_by_Y(asof_t[:] left_values,
+ asof_t[:] right_values,
+ by_t[:] left_by_values,
+ by_t[:] right_by_values,
bint allow_exact_matches=1,
tolerance=None):
@@ -746,10 +746,10 @@ def asof_join_backward_on_X_by_Y(ndarray[asof_t] left_values,
return left_indexer, right_indexer
-def asof_join_forward_on_X_by_Y(ndarray[asof_t] left_values,
- ndarray[asof_t] right_values,
- ndarray[by_t] left_by_values,
- ndarray[by_t] right_by_values,
+def asof_join_forward_on_X_by_Y(asof_t[:] left_values,
+ asof_t[:] right_values,
+ by_t[:] left_by_values,
+ by_t[:] right_by_values,
bint allow_exact_matches=1,
tolerance=None):
@@ -815,10 +815,10 @@ def asof_join_forward_on_X_by_Y(ndarray[asof_t] left_values,
return left_indexer, right_indexer
-def asof_join_nearest_on_X_by_Y(ndarray[asof_t] left_values,
- ndarray[asof_t] right_values,
- ndarray[by_t] left_by_values,
- ndarray[by_t] right_by_values,
+def asof_join_nearest_on_X_by_Y(asof_t[:] left_values,
+ asof_t[:] right_values,
+ by_t[:] left_by_values,
+ by_t[:] right_by_values,
bint allow_exact_matches=1,
tolerance=None):
@@ -864,8 +864,8 @@ def asof_join_nearest_on_X_by_Y(ndarray[asof_t] left_values,
# asof_join
# ----------------------------------------------------------------------
-def asof_join_backward(ndarray[asof_t] left_values,
- ndarray[asof_t] right_values,
+def asof_join_backward(asof_t[:] left_values,
+ asof_t[:] right_values,
bint allow_exact_matches=1,
tolerance=None):
@@ -917,8 +917,8 @@ def asof_join_backward(ndarray[asof_t] left_values,
return left_indexer, right_indexer
-def asof_join_forward(ndarray[asof_t] left_values,
- ndarray[asof_t] right_values,
+def asof_join_forward(asof_t[:] left_values,
+ asof_t[:] right_values,
bint allow_exact_matches=1,
tolerance=None):
@@ -971,8 +971,8 @@ def asof_join_forward(ndarray[asof_t] left_values,
return left_indexer, right_indexer
-def asof_join_nearest(ndarray[asof_t] left_values,
- ndarray[asof_t] right_values,
+def asof_join_nearest(asof_t[:] left_values,
+ asof_t[:] right_values,
bint allow_exact_matches=1,
tolerance=None):
diff --git a/pandas/_libs/lib.pyx b/pandas/_libs/lib.pyx
index f845a5437ded4..4745916eb0ce2 100644
--- a/pandas/_libs/lib.pyx
+++ b/pandas/_libs/lib.pyx
@@ -40,11 +40,12 @@ cdef extern from "numpy/arrayobject.h":
# Use PyDataType_* macros when possible, however there are no macros
# for accessing some of the fields, so some are defined. Please
# ask on cython-dev if you need more.
- cdef int type_num
- cdef int itemsize "elsize"
- cdef char byteorder
- cdef object fields
- cdef tuple names
+ cdef:
+ int type_num
+ int itemsize "elsize"
+ char byteorder
+ object fields
+ tuple names
cdef extern from "src/parse_helper.h":
@@ -67,12 +68,13 @@ from pandas._libs.missing cimport (
# constants that will be compared to potentially arbitrarily large
# python int
-cdef object oINT64_MAX = <int64_t>INT64_MAX
-cdef object oINT64_MIN = <int64_t>INT64_MIN
-cdef object oUINT64_MAX = <uint64_t>UINT64_MAX
+cdef:
+ object oINT64_MAX = <int64_t>INT64_MAX
+ object oINT64_MIN = <int64_t>INT64_MIN
+ object oUINT64_MAX = <uint64_t>UINT64_MAX
-cdef bint PY2 = sys.version_info[0] == 2
-cdef float64_t NaN = <float64_t>np.NaN
+ bint PY2 = sys.version_info[0] == 2
+ float64_t NaN = <float64_t>np.NaN
def values_from_object(obj: object):
@@ -376,7 +378,7 @@ def fast_zip(list ndarrays):
return result
-def get_reverse_indexer(ndarray[int64_t] indexer, Py_ssize_t length):
+def get_reverse_indexer(const int64_t[:] indexer, Py_ssize_t length):
"""
Reverse indexing operation.
@@ -405,7 +407,7 @@ def get_reverse_indexer(ndarray[int64_t] indexer, Py_ssize_t length):
@cython.wraparound(False)
@cython.boundscheck(False)
-def has_infs_f4(ndarray[float32_t] arr) -> bool:
+def has_infs_f4(const float32_t[:] arr) -> bool:
cdef:
Py_ssize_t i, n = len(arr)
float32_t inf, neginf, val
@@ -422,7 +424,7 @@ def has_infs_f4(ndarray[float32_t] arr) -> bool:
@cython.wraparound(False)
@cython.boundscheck(False)
-def has_infs_f8(ndarray[float64_t] arr) -> bool:
+def has_infs_f8(const float64_t[:] arr) -> bool:
cdef:
Py_ssize_t i, n = len(arr)
float64_t inf, neginf, val
@@ -660,7 +662,7 @@ def clean_index_list(obj: list):
# is a general, O(max(len(values), len(binner))) method.
@cython.boundscheck(False)
@cython.wraparound(False)
-def generate_bins_dt64(ndarray[int64_t] values, ndarray[int64_t] binner,
+def generate_bins_dt64(ndarray[int64_t] values, const int64_t[:] binner,
object closed='left', bint hasnans=0):
"""
Int64 (datetime64) version of generic python version in groupby.py
@@ -723,7 +725,7 @@ def generate_bins_dt64(ndarray[int64_t] values, ndarray[int64_t] binner,
@cython.boundscheck(False)
@cython.wraparound(False)
-def row_bool_subset(ndarray[float64_t, ndim=2] values,
+def row_bool_subset(const float64_t[:, :] values,
ndarray[uint8_t, cast=True] mask):
cdef:
Py_ssize_t i, j, n, k, pos = 0
@@ -767,8 +769,8 @@ def row_bool_subset_object(ndarray[object, ndim=2] values,
@cython.boundscheck(False)
@cython.wraparound(False)
-def get_level_sorter(ndarray[int64_t, ndim=1] label,
- ndarray[int64_t, ndim=1] starts):
+def get_level_sorter(const int64_t[:] label,
+ const int64_t[:] starts):
"""
argsort for a single level of a multi-index, keeping the order of higher
levels unchanged. `starts` points to starts of same-key indices w.r.t
@@ -780,10 +782,11 @@ def get_level_sorter(ndarray[int64_t, ndim=1] label,
int64_t l, r
Py_ssize_t i
ndarray[int64_t, ndim=1] out = np.empty(len(label), dtype=np.int64)
+ ndarray[int64_t, ndim=1] label_arr = np.asarray(label)
for i in range(len(starts) - 1):
l, r = starts[i], starts[i + 1]
- out[l:r] = l + label[l:r].argsort(kind='mergesort')
+ out[l:r] = l + label_arr[l:r].argsort(kind='mergesort')
return out
@@ -791,7 +794,7 @@ def get_level_sorter(ndarray[int64_t, ndim=1] label,
@cython.boundscheck(False)
@cython.wraparound(False)
def count_level_2d(ndarray[uint8_t, ndim=2, cast=True] mask,
- ndarray[int64_t, ndim=1] labels,
+ const int64_t[:] labels,
Py_ssize_t max_bin,
int axis):
cdef:
@@ -818,7 +821,7 @@ def count_level_2d(ndarray[uint8_t, ndim=2, cast=True] mask,
return counts
-def generate_slices(ndarray[int64_t] labels, Py_ssize_t ngroups):
+def generate_slices(const int64_t[:] labels, Py_ssize_t ngroups):
cdef:
Py_ssize_t i, group_size, n, start
int64_t lab
@@ -847,7 +850,7 @@ def generate_slices(ndarray[int64_t] labels, Py_ssize_t ngroups):
return starts, ends
-def indices_fast(object index, ndarray[int64_t] labels, list keys,
+def indices_fast(object index, const int64_t[:] labels, list keys,
list sorted_labels):
cdef:
Py_ssize_t i, j, k, lab, cur, start, n = len(labels)
@@ -2146,7 +2149,7 @@ def maybe_convert_objects(ndarray[object] objects, bint try_float=0,
@cython.boundscheck(False)
@cython.wraparound(False)
-def map_infer_mask(ndarray arr, object f, ndarray[uint8_t] mask,
+def map_infer_mask(ndarray arr, object f, const uint8_t[:] mask,
bint convert=1):
"""
Substitute for np.vectorize with pandas-friendly dtype inference
diff --git a/pandas/_libs/missing.pyx b/pandas/_libs/missing.pyx
index 229edbac4992d..ab0e4cd6cc765 100644
--- a/pandas/_libs/missing.pyx
+++ b/pandas/_libs/missing.pyx
@@ -16,10 +16,11 @@ from pandas._libs.tslibs.nattype cimport (
checknull_with_nat, c_NaT as NaT, is_null_datetimelike)
-cdef float64_t INF = <float64_t>np.inf
-cdef float64_t NEGINF = -INF
+cdef:
+ float64_t INF = <float64_t>np.inf
+ float64_t NEGINF = -INF
-cdef int64_t NPY_NAT = util.get_nat()
+ int64_t NPY_NAT = util.get_nat()
cpdef bint checknull(object val):
diff --git a/pandas/_libs/parsers.pyx b/pandas/_libs/parsers.pyx
index 6cb6ed749f87b..f679746643643 100644
--- a/pandas/_libs/parsers.pyx
+++ b/pandas/_libs/parsers.pyx
@@ -64,10 +64,11 @@ from pandas.errors import (ParserError, DtypeWarning,
CParserError = ParserError
-cdef bint PY3 = (sys.version_info[0] >= 3)
+cdef:
+ bint PY3 = (sys.version_info[0] >= 3)
-cdef float64_t INF = <float64_t>np.inf
-cdef float64_t NEGINF = -INF
+ float64_t INF = <float64_t>np.inf
+ float64_t NEGINF = -INF
cdef extern from "errno.h":
@@ -735,7 +736,7 @@ cdef class TextReader:
int status
int64_t hr, data_line
char *errors = "strict"
- cdef StringPath path = _string_path(self.c_encoding)
+ StringPath path = _string_path(self.c_encoding)
header = []
unnamed_cols = set()
@@ -1389,8 +1390,9 @@ cdef class TextReader:
return None
-cdef object _true_values = [b'True', b'TRUE', b'true']
-cdef object _false_values = [b'False', b'FALSE', b'false']
+cdef:
+ object _true_values = [b'True', b'TRUE', b'true']
+ object _false_values = [b'False', b'FALSE', b'false']
def _ensure_encoded(list lst):
@@ -1637,7 +1639,7 @@ cdef _categorical_convert(parser_t *parser, int64_t col,
int64_t current_category = 0
char *errors = "strict"
- cdef StringPath path = _string_path(encoding)
+ StringPath path = _string_path(encoding)
int ret = 0
kh_str_t *table
@@ -1727,9 +1729,10 @@ cdef inline void _to_fw_string_nogil(parser_t *parser, int64_t col,
data += width
-cdef char* cinf = b'inf'
-cdef char* cposinf = b'+inf'
-cdef char* cneginf = b'-inf'
+cdef:
+ char* cinf = b'inf'
+ char* cposinf = b'+inf'
+ char* cneginf = b'-inf'
cdef _try_double(parser_t *parser, int64_t col,
diff --git a/pandas/_libs/reduction.pyx b/pandas/_libs/reduction.pyx
index ca39c4de4d309..507567cf480d7 100644
--- a/pandas/_libs/reduction.pyx
+++ b/pandas/_libs/reduction.pyx
@@ -494,7 +494,7 @@ class InvalidApply(Exception):
def apply_frame_axis0(object frame, object f, object names,
- ndarray[int64_t] starts, ndarray[int64_t] ends):
+ const int64_t[:] starts, const int64_t[:] ends):
cdef:
BlockSlider slider
Py_ssize_t i, n = len(starts)
diff --git a/pandas/_libs/skiplist.pyx b/pandas/_libs/skiplist.pyx
index 6698fcb767d7c..2fdee72f9d588 100644
--- a/pandas/_libs/skiplist.pyx
+++ b/pandas/_libs/skiplist.pyx
@@ -57,8 +57,9 @@ cdef class IndexableSkiplist:
return self.get(i)
cpdef get(self, Py_ssize_t i):
- cdef Py_ssize_t level
- cdef Node node
+ cdef:
+ Py_ssize_t level
+ Node node
node = self.head
i += 1
@@ -71,9 +72,10 @@ cdef class IndexableSkiplist:
return node.value
cpdef insert(self, double value):
- cdef Py_ssize_t level, steps, d
- cdef Node node, prevnode, newnode, next_at_level, tmp
- cdef list chain, steps_at_level
+ cdef:
+ Py_ssize_t level, steps, d
+ Node node, prevnode, newnode, next_at_level, tmp
+ list chain, steps_at_level
# find first node on each level where node.next[levels].value > value
chain = [None] * self.maxlevels
@@ -110,9 +112,10 @@ cdef class IndexableSkiplist:
self.size += 1
cpdef remove(self, double value):
- cdef Py_ssize_t level, d
- cdef Node node, prevnode, tmpnode, next_at_level
- cdef list chain
+ cdef:
+ Py_ssize_t level, d
+ Node node, prevnode, tmpnode, next_at_level
+ list chain
# find first node on each level where node.next[levels].value >= value
chain = [None] * self.maxlevels
diff --git a/pandas/_libs/sparse_op_helper.pxi.in b/pandas/_libs/sparse_op_helper.pxi.in
index c6621ab5977ca..5949a3fd0ed81 100644
--- a/pandas/_libs/sparse_op_helper.pxi.in
+++ b/pandas/_libs/sparse_op_helper.pxi.in
@@ -125,10 +125,10 @@ def get_dispatch(dtypes):
@cython.wraparound(False)
@cython.boundscheck(False)
-cdef inline tuple block_op_{{opname}}_{{dtype}}(ndarray x_,
+cdef inline tuple block_op_{{opname}}_{{dtype}}({{dtype}}_t[:] x_,
BlockIndex xindex,
{{dtype}}_t xfill,
- ndarray y_,
+ {{dtype}}_t[:] y_,
BlockIndex yindex,
{{dtype}}_t yfill):
'''
@@ -142,7 +142,7 @@ cdef inline tuple block_op_{{opname}}_{{dtype}}(ndarray x_,
int32_t xloc, yloc
Py_ssize_t xblock = 0, yblock = 0 # block numbers
- ndarray[{{dtype}}_t, ndim=1] x, y
+ {{dtype}}_t[:] x, y
ndarray[{{rdtype}}_t, ndim=1] out
# to suppress Cython warning
@@ -226,16 +226,18 @@ cdef inline tuple block_op_{{opname}}_{{dtype}}(ndarray x_,
@cython.wraparound(False)
@cython.boundscheck(False)
-cdef inline tuple int_op_{{opname}}_{{dtype}}(ndarray x_, IntIndex xindex,
+cdef inline tuple int_op_{{opname}}_{{dtype}}({{dtype}}_t[:] x_,
+ IntIndex xindex,
{{dtype}}_t xfill,
- ndarray y_, IntIndex yindex,
+ {{dtype}}_t[:] y_,
+ IntIndex yindex,
{{dtype}}_t yfill):
cdef:
IntIndex out_index
Py_ssize_t xi = 0, yi = 0, out_i = 0 # fp buf indices
int32_t xloc, yloc
- ndarray[int32_t, ndim=1] xindices, yindices, out_indices
- ndarray[{{dtype}}_t, ndim=1] x, y
+ int32_t[:] xindices, yindices, out_indices
+ {{dtype}}_t[:] x, y
ndarray[{{rdtype}}_t, ndim=1] out
# suppress Cython compiler warnings due to inlining
@@ -284,9 +286,9 @@ cdef inline tuple int_op_{{opname}}_{{dtype}}(ndarray x_, IntIndex xindex,
return out, out_index, {{(opname, 'xfill', 'yfill', dtype) | get_op}}
-cpdef sparse_{{opname}}_{{dtype}}(ndarray[{{dtype}}_t, ndim=1] x,
+cpdef sparse_{{opname}}_{{dtype}}({{dtype}}_t[:] x,
SparseIndex xindex, {{dtype}}_t xfill,
- ndarray[{{dtype}}_t, ndim=1] y,
+ {{dtype}}_t[:] y,
SparseIndex yindex, {{dtype}}_t yfill):
if isinstance(xindex, BlockIndex):
diff --git a/pandas/_libs/tslibs/conversion.pyx b/pandas/_libs/tslibs/conversion.pyx
index 6c8b732928bc3..1c0adaaa288a9 100644
--- a/pandas/_libs/tslibs/conversion.pyx
+++ b/pandas/_libs/tslibs/conversion.pyx
@@ -147,7 +147,7 @@ def ensure_timedelta64ns(arr: ndarray, copy: bool=True):
@cython.boundscheck(False)
@cython.wraparound(False)
-def datetime_to_datetime64(values: object[:]):
+def datetime_to_datetime64(object[:] values):
"""
Convert ndarray of datetime-like objects to int64 array representing
nanosecond timestamps.
diff --git a/pandas/_libs/tslibs/fields.pyx b/pandas/_libs/tslibs/fields.pyx
index 5cda7992369fc..240f008394099 100644
--- a/pandas/_libs/tslibs/fields.pyx
+++ b/pandas/_libs/tslibs/fields.pyx
@@ -381,7 +381,7 @@ def get_start_end_field(int64_t[:] dtindex, object field,
@cython.wraparound(False)
@cython.boundscheck(False)
-def get_date_field(ndarray[int64_t] dtindex, object field):
+def get_date_field(int64_t[:] dtindex, object field):
"""
Given a int64-based datetime index, extract the year, month, etc.,
field and return an array of these values.
diff --git a/pandas/_libs/tslibs/parsing.pyx b/pandas/_libs/tslibs/parsing.pyx
index 82719de2dbdbd..7759e165b7193 100644
--- a/pandas/_libs/tslibs/parsing.pyx
+++ b/pandas/_libs/tslibs/parsing.pyx
@@ -44,9 +44,10 @@ class DateParseError(ValueError):
_DEFAULT_DATETIME = datetime(1, 1, 1).replace(hour=0, minute=0,
second=0, microsecond=0)
-cdef object _TIMEPAT = re.compile(r'^([01]?[0-9]|2[0-3]):([0-5][0-9])')
+cdef:
+ object _TIMEPAT = re.compile(r'^([01]?[0-9]|2[0-3]):([0-5][0-9])')
-cdef set _not_datelike_strings = {'a', 'A', 'm', 'M', 'p', 'P', 't', 'T'}
+ set _not_datelike_strings = {'a', 'A', 'm', 'M', 'p', 'P', 't', 'T'}
# ----------------------------------------------------------------------
diff --git a/pandas/_libs/tslibs/period.pyx b/pandas/_libs/tslibs/period.pyx
index 2f4edb7de8f95..e38e9a1ca5df6 100644
--- a/pandas/_libs/tslibs/period.pyx
+++ b/pandas/_libs/tslibs/period.pyx
@@ -52,9 +52,10 @@ from pandas._libs.tslibs.nattype cimport (
from pandas._libs.tslibs.offsets cimport to_offset
from pandas._libs.tslibs.offsets import _Tick
-cdef bint PY2 = str == bytes
-cdef enum:
- INT32_MIN = -2147483648
+cdef:
+ bint PY2 = str == bytes
+ enum:
+ INT32_MIN = -2147483648
ctypedef struct asfreq_info:
diff --git a/pandas/_libs/tslibs/resolution.pyx b/pandas/_libs/tslibs/resolution.pyx
index f80c1e9841abe..13a4f5ba48557 100644
--- a/pandas/_libs/tslibs/resolution.pyx
+++ b/pandas/_libs/tslibs/resolution.pyx
@@ -16,15 +16,16 @@ from pandas._libs.tslibs.ccalendar cimport get_days_in_month
# ----------------------------------------------------------------------
# Constants
-cdef int64_t NPY_NAT = get_nat()
-
-cdef int RESO_NS = 0
-cdef int RESO_US = 1
-cdef int RESO_MS = 2
-cdef int RESO_SEC = 3
-cdef int RESO_MIN = 4
-cdef int RESO_HR = 5
-cdef int RESO_DAY = 6
+cdef:
+ int64_t NPY_NAT = get_nat()
+
+ int RESO_NS = 0
+ int RESO_US = 1
+ int RESO_MS = 2
+ int RESO_SEC = 3
+ int RESO_MIN = 4
+ int RESO_HR = 5
+ int RESO_DAY = 6
# ----------------------------------------------------------------------
diff --git a/pandas/_libs/window.pyx b/pandas/_libs/window.pyx
index e8f3de64c3823..cc5b3b63f5b04 100644
--- a/pandas/_libs/window.pyx
+++ b/pandas/_libs/window.pyx
@@ -26,13 +26,14 @@ from pandas._libs.skiplist cimport (
skiplist_t, skiplist_init, skiplist_destroy, skiplist_get, skiplist_insert,
skiplist_remove)
-cdef float32_t MINfloat32 = np.NINF
-cdef float64_t MINfloat64 = np.NINF
+cdef:
+ float32_t MINfloat32 = np.NINF
+ float64_t MINfloat64 = np.NINF
-cdef float32_t MAXfloat32 = np.inf
-cdef float64_t MAXfloat64 = np.inf
+ float32_t MAXfloat32 = np.inf
+ float64_t MAXfloat64 = np.inf
-cdef float64_t NaN = <float64_t>np.NaN
+ float64_t NaN = <float64_t>np.NaN
cdef inline int int_max(int a, int b): return a if a >= b else b
cdef inline int int_min(int a, int b): return a if a <= b else b
@@ -242,7 +243,7 @@ cdef class VariableWindowIndexer(WindowIndexer):
# max window size
self.win = (self.end - self.start).max()
- def build(self, ndarray[int64_t] index, int64_t win, bint left_closed,
+ def build(self, const int64_t[:] index, int64_t win, bint left_closed,
bint right_closed):
cdef:
diff --git a/pandas/io/msgpack/_packer.pyx b/pandas/io/msgpack/_packer.pyx
index d67c632188e62..8e2d943d8ddb1 100644
--- a/pandas/io/msgpack/_packer.pyx
+++ b/pandas/io/msgpack/_packer.pyx
@@ -74,14 +74,15 @@ cdef class Packer(object):
Use bin type introduced in msgpack spec 2.0 for bytes.
It also enable str8 type for unicode.
"""
- cdef msgpack_packer pk
- cdef object _default
- cdef object _bencoding
- cdef object _berrors
- cdef char *encoding
- cdef char *unicode_errors
- cdef bint use_float
- cdef bint autoreset
+ cdef:
+ msgpack_packer pk
+ object _default
+ object _bencoding
+ object _berrors
+ char *encoding
+ char *unicode_errors
+ bint use_float
+ bint autoreset
def __cinit__(self):
cdef int buf_size = 1024 * 1024
@@ -123,16 +124,17 @@ cdef class Packer(object):
cdef int _pack(self, object o,
int nest_limit=DEFAULT_RECURSE_LIMIT) except -1:
- cdef long long llval
- cdef unsigned long long ullval
- cdef long longval
- cdef float fval
- cdef double dval
- cdef char* rawval
- cdef int ret
- cdef dict d
- cdef size_t L
- cdef int default_used = 0
+ cdef:
+ long long llval
+ unsigned long long ullval
+ long longval
+ float fval
+ double dval
+ char* rawval
+ int ret
+ dict d
+ size_t L
+ int default_used = 0
if nest_limit < 0:
raise PackValueError("recursion limit exceeded.")
diff --git a/pandas/io/msgpack/_unpacker.pyx b/pandas/io/msgpack/_unpacker.pyx
index 0c50aa5e68103..9bbfe749ef9ba 100644
--- a/pandas/io/msgpack/_unpacker.pyx
+++ b/pandas/io/msgpack/_unpacker.pyx
@@ -120,14 +120,15 @@ def unpackb(object packed, object object_hook=None, object list_hook=None,
See :class:`Unpacker` for options.
"""
- cdef unpack_context ctx
- cdef size_t off = 0
- cdef int ret
+ cdef:
+ unpack_context ctx
+ size_t off = 0
+ int ret
- cdef char* buf
- cdef Py_ssize_t buf_len
- cdef char* cenc = NULL
- cdef char* cerr = NULL
+ char* buf
+ Py_ssize_t buf_len
+ char* cenc = NULL
+ char* cerr = NULL
PyObject_AsReadBuffer(packed, <const void**>&buf, &buf_len)
@@ -243,16 +244,17 @@ cdef class Unpacker(object):
for o in unpacker:
process(o)
"""
- cdef unpack_context ctx
- cdef char* buf
- cdef size_t buf_size, buf_head, buf_tail
- cdef object file_like
- cdef object file_like_read
- cdef Py_ssize_t read_size
- # To maintain refcnt.
- cdef object object_hook, object_pairs_hook, list_hook, ext_hook
- cdef object encoding, unicode_errors
- cdef size_t max_buffer_size
+ cdef:
+ unpack_context ctx
+ char* buf
+ size_t buf_size, buf_head, buf_tail
+ object file_like
+ object file_like_read
+ Py_ssize_t read_size
+ # To maintain refcnt.
+ object object_hook, object_pairs_hook, list_hook, ext_hook
+ object encoding, unicode_errors
+ size_t max_buffer_size
def __cinit__(self):
self.buf = NULL
@@ -270,8 +272,9 @@ cdef class Unpacker(object):
Py_ssize_t max_array_len=2147483647,
Py_ssize_t max_map_len=2147483647,
Py_ssize_t max_ext_len=2147483647):
- cdef char *cenc=NULL,
- cdef char *cerr=NULL
+ cdef:
+ char *cenc=NULL,
+ char *cerr=NULL
self.object_hook = object_hook
self.object_pairs_hook = object_pairs_hook
@@ -388,9 +391,10 @@ cdef class Unpacker(object):
cdef object _unpack(self, execute_fn execute,
object write_bytes, bint iter=0):
- cdef int ret
- cdef object obj
- cdef size_t prev_head
+ cdef:
+ int ret
+ object obj
+ size_t prev_head
if self.buf_head >= self.buf_tail and self.file_like is not None:
self.read_from_file()
diff --git a/pandas/io/sas/sas.pyx b/pandas/io/sas/sas.pyx
index a5bfd5866a261..9b8fba16741f6 100644
--- a/pandas/io/sas/sas.pyx
+++ b/pandas/io/sas/sas.pyx
@@ -203,11 +203,12 @@ cdef enum ColumnTypes:
# type the page_data types
-cdef int page_meta_type = const.page_meta_type
-cdef int page_mix_types_0 = const.page_mix_types[0]
-cdef int page_mix_types_1 = const.page_mix_types[1]
-cdef int page_data_type = const.page_data_type
-cdef int subheader_pointers_offset = const.subheader_pointers_offset
+cdef:
+ int page_meta_type = const.page_meta_type
+ int page_mix_types_0 = const.page_mix_types[0]
+ int page_mix_types_1 = const.page_mix_types[1]
+ int page_data_type = const.page_data_type
+ int subheader_pointers_offset = const.subheader_pointers_offset
cdef class Parser(object):
From 2b16e2e6c5a298396727fc2e66a60edf1eb13bf9 Mon Sep 17 00:00:00 2001
From: Daniel Saxton <daniel.saxton@gmail.com>
Date: Sat, 26 Jan 2019 21:05:46 -0600
Subject: [PATCH 42/48] DOC: Clean sort_values and sort_index docstrings
(#24843)
---
pandas/core/generic.py | 51 +++++++++++++++++++++++-------------------
pandas/core/series.py | 4 ++--
2 files changed, 30 insertions(+), 25 deletions(-)
diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 2b97661fe9ec3..a351233a77465 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -530,7 +530,7 @@ def set_axis(self, labels, axis=0, inplace=None):
The axis to update. The value 0 identifies the rows, and 1
identifies the columns.
- inplace : boolean, default None
+ inplace : bool, default None
Whether to return a new %(klass)s instance.
.. warning::
@@ -3966,35 +3966,37 @@ def add_suffix(self, suffix):
def sort_values(self, by=None, axis=0, ascending=True, inplace=False,
kind='quicksort', na_position='last'):
"""
- Sort by the values along either axis
+ Sort by the values along either axis.
Parameters
----------%(optional_by)s
axis : %(axes_single_arg)s, default 0
- Axis to be sorted
+ Axis to be sorted.
ascending : bool or list of bool, default True
Sort ascending vs. descending. Specify list for multiple sort
orders. If this is a list of bools, must match the length of
the by.
inplace : bool, default False
- if True, perform operation in-place
+ If True, perform operation in-place.
kind : {'quicksort', 'mergesort', 'heapsort'}, default 'quicksort'
Choice of sorting algorithm. See also ndarray.np.sort for more
information. `mergesort` is the only stable algorithm. For
DataFrames, this option is only applied when sorting on a single
column or label.
na_position : {'first', 'last'}, default 'last'
- `first` puts NaNs at the beginning, `last` puts NaNs at the end
+ Puts NaNs at the beginning if `first`; `last` puts NaNs at the
+ end.
Returns
-------
- sorted_obj : %(klass)s
+ sorted_obj : DataFrame or None
+ DataFrame with sorted values if inplace=False, None otherwise.
Examples
--------
>>> df = pd.DataFrame({
- ... 'col1' : ['A', 'A', 'B', np.nan, 'D', 'C'],
- ... 'col2' : [2, 1, 9, 8, 7, 4],
+ ... 'col1': ['A', 'A', 'B', np.nan, 'D', 'C'],
+ ... 'col2': [2, 1, 9, 8, 7, 4],
... 'col3': [0, 1, 9, 4, 2, 3],
... })
>>> df
@@ -4056,32 +4058,35 @@ def sort_values(self, by=None, axis=0, ascending=True, inplace=False,
def sort_index(self, axis=0, level=None, ascending=True, inplace=False,
kind='quicksort', na_position='last', sort_remaining=True):
"""
- Sort object by labels (along an axis)
+ Sort object by labels (along an axis).
Parameters
----------
- axis : %(axes)s to direct sorting
+ axis : {0 or 'index', 1 or 'columns'}, default 0
+ The axis along which to sort. The value 0 identifies the rows,
+ and 1 identifies the columns.
level : int or level name or list of ints or list of level names
- if not None, sort on values in specified index level(s)
- ascending : boolean, default True
- Sort ascending vs. descending
+ If not None, sort on values in specified index level(s).
+ ascending : bool, default True
+ Sort ascending vs. descending.
inplace : bool, default False
- if True, perform operation in-place
+ If True, perform operation in-place.
kind : {'quicksort', 'mergesort', 'heapsort'}, default 'quicksort'
- Choice of sorting algorithm. See also ndarray.np.sort for more
- information. `mergesort` is the only stable algorithm. For
- DataFrames, this option is only applied when sorting on a single
- column or label.
+ Choice of sorting algorithm. See also ndarray.np.sort for more
+ information. `mergesort` is the only stable algorithm. For
+ DataFrames, this option is only applied when sorting on a single
+ column or label.
na_position : {'first', 'last'}, default 'last'
- `first` puts NaNs at the beginning, `last` puts NaNs at the end.
- Not implemented for MultiIndex.
+ Puts NaNs at the beginning if `first`; `last` puts NaNs at the end.
+ Not implemented for MultiIndex.
sort_remaining : bool, default True
- if true and sorting by level and index is multilevel, sort by other
- levels too (in order) after sorting by specified level
+ If True and sorting by level and index is multilevel, sort by other
+ levels too (in order) after sorting by specified level.
Returns
-------
- sorted_obj : %(klass)s
+ sorted_obj : DataFrame or None
+ DataFrame with sorted index if inplace=False, None otherwise.
"""
inplace = validate_bool_kwarg(inplace, 'inplace')
axis = self._get_axis_number(axis)
diff --git a/pandas/core/series.py b/pandas/core/series.py
index 0c8e697c572e8..a25aa86a47927 100644
--- a/pandas/core/series.py
+++ b/pandas/core/series.py
@@ -2857,13 +2857,13 @@ def sort_index(self, axis=0, level=None, ascending=True, inplace=False,
If 'first' puts NaNs at the beginning, 'last' puts NaNs at the end.
Not implemented for MultiIndex.
sort_remaining : bool, default True
- If true and sorting by level and index is multilevel, sort by other
+ If True and sorting by level and index is multilevel, sort by other
levels too (in order) after sorting by specified level.
Returns
-------
pandas.Series
- The original Series sorted by the labels
+ The original Series sorted by the labels.
See Also
--------
From 22b279569e4abef2c727a5dd7f990558268e3409 Mon Sep 17 00:00:00 2001
From: Kaiqi Dong <kaiqi@kth.se>
Date: Sun, 27 Jan 2019 22:17:43 +0100
Subject: [PATCH 43/48] changes based on reviews
---
pandas/plotting/_core.py | 6 +++---
1 file changed, 3 insertions(+), 3 deletions(-)
diff --git a/pandas/plotting/_core.py b/pandas/plotting/_core.py
index 8002811acc88a..cb7df013c4771 100644
--- a/pandas/plotting/_core.py
+++ b/pandas/plotting/_core.py
@@ -309,10 +309,10 @@ def _setup_subplots(self):
axes = _flatten(axes)
- valid_log = [False, True, 'sym']
- for i in [self.logx, self.logy, self.loglog]:
+ valid_log = [False, True, 'sym', None]
+ for i in (self.logx, self.logy, self.loglog):
if i not in valid_log:
- raise ValueError("Wrong input for log option.")
+ raise ValueError("Valid inputs are boolean, None and 'sym'.")
if self.logx is True or self.loglog is True:
[a.set_xscale('log') for a in axes]
From f7241137fe692c37146745cfaacba0ae188baf87 Mon Sep 17 00:00:00 2001
From: Kaiqi Dong <kaiqi@kth.se>
Date: Tue, 22 Jan 2019 00:23:18 +0100
Subject: [PATCH 44/48] add sym option for logx logy loglog and tests
---
pandas/plotting/_core.py | 14 ++++++++++----
pandas/tests/plotting/test_frame.py | 6 ++++++
2 files changed, 16 insertions(+), 4 deletions(-)
diff --git a/pandas/plotting/_core.py b/pandas/plotting/_core.py
index e543ab88f53b2..ce5966ebc9c34 100644
--- a/pandas/plotting/_core.py
+++ b/pandas/plotting/_core.py
@@ -82,9 +82,9 @@ def _kind(self):
_default_rot = 0
orientation = None
_pop_attributes = ['label', 'style', 'logy', 'logx', 'loglog',
- 'mark_right', 'stacked']
+ 'mark_right', 'stacked', 'sym']
_attr_defaults = {'logy': False, 'logx': False, 'loglog': False,
- 'mark_right': True, 'stacked': False}
+ 'mark_right': True, 'stacked': False, 'sym': False}
def __init__(self, data, kind=None, by=None, subplots=False, sharex=None,
sharey=False, use_index=True,
@@ -309,9 +309,15 @@ def _setup_subplots(self):
axes = _flatten(axes)
if self.logx or self.loglog:
- [a.set_xscale('log') for a in axes]
+ if self.sym:
+ [a.set_xscale('symlog') for a in axes]
+ else:
+ [a.set_xscale('log') for a in axes]
if self.logy or self.loglog:
- [a.set_yscale('log') for a in axes]
+ if self.sym:
+ [a.set_yscale('symlog') for a in axes]
+ else:
+ [a.set_yscale('log') for a in axes]
self.fig = fig
self.axes = axes
diff --git a/pandas/tests/plotting/test_frame.py b/pandas/tests/plotting/test_frame.py
index 98b241f5c8206..93508d1f99d91 100644
--- a/pandas/tests/plotting/test_frame.py
+++ b/pandas/tests/plotting/test_frame.py
@@ -233,12 +233,18 @@ def test_logscales(self):
df = DataFrame({'a': np.arange(100)}, index=np.arange(100))
ax = df.plot(logy=True)
self._check_ax_scales(ax, yaxis='log')
+ ax = df.plot(logy=True, sym=True)
+ self._check_ax_scales(ax, yaxis='symlog')
ax = df.plot(logx=True)
self._check_ax_scales(ax, xaxis='log')
+ ax = df.plot(logx=True, sym=True)
+ self._check_ax_scales(ax, xaxis='symlog')
ax = df.plot(loglog=True)
self._check_ax_scales(ax, xaxis='log', yaxis='log')
+ ax = df.plot(loglog=True, sym=True)
+ self._check_ax_scales(ax, xaxis='symlog', yaxis='symlog')
@pytest.mark.slow
def test_xcompat(self):
From aab92aef385589fc32cfbf03b88bccd181c71567 Mon Sep 17 00:00:00 2001
From: Kaiqi Dong <kaiqi@kth.se>
Date: Tue, 22 Jan 2019 23:04:44 +0100
Subject: [PATCH 45/48] changes based on reviews
---
pandas/plotting/_core.py | 28 ++++++++++++++++------------
pandas/tests/plotting/test_frame.py | 26 +++++++++++++++++++++++---
2 files changed, 39 insertions(+), 15 deletions(-)
diff --git a/pandas/plotting/_core.py b/pandas/plotting/_core.py
index ce5966ebc9c34..08627a9249827 100644
--- a/pandas/plotting/_core.py
+++ b/pandas/plotting/_core.py
@@ -82,9 +82,9 @@ def _kind(self):
_default_rot = 0
orientation = None
_pop_attributes = ['label', 'style', 'logy', 'logx', 'loglog',
- 'mark_right', 'stacked', 'sym']
+ 'mark_right', 'stacked']
_attr_defaults = {'logy': False, 'logx': False, 'loglog': False,
- 'mark_right': True, 'stacked': False, 'sym': False}
+ 'mark_right': True, 'stacked': False}
def __init__(self, data, kind=None, by=None, subplots=False, sharex=None,
sharey=False, use_index=True,
@@ -308,16 +308,20 @@ def _setup_subplots(self):
axes = _flatten(axes)
- if self.logx or self.loglog:
- if self.sym:
- [a.set_xscale('symlog') for a in axes]
- else:
- [a.set_xscale('log') for a in axes]
- if self.logy or self.loglog:
- if self.sym:
- [a.set_yscale('symlog') for a in axes]
- else:
- [a.set_yscale('log') for a in axes]
+ valid_log = [False, True, 'sym']
+ for i in [self.logx, self.logy, self.loglog]:
+ if i not in valid_log:
+ raise ValueError("Wrong input for log option.")
+
+ if self.logx is True or self.loglog is True:
+ [a.set_xscale('log') for a in axes]
+ elif self.logx == 'sym' or self.loglog == 'sym':
+ [a.set_xscale('symlog') for a in axes]
+
+ if self.logy is True or self.loglog is True:
+ [a.set_yscale('log') for a in axes]
+ elif self.logy == 'sym' or self.loglog == 'sym':
+ [a.set_yscale('symlog') for a in axes]
self.fig = fig
self.axes = axes
diff --git a/pandas/tests/plotting/test_frame.py b/pandas/tests/plotting/test_frame.py
index 93508d1f99d91..645abc11ab732 100644
--- a/pandas/tests/plotting/test_frame.py
+++ b/pandas/tests/plotting/test_frame.py
@@ -231,20 +231,40 @@ def test_plot_xy(self):
@pytest.mark.slow
def test_logscales(self):
df = DataFrame({'a': np.arange(100)}, index=np.arange(100))
+
ax = df.plot(logy=True)
self._check_ax_scales(ax, yaxis='log')
- ax = df.plot(logy=True, sym=True)
+ assert ax.get_yscale() == 'log'
+
+ ax = df.plot(logy='sym')
self._check_ax_scales(ax, yaxis='symlog')
+ assert ax.get_yscale() == 'symlog'
ax = df.plot(logx=True)
self._check_ax_scales(ax, xaxis='log')
- ax = df.plot(logx=True, sym=True)
+ assert ax.get_xscale() == 'log'
+
+ ax = df.plot(logx='sym')
self._check_ax_scales(ax, xaxis='symlog')
+ assert ax.get_xscale() == 'symlog'
ax = df.plot(loglog=True)
self._check_ax_scales(ax, xaxis='log', yaxis='log')
- ax = df.plot(loglog=True, sym=True)
+ assert ax.get_xscale() == 'log'
+ assert ax.get_yscale() == 'log'
+
+ ax = df.plot(loglog='sym')
self._check_ax_scales(ax, xaxis='symlog', yaxis='symlog')
+ assert ax.get_xscale() == 'symlog'
+ assert ax.get_yscale() == 'symlog'
+
+ @pytest.mark.parametrize("wrong_input", ["sm", "symlog"])
+ def test_invalid_logscale(self, wrong_input):
+ df = DataFrame({'a': np.arange(100)}, index=np.arange(100))
+
+ msg = "Wrong input for log option."
+ with pytest.raises(ValueError, match=msg):
+ df.plot(logy=wrong_input)
@pytest.mark.slow
def test_xcompat(self):
From c04601a71dec5caeb73a96fadb52826deea31320 Mon Sep 17 00:00:00 2001
From: Kaiqi Dong <kaiqi@kth.se>
Date: Sun, 27 Jan 2019 22:17:43 +0100
Subject: [PATCH 46/48] changes based on reviews
---
pandas/plotting/_core.py | 6 +++---
1 file changed, 3 insertions(+), 3 deletions(-)
diff --git a/pandas/plotting/_core.py b/pandas/plotting/_core.py
index 08627a9249827..12810c73f11f0 100644
--- a/pandas/plotting/_core.py
+++ b/pandas/plotting/_core.py
@@ -308,10 +308,10 @@ def _setup_subplots(self):
axes = _flatten(axes)
- valid_log = [False, True, 'sym']
- for i in [self.logx, self.logy, self.loglog]:
+ valid_log = [False, True, 'sym', None]
+ for i in (self.logx, self.logy, self.loglog):
if i not in valid_log:
- raise ValueError("Wrong input for log option.")
+ raise ValueError("Valid inputs are boolean, None and 'sym'.")
if self.logx is True or self.loglog is True:
[a.set_xscale('log') for a in axes]
From 41b08c83c6c753f00a0d0cd2e17d5181f4702f65 Mon Sep 17 00:00:00 2001
From: Kaiqi Dong <kaiqi@kth.se>
Date: Sun, 27 Jan 2019 22:48:26 +0100
Subject: [PATCH 47/48] add whatsnew
---
doc/source/whatsnew/v0.25.0.rst | 5 +----
1 file changed, 1 insertion(+), 4 deletions(-)
diff --git a/doc/source/whatsnew/v0.25.0.rst b/doc/source/whatsnew/v0.25.0.rst
index 5129449e4fdf3..1bc91fc51c0ba 100644
--- a/doc/source/whatsnew/v0.25.0.rst
+++ b/doc/source/whatsnew/v0.25.0.rst
@@ -18,10 +18,7 @@ including other versions of pandas.
Other Enhancements
^^^^^^^^^^^^^^^^^^
-
--
--
--
+:func:`DataFrame.plot` now can take 'sym' so as to expose symlog scaling.
.. _whatsnew_0250.api_breaking:
From 0bd227f645ea99c740bf15742c9765d5a948bdc2 Mon Sep 17 00:00:00 2001
From: Kaiqi Dong <kaiqi@kth.se>
Date: Sun, 27 Jan 2019 22:58:59 +0100
Subject: [PATCH 48/48] all my changes in a signle change
---
doc/source/whatsnew/v0.25.0.rst | 5 +----
pandas/plotting/_core.py | 14 ++++++++++++--
pandas/tests/plotting/test_frame.py | 26 ++++++++++++++++++++++++++
3 files changed, 39 insertions(+), 6 deletions(-)
diff --git a/doc/source/whatsnew/v0.25.0.rst b/doc/source/whatsnew/v0.25.0.rst
index 5129449e4fdf3..1bc91fc51c0ba 100644
--- a/doc/source/whatsnew/v0.25.0.rst
+++ b/doc/source/whatsnew/v0.25.0.rst
@@ -18,10 +18,7 @@ including other versions of pandas.
Other Enhancements
^^^^^^^^^^^^^^^^^^
-
--
--
--
+:func:`DataFrame.plot` now can take 'sym' so as to expose symlog scaling.
.. _whatsnew_0250.api_breaking:
diff --git a/pandas/plotting/_core.py b/pandas/plotting/_core.py
index e543ab88f53b2..12810c73f11f0 100644
--- a/pandas/plotting/_core.py
+++ b/pandas/plotting/_core.py
@@ -308,10 +308,20 @@ def _setup_subplots(self):
axes = _flatten(axes)
- if self.logx or self.loglog:
+ valid_log = [False, True, 'sym', None]
+ for i in (self.logx, self.logy, self.loglog):
+ if i not in valid_log:
+ raise ValueError("Valid inputs are boolean, None and 'sym'.")
+
+ if self.logx is True or self.loglog is True:
[a.set_xscale('log') for a in axes]
- if self.logy or self.loglog:
+ elif self.logx == 'sym' or self.loglog == 'sym':
+ [a.set_xscale('symlog') for a in axes]
+
+ if self.logy is True or self.loglog is True:
[a.set_yscale('log') for a in axes]
+ elif self.logy == 'sym' or self.loglog == 'sym':
+ [a.set_yscale('symlog') for a in axes]
self.fig = fig
self.axes = axes
diff --git a/pandas/tests/plotting/test_frame.py b/pandas/tests/plotting/test_frame.py
index 98b241f5c8206..645abc11ab732 100644
--- a/pandas/tests/plotting/test_frame.py
+++ b/pandas/tests/plotting/test_frame.py
@@ -231,14 +231,40 @@ def test_plot_xy(self):
@pytest.mark.slow
def test_logscales(self):
df = DataFrame({'a': np.arange(100)}, index=np.arange(100))
+
ax = df.plot(logy=True)
self._check_ax_scales(ax, yaxis='log')
+ assert ax.get_yscale() == 'log'
+
+ ax = df.plot(logy='sym')
+ self._check_ax_scales(ax, yaxis='symlog')
+ assert ax.get_yscale() == 'symlog'
ax = df.plot(logx=True)
self._check_ax_scales(ax, xaxis='log')
+ assert ax.get_xscale() == 'log'
+
+ ax = df.plot(logx='sym')
+ self._check_ax_scales(ax, xaxis='symlog')
+ assert ax.get_xscale() == 'symlog'
ax = df.plot(loglog=True)
self._check_ax_scales(ax, xaxis='log', yaxis='log')
+ assert ax.get_xscale() == 'log'
+ assert ax.get_yscale() == 'log'
+
+ ax = df.plot(loglog='sym')
+ self._check_ax_scales(ax, xaxis='symlog', yaxis='symlog')
+ assert ax.get_xscale() == 'symlog'
+ assert ax.get_yscale() == 'symlog'
+
+ @pytest.mark.parametrize("wrong_input", ["sm", "symlog"])
+ def test_invalid_logscale(self, wrong_input):
+ df = DataFrame({'a': np.arange(100)}, index=np.arange(100))
+
+ msg = "Wrong input for log option."
+ with pytest.raises(ValueError, match=msg):
+ df.plot(logy=wrong_input)
@pytest.mark.slow
def test_xcompat(self):