From 4417106533d0b12866f50ae4bf5137ade084a81a Mon Sep 17 00:00:00 2001
From: tp <contribute@tensortable.com>
Date: Wed, 8 May 2019 23:54:23 +0200
Subject: [PATCH] CLN: remove compat.lmap
---
pandas/compat/__init__.py | 6 +--
pandas/core/computation/expr.py | 4 +-
pandas/core/frame.py | 9 ++--
pandas/core/internals/construction.py | 4 +-
pandas/core/sparse/frame.py | 3 +-
pandas/core/sparse/scipy_sparse.py | 4 +-
pandas/io/html.py | 4 +-
pandas/io/stata.py | 9 ++--
pandas/plotting/_misc.py | 4 +-
pandas/plotting/_style.py | 6 +--
pandas/tests/frame/test_constructors.py | 4 +-
pandas/tests/frame/test_to_csv.py | 46 +++++++++++--------
pandas/tests/groupby/test_groupby.py | 11 ++---
pandas/tests/indexes/datetimes/test_tools.py | 3 +-
.../tests/indexes/period/test_construction.py | 4 +-
pandas/tests/indexing/test_iloc.py | 4 +-
pandas/tests/io/parser/test_converters.py | 4 +-
pandas/tests/plotting/test_frame.py | 26 +++++------
pandas/tests/plotting/test_misc.py | 12 ++---
pandas/tests/test_compat.py | 10 +---
pandas/util/testing.py | 4 +-
21 files changed, 84 insertions(+), 97 deletions(-)
diff --git a/pandas/compat/__init__.py b/pandas/compat/__init__.py
index 90444efd2ea18..6acd3c65e4bea 100644
--- a/pandas/compat/__init__.py
+++ b/pandas/compat/__init__.py
@@ -5,7 +5,7 @@
Cross-compatible functions for different versions of Python.
Key items to import for compatible code:
-* lists: lrange(), lmap()
+* lists: lrange()
Other items:
* platform checker
@@ -24,10 +24,6 @@ def lrange(*args, **kwargs):
return list(range(*args, **kwargs))
-def lmap(*args, **kwargs):
- return list(map(*args, **kwargs))
-
-
# ----------------------------------------------------------------------------
# functions largely based / taken from the six module
diff --git a/pandas/core/computation/expr.py b/pandas/core/computation/expr.py
index b87ef465459b4..cb9d537e61ebc 100644
--- a/pandas/core/computation/expr.py
+++ b/pandas/core/computation/expr.py
@@ -11,8 +11,6 @@
import numpy as np
-from pandas.compat import lmap
-
import pandas as pd
from pandas.core import common as com
from pandas.core.base import StringMixin
@@ -180,7 +178,7 @@ def _preparse(source, f=_compose(_replace_locals, _replace_booleans,
the ``tokenize`` module and ``tokval`` is a string.
"""
assert callable(f), 'f must be callable'
- return tokenize.untokenize(lmap(f, tokenize_string(source)))
+ return tokenize.untokenize((f(x) for x in tokenize_string(source)))
def _is_type(t):
diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index c27bb743c8126..63daae83916c2 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -31,7 +31,7 @@
from pandas.util._validators import (validate_bool_kwarg,
validate_axis_style_args)
-from pandas.compat import PY36, lmap, raise_with_traceback
+from pandas.compat import PY36, raise_with_traceback
from pandas.compat.numpy import function as nv
from pandas.core.dtypes.cast import (
maybe_upcast,
@@ -1633,7 +1633,7 @@ def to_records(self, index=True, convert_datetime64=None,
else:
if isinstance(self.index, MultiIndex):
# array of tuples to numpy cols. copy copy copy
- ix_vals = lmap(np.array, zip(*self.index.values))
+ ix_vals = list(map(np.array, zip(*self.index.values)))
else:
ix_vals = [self.index.values]
@@ -1650,10 +1650,11 @@ def to_records(self, index=True, convert_datetime64=None,
elif index_names[0] is None:
index_names = ['index']
- names = lmap(str, index_names) + lmap(str, self.columns)
+ names = [str(name) for name in itertools.chain(index_names,
+ self.columns)]
else:
arrays = [self[c].get_values() for c in self.columns]
- names = lmap(str, self.columns)
+ names = [str(c) for c in self.columns]
index_names = []
index_len = len(index_names)
diff --git a/pandas/core/internals/construction.py b/pandas/core/internals/construction.py
index 9c0c5fd4a2a4c..2ee49c30b226d 100644
--- a/pandas/core/internals/construction.py
+++ b/pandas/core/internals/construction.py
@@ -9,7 +9,7 @@
from pandas._libs import lib
from pandas._libs.tslibs import IncompatibleFrequency
-from pandas.compat import lmap, raise_with_traceback
+from pandas.compat import raise_with_traceback
from pandas.core.dtypes.cast import (
construct_1d_arraylike_from_scalar, construct_1d_ndarray_preserving_na,
@@ -413,7 +413,7 @@ def to_arrays(data, columns, coerce_float=False, dtype=None):
return arrays, columns
else:
# last ditch effort
- data = lmap(tuple, data)
+ data = [tuple(x) for x in data]
return _list_to_arrays(data, columns, coerce_float=coerce_float,
dtype=dtype)
diff --git a/pandas/core/sparse/frame.py b/pandas/core/sparse/frame.py
index 22f5df411a2ad..3adeefd6ffd4e 100644
--- a/pandas/core/sparse/frame.py
+++ b/pandas/core/sparse/frame.py
@@ -7,7 +7,6 @@
import numpy as np
from pandas._libs.sparse import BlockIndex, get_blocks
-from pandas.compat import lmap
from pandas.compat.numpy import function as nv
from pandas.util._decorators import Appender
@@ -945,7 +944,7 @@ def applymap(self, func):
-------
applied : DataFrame
"""
- return self.apply(lambda x: lmap(func, x))
+ return self.apply(lambda x: [func(y) for y in x])
def to_manager(sdf, columns, index):
diff --git a/pandas/core/sparse/scipy_sparse.py b/pandas/core/sparse/scipy_sparse.py
index 5a39a1529a33a..40b4452caa8dc 100644
--- a/pandas/core/sparse/scipy_sparse.py
+++ b/pandas/core/sparse/scipy_sparse.py
@@ -5,8 +5,6 @@
"""
from collections import OrderedDict
-from pandas.compat import lmap
-
from pandas.core.index import Index, MultiIndex
from pandas.core.series import Series
@@ -53,7 +51,7 @@ def _get_label_to_i_dict(labels, sort_labels=False):
""" Return OrderedDict of unique labels to number.
Optionally sort by label.
"""
- labels = Index(lmap(tuple, labels)).unique().tolist() # squish
+ labels = Index(map(tuple, labels)).unique().tolist() # squish
if sort_labels:
labels = sorted(list(labels))
d = OrderedDict((k, i) for i, k in enumerate(labels))
diff --git a/pandas/io/html.py b/pandas/io/html.py
index 2ef2ebf80f117..cbdc513cfbbe3 100644
--- a/pandas/io/html.py
+++ b/pandas/io/html.py
@@ -9,7 +9,7 @@
import os
import re
-from pandas.compat import lmap, raise_with_traceback
+from pandas.compat import raise_with_traceback
from pandas.errors import AbstractMethodError, EmptyDataError
from pandas.core.dtypes.common import is_list_like
@@ -764,7 +764,7 @@ def _parse_tfoot_tr(self, table):
def _expand_elements(body):
- lens = Series(lmap(len, body))
+ lens = Series([len(elem) for elem in body])
lens_max = lens.max()
not_max = lens[lens != lens_max]
diff --git a/pandas/io/stata.py b/pandas/io/stata.py
index b4daca6a4dbb9..c59e21678ed1e 100644
--- a/pandas/io/stata.py
+++ b/pandas/io/stata.py
@@ -23,7 +23,6 @@
from pandas._libs.lib import infer_dtype
from pandas._libs.writers import max_len_string_array
-from pandas.compat import lmap
from pandas.util._decorators import Appender, deprecate_kwarg
from pandas.core.dtypes.common import (
@@ -1030,7 +1029,7 @@ def _read_header(self):
if type(x) is int]) > 0
# calculate size of a data record
- self.col_sizes = lmap(lambda x: self._calcsize(x), self.typlist)
+ self.col_sizes = [self._calcsize(typ) for typ in self.typlist]
def _read_new_header(self, first_char):
# The first part of the header is common to 117 and 118.
@@ -1573,9 +1572,9 @@ def read(self, nrows=None, convert_dates=None,
data = self._do_convert_missing(data, convert_missing)
if convert_dates:
- cols = np.where(lmap(lambda x: any(x.startswith(fmt)
- for fmt in _date_formats),
- self.fmtlist))[0]
+ def any_startswith(x: str) -> bool:
+ return any(x.startswith(fmt) for fmt in _date_formats)
+ cols = np.where([any_startswith(x) for x in self.fmtlist])[0]
for i in cols:
col = data.columns[i]
try:
diff --git a/pandas/plotting/_misc.py b/pandas/plotting/_misc.py
index 8d3aa06131126..1a25d2cd133eb 100644
--- a/pandas/plotting/_misc.py
+++ b/pandas/plotting/_misc.py
@@ -1,7 +1,7 @@
# being a bit too dynamic
import numpy as np
-from pandas.compat import lmap, lrange
+from pandas.compat import lrange
from pandas.util._decorators import deprecate_kwarg
from pandas.core.dtypes.missing import notna
@@ -625,7 +625,7 @@ def r(h):
return ((data[:n - h] - mean) *
(data[h:] - mean)).sum() / float(n) / c0
x = np.arange(n) + 1
- y = lmap(r, x)
+ y = [r(loc) for loc in x]
z95 = 1.959963984540054
z99 = 2.5758293035489004
ax.axhline(y=z99 / np.sqrt(n), linestyle='--', color='grey')
diff --git a/pandas/plotting/_style.py b/pandas/plotting/_style.py
index 72b14e721c6df..ba75d05f62131 100644
--- a/pandas/plotting/_style.py
+++ b/pandas/plotting/_style.py
@@ -4,7 +4,7 @@
import numpy as np
-from pandas.compat import lmap, lrange
+from pandas.compat import lrange
from pandas.core.dtypes.common import is_list_like
@@ -20,7 +20,7 @@ def _get_standard_colors(num_colors=None, colormap=None, color_type='default',
colormap = cm.get_cmap(colormap)
if colormap is None:
raise ValueError("Colormap {0} is not recognized".format(cmap))
- colors = lmap(colormap, np.linspace(0, 1, num=num_colors))
+ colors = [colormap(num) for num in np.linspace(0, 1, num=num_colors)]
elif color is not None:
if colormap is not None:
warnings.warn("'color' and 'colormap' cannot be used "
@@ -49,7 +49,7 @@ def random_color(column):
rs = com.random_state(column)
return rs.rand(3).tolist()
- colors = lmap(random_color, lrange(num_colors))
+ colors = [random_color(num) for num in lrange(num_colors)]
else:
raise ValueError("color_type must be either 'default' or 'random'")
diff --git a/pandas/tests/frame/test_constructors.py b/pandas/tests/frame/test_constructors.py
index 0ec533f4d8b50..a6ce2bfb31248 100644
--- a/pandas/tests/frame/test_constructors.py
+++ b/pandas/tests/frame/test_constructors.py
@@ -7,7 +7,7 @@
import numpy.ma as ma
import pytest
-from pandas.compat import PY36, is_platform_little_endian, lmap
+from pandas.compat import PY36, is_platform_little_endian
from pandas.core.dtypes.cast import construct_1d_object_array_from_listlike
from pandas.core.dtypes.common import is_integer_dtype
@@ -2224,7 +2224,7 @@ def __iter__(self):
return iter(self.args)
recs = [Record(1, 2, 3), Record(4, 5, 6), Record(7, 8, 9)]
- tups = lmap(tuple, recs)
+ tups = [tuple(rec) for rec in recs]
result = DataFrame.from_records(recs)
expected = DataFrame.from_records(tups)
diff --git a/pandas/tests/frame/test_to_csv.py b/pandas/tests/frame/test_to_csv.py
index 20cd8c9dc744a..012441d8a66b7 100644
--- a/pandas/tests/frame/test_to_csv.py
+++ b/pandas/tests/frame/test_to_csv.py
@@ -5,7 +5,6 @@
import numpy as np
import pytest
-from pandas.compat import lmap
from pandas.errors import ParserError
import pandas as pd
@@ -120,8 +119,8 @@ def test_to_csv_from_csv3(self):
df2.to_csv(path, mode='a', header=False)
xp = pd.concat([df1, df2])
rs = pd.read_csv(path, index_col=0)
- rs.columns = lmap(int, rs.columns)
- xp.columns = lmap(int, xp.columns)
+ rs.columns = [int(label) for label in rs.columns]
+ xp.columns = [int(label) for label in xp.columns]
assert_frame_equal(xp, rs)
def test_to_csv_from_csv4(self):
@@ -292,19 +291,24 @@ def _to_uni(x):
if r_dtype:
if r_dtype == 'u': # unicode
r_dtype = 'O'
- recons.index = np.array(lmap(_to_uni, recons.index),
- dtype=r_dtype)
- df.index = np.array(lmap(_to_uni, df.index), dtype=r_dtype)
+ recons.index = np.array(
+ [_to_uni(label) for label in recons.index],
+ dtype=r_dtype)
+ df.index = np.array(
+ [_to_uni(label) for label in df.index], dtype=r_dtype)
elif r_dtype == 'dt': # unicode
r_dtype = 'O'
- recons.index = np.array(lmap(Timestamp, recons.index),
- dtype=r_dtype)
+ recons.index = np.array(
+ [Timestamp(label) for label in recons.index],
+ dtype=r_dtype)
df.index = np.array(
- lmap(Timestamp, df.index), dtype=r_dtype)
+ [Timestamp(label) for label in df.index],
+ dtype=r_dtype)
elif r_dtype == 'p':
r_dtype = 'O'
+ idx_list = to_datetime(recons.index)
recons.index = np.array(
- list(map(Timestamp, to_datetime(recons.index))),
+ [Timestamp(label) for label in idx_list],
dtype=r_dtype)
df.index = np.array(
list(map(Timestamp, df.index.to_timestamp())),
@@ -316,23 +320,29 @@ def _to_uni(x):
if c_dtype:
if c_dtype == 'u':
c_dtype = 'O'
- recons.columns = np.array(lmap(_to_uni, recons.columns),
- dtype=c_dtype)
+ recons.columns = np.array(
+ [_to_uni(label) for label in recons.columns],
+ dtype=c_dtype)
df.columns = np.array(
- lmap(_to_uni, df.columns), dtype=c_dtype)
+ [_to_uni(label) for label in df.columns],
+ dtype=c_dtype)
elif c_dtype == 'dt':
c_dtype = 'O'
- recons.columns = np.array(lmap(Timestamp, recons.columns),
- dtype=c_dtype)
+ recons.columns = np.array(
+ [Timestamp(label) for label in recons.columns],
+ dtype=c_dtype)
df.columns = np.array(
- lmap(Timestamp, df.columns), dtype=c_dtype)
+ [Timestamp(label) for label in df.columns],
+ dtype=c_dtype)
elif c_dtype == 'p':
c_dtype = 'O'
+ col_list = to_datetime(recons.columns)
recons.columns = np.array(
- lmap(Timestamp, to_datetime(recons.columns)),
+ [Timestamp(label) for label in col_list],
dtype=c_dtype)
+ col_list = df.columns.to_timestamp()
df.columns = np.array(
- lmap(Timestamp, df.columns.to_timestamp()),
+ [Timestamp(label) for label in col_list],
dtype=c_dtype)
else:
c_dtype = type_map.get(c_dtype)
diff --git a/pandas/tests/groupby/test_groupby.py b/pandas/tests/groupby/test_groupby.py
index 31065cbb6f69a..c9df40504cc3b 100644
--- a/pandas/tests/groupby/test_groupby.py
+++ b/pandas/tests/groupby/test_groupby.py
@@ -6,7 +6,6 @@
import numpy as np
import pytest
-from pandas.compat import lmap
from pandas.errors import PerformanceWarning
import pandas as pd
@@ -874,7 +873,7 @@ def test_mutate_groups():
'cat1': ['a'] * 8 + ['b'] * 6,
'cat2': ['c'] * 2 + ['d'] * 2 + ['e'] * 2 + ['f'] * 2 + ['c'] * 2 +
['d'] * 2 + ['e'] * 2,
- 'cat3': lmap(lambda x: 'g%s' % x, range(1, 15)),
+ 'cat3': ['g{}'.format(x) for x in range(1, 15)],
'val': np.random.randint(100, size=14),
})
@@ -1248,17 +1247,17 @@ def test_groupby_sort_multi():
'c': [0, 1, 2],
'd': np.random.randn(3)})
- tups = lmap(tuple, df[['a', 'b', 'c']].values)
+ tups = [tuple(row) for row in df[['a', 'b', 'c']].values]
tups = com.asarray_tuplesafe(tups)
result = df.groupby(['a', 'b', 'c'], sort=True).sum()
tm.assert_numpy_array_equal(result.index.values, tups[[1, 2, 0]])
- tups = lmap(tuple, df[['c', 'a', 'b']].values)
+ tups = [tuple(row) for row in df[['c', 'a', 'b']].values]
tups = com.asarray_tuplesafe(tups)
result = df.groupby(['c', 'a', 'b'], sort=True).sum()
tm.assert_numpy_array_equal(result.index.values, tups)
- tups = lmap(tuple, df[['b', 'c', 'a']].values)
+ tups = [tuple(x) for x in df[['b', 'c', 'a']].values]
tups = com.asarray_tuplesafe(tups)
result = df.groupby(['b', 'c', 'a'], sort=True).sum()
tm.assert_numpy_array_equal(result.index.values, tups[[2, 1, 0]])
@@ -1270,7 +1269,7 @@ def test_groupby_sort_multi():
result = grouped.sum()
def _check_groupby(df, result, keys, field, f=lambda x: x.sum()):
- tups = lmap(tuple, df[keys].values)
+ tups = [tuple(row) for row in df[keys].values]
tups = com.asarray_tuplesafe(tups)
expected = f(df.groupby(tups)[field])
for k, v in expected.items():
diff --git a/pandas/tests/indexes/datetimes/test_tools.py b/pandas/tests/indexes/datetimes/test_tools.py
index 5bad5d415f5f7..d0f551f55f5ad 100644
--- a/pandas/tests/indexes/datetimes/test_tools.py
+++ b/pandas/tests/indexes/datetimes/test_tools.py
@@ -14,7 +14,6 @@
from pandas._libs import tslib
from pandas._libs.tslibs import iNaT, parsing
-from pandas.compat import lmap
from pandas.errors import OutOfBoundsDatetime
import pandas.util._test_decorators as td
@@ -1264,7 +1263,7 @@ def test_to_datetime_types(self, cache):
# array = ['2012','20120101','20120101 12:01:01']
array = ['20120101', '20120101 12:01:01']
expected = list(to_datetime(array, cache=cache))
- result = lmap(Timestamp, array)
+ result = [Timestamp(date_str) for date_str in array]
tm.assert_almost_equal(result, expected)
# currently fails ###
diff --git a/pandas/tests/indexes/period/test_construction.py b/pandas/tests/indexes/period/test_construction.py
index 1c3125571a27d..a017fc693e1de 100644
--- a/pandas/tests/indexes/period/test_construction.py
+++ b/pandas/tests/indexes/period/test_construction.py
@@ -2,7 +2,7 @@
import pytest
from pandas._libs.tslibs.period import IncompatibleFrequency
-from pandas.compat import lmap, lrange
+from pandas.compat import lrange
from pandas.core.dtypes.dtypes import PeriodDtype
@@ -514,7 +514,7 @@ def test_map_with_string_constructor(self):
raw = [2005, 2007, 2009]
index = PeriodIndex(raw, freq='A')
- expected = Index(lmap(str, raw))
+ expected = Index([str(num) for num in raw])
res = index.map(str)
# should return an Index
diff --git a/pandas/tests/indexing/test_iloc.py b/pandas/tests/indexing/test_iloc.py
index 27f62af8394ef..88d20b8f68173 100644
--- a/pandas/tests/indexing/test_iloc.py
+++ b/pandas/tests/indexing/test_iloc.py
@@ -5,7 +5,7 @@
import numpy as np
import pytest
-from pandas.compat import lmap, lrange
+from pandas.compat import lrange
import pandas as pd
from pandas import DataFrame, Series, concat, date_range, isna
@@ -603,7 +603,7 @@ def test_iloc_mask(self):
# the possibilities
locs = np.arange(4)
nums = 2 ** locs
- reps = lmap(bin, nums)
+ reps = [bin(num) for num in nums]
df = DataFrame({'locs': locs, 'nums': nums}, reps)
expected = {
diff --git a/pandas/tests/io/parser/test_converters.py b/pandas/tests/io/parser/test_converters.py
index bb67367cd3210..4df99d396b7ac 100644
--- a/pandas/tests/io/parser/test_converters.py
+++ b/pandas/tests/io/parser/test_converters.py
@@ -8,8 +8,6 @@
import numpy as np
import pytest
-from pandas.compat import lmap
-
import pandas as pd
from pandas import DataFrame, Index
import pandas.util.testing as tm
@@ -126,7 +124,7 @@ def convert_score(x):
return np.nan
if x.find("-") > 0:
- val_min, val_max = lmap(int, x.split("-"))
+ val_min, val_max = map(int, x.split("-"))
val = 0.5 * (val_min + val_max)
else:
val = float(x)
diff --git a/pandas/tests/plotting/test_frame.py b/pandas/tests/plotting/test_frame.py
index 3bb49baf78c3a..bae386a98b988 100644
--- a/pandas/tests/plotting/test_frame.py
+++ b/pandas/tests/plotting/test_frame.py
@@ -10,7 +10,7 @@
from numpy.random import rand, randn
import pytest
-from pandas.compat import lmap, lrange
+from pandas.compat import lrange
import pandas.util._test_decorators as td
from pandas.core.dtypes.api import is_list_like
@@ -897,13 +897,13 @@ def test_bar_colors(self):
from matplotlib import cm
# Test str -> colormap functionality
ax = df.plot.bar(colormap='jet')
- rgba_colors = lmap(cm.jet, np.linspace(0, 1, 5))
+ rgba_colors = [cm.jet(n) for n in np.linspace(0, 1, 5)]
self._check_colors(ax.patches[::5], facecolors=rgba_colors)
tm.close()
# Test colormap functionality
ax = df.plot.bar(colormap=cm.jet)
- rgba_colors = lmap(cm.jet, np.linspace(0, 1, 5))
+ rgba_colors = [cm.jet(n) for n in np.linspace(0, 1, 5)]
self._check_colors(ax.patches[::5], facecolors=rgba_colors)
tm.close()
@@ -1853,12 +1853,12 @@ def test_line_colors(self):
tm.close()
ax = df.plot(colormap='jet')
- rgba_colors = lmap(cm.jet, np.linspace(0, 1, len(df)))
+ rgba_colors = [cm.jet(n) for n in np.linspace(0, 1, len(df))]
self._check_colors(ax.get_lines(), linecolors=rgba_colors)
tm.close()
ax = df.plot(colormap=cm.jet)
- rgba_colors = lmap(cm.jet, np.linspace(0, 1, len(df)))
+ rgba_colors = [cm.jet(n) for n in np.linspace(0, 1, len(df))]
self._check_colors(ax.get_lines(), linecolors=rgba_colors)
tm.close()
@@ -1941,7 +1941,7 @@ def test_line_colors_and_styles_subplots(self):
with tm.assert_produces_warning(UserWarning):
_check_plot_works(df.plot, color=custom_colors, subplots=True)
- rgba_colors = lmap(cm.jet, np.linspace(0, 1, len(df)))
+ rgba_colors = [cm.jet(n) for n in np.linspace(0, 1, len(df))]
for cmap in ['jet', cm.jet]:
axes = df.plot(colormap=cmap, subplots=True)
for ax, c in zip(axes, rgba_colors):
@@ -1987,7 +1987,7 @@ def test_area_colors(self):
tm.close()
ax = df.plot.area(colormap='jet')
- jet_colors = lmap(cm.jet, np.linspace(0, 1, len(df)))
+ jet_colors = [cm.jet(n) for n in np.linspace(0, 1, len(df))]
self._check_colors(ax.get_lines(), linecolors=jet_colors)
poly = [o for o in ax.get_children() if isinstance(o, PolyCollection)]
self._check_colors(poly, facecolors=jet_colors)
@@ -2028,13 +2028,13 @@ def test_hist_colors(self):
from matplotlib import cm
# Test str -> colormap functionality
ax = df.plot.hist(colormap='jet')
- rgba_colors = lmap(cm.jet, np.linspace(0, 1, 5))
+ rgba_colors = [cm.jet(n) for n in np.linspace(0, 1, 5)]
self._check_colors(ax.patches[::10], facecolors=rgba_colors)
tm.close()
# Test colormap functionality
ax = df.plot.hist(colormap=cm.jet)
- rgba_colors = lmap(cm.jet, np.linspace(0, 1, 5))
+ rgba_colors = [cm.jet(n) for n in np.linspace(0, 1, 5)]
self._check_colors(ax.patches[::10], facecolors=rgba_colors)
tm.close()
@@ -2058,12 +2058,12 @@ def test_kde_colors(self):
tm.close()
ax = df.plot.kde(colormap='jet')
- rgba_colors = lmap(cm.jet, np.linspace(0, 1, len(df)))
+ rgba_colors = [cm.jet(n) for n in np.linspace(0, 1, len(df))]
self._check_colors(ax.get_lines(), linecolors=rgba_colors)
tm.close()
ax = df.plot.kde(colormap=cm.jet)
- rgba_colors = lmap(cm.jet, np.linspace(0, 1, len(df)))
+ rgba_colors = [cm.jet(n) for n in np.linspace(0, 1, len(df))]
self._check_colors(ax.get_lines(), linecolors=rgba_colors)
@pytest.mark.slow
@@ -2097,7 +2097,7 @@ def test_kde_colors_and_styles_subplots(self):
self._check_colors(ax.get_lines(), linecolors=[c])
tm.close()
- rgba_colors = lmap(cm.jet, np.linspace(0, 1, len(df)))
+ rgba_colors = [cm.jet(n) for n in np.linspace(0, 1, len(df))]
for cmap in ['jet', cm.jet]:
axes = df.plot(kind='kde', colormap=cmap, subplots=True)
for ax, c in zip(axes, rgba_colors):
@@ -2165,7 +2165,7 @@ def _check_colors(bp, box_c, whiskers_c, medians_c, caps_c='k',
from matplotlib import cm
# Test str -> colormap functionality
bp = df.plot.box(colormap='jet', return_type='dict')
- jet_colors = lmap(cm.jet, np.linspace(0, 1, 3))
+ jet_colors = [cm.jet(n) for n in np.linspace(0, 1, 3)]
_check_colors(bp, jet_colors[0], jet_colors[0], jet_colors[2])
tm.close()
diff --git a/pandas/tests/plotting/test_misc.py b/pandas/tests/plotting/test_misc.py
index a184c024f4459..5ffbe9ec8fd47 100644
--- a/pandas/tests/plotting/test_misc.py
+++ b/pandas/tests/plotting/test_misc.py
@@ -7,7 +7,6 @@
from numpy.random import randn
import pytest
-from pandas.compat import lmap
import pandas.util._test_decorators as td
from pandas import DataFrame
@@ -115,7 +114,7 @@ def test_andrews_curves(self, iris):
ax = _check_plot_works(andrews_curves, frame=df,
class_column='Name', colormap=cm.jet)
- cmaps = lmap(cm.jet, np.linspace(0, 1, df['Name'].nunique()))
+ cmaps = [cm.jet(n) for n in np.linspace(0, 1, df['Name'].nunique())]
self._check_colors(
ax.get_lines()[:10], linecolors=cmaps, mapping=df['Name'][:10])
@@ -141,7 +140,7 @@ def test_andrews_curves(self, iris):
ax = _check_plot_works(andrews_curves, frame=df,
class_column='Name', colormap=cm.jet)
- cmaps = lmap(cm.jet, np.linspace(0, 1, df['Name'].nunique()))
+ cmaps = [cm.jet(n) for n in np.linspace(0, 1, df['Name'].nunique())]
self._check_colors(
ax.get_lines()[:10], linecolors=cmaps, mapping=df['Name'][:10])
@@ -183,7 +182,7 @@ def test_parallel_coordinates(self, iris):
ax = _check_plot_works(parallel_coordinates,
frame=df, class_column='Name', colormap=cm.jet)
- cmaps = lmap(cm.jet, np.linspace(0, 1, df['Name'].nunique()))
+ cmaps = [cm.jet(n) for n in np.linspace(0, 1, df['Name'].nunique())]
self._check_colors(
ax.get_lines()[:10], linecolors=cmaps, mapping=df['Name'][:10])
@@ -250,7 +249,7 @@ def test_radviz(self, iris):
_check_plot_works(radviz, frame=df,
class_column='Name', colormap=cm.jet)
- cmaps = lmap(cm.jet, np.linspace(0, 1, df['Name'].nunique()))
+ cmaps = [cm.jet(n) for n in np.linspace(0, 1, df['Name'].nunique())]
patches = [p for p in ax.patches[:20] if p.get_label() != '']
self._check_colors(patches, facecolors=cmaps, mapping=df['Name'][:10])
@@ -337,8 +336,7 @@ def test_plot_single_color(self):
'rank': [52, 525, 32],
})
ax = df.client.value_counts().plot.bar()
- colors = lmap(lambda rect: rect.get_facecolor(),
- ax.get_children()[0:3])
+ colors = [rect.get_facecolor() for rect in ax.get_children()[0:3]]
assert all(color == colors[0] for color in colors)
def test_get_standard_colors_no_appending(self):
diff --git a/pandas/tests/test_compat.py b/pandas/tests/test_compat.py
index 1add28c1f56ab..478cb87b8ab68 100644
--- a/pandas/tests/test_compat.py
+++ b/pandas/tests/test_compat.py
@@ -3,7 +3,7 @@
"""
import builtins
-from pandas.compat import lmap, lrange
+from pandas.compat import lrange
class TestBuiltinIterators:
@@ -24,11 +24,3 @@ def test_lrange(self):
lengths += 5,
expecteds += list(builtins.range(1, 10, 2)),
self.check_results(results, expecteds, lengths)
-
- def test_lmap(self):
- func = lambda x, y, z: x + y + z
- lst = [builtins.range(10), builtins.range(10), builtins.range(10)]
- results = lmap(func, *lst),
- expecteds = list(builtins.map(func, *lst)),
- lengths = 10,
- self.check_results(results, expecteds, lengths)
diff --git a/pandas/util/testing.py b/pandas/util/testing.py
index b7fa15984f294..9084ebc736599 100644
--- a/pandas/util/testing.py
+++ b/pandas/util/testing.py
@@ -22,7 +22,7 @@
can_set_locale, get_locales, set_locale)
from pandas._libs import testing as _testing
-from pandas.compat import lmap, raise_with_traceback
+from pandas.compat import raise_with_traceback
from pandas.core.dtypes.common import (
is_bool, is_categorical_dtype, is_datetime64_dtype, is_datetime64tz_dtype,
@@ -1815,7 +1815,7 @@ def makeCustomIndex(nentries, nlevels, prefix='#', names=False, ndupe_l=None,
def keyfunc(x):
import re
numeric_tuple = re.sub(r"[^\d_]_?", "", x).split("_")
- return lmap(int, numeric_tuple)
+ return [int(num) for num in numeric_tuple]
# build a list of lists to create the index from
div_factor = nentries // ndupe_l[i] + 1