DOC: further clean-up null/na changes

doc/source/basics.rst

@@ -511,7 +511,7 @@ optional ``level`` parameter which applies only if the object has a
     :header: "Function", "Description"
     :widths: 20, 80
 
-    ``count``, Number of non-na observations
+    ``count``, Number of non-NA observations
     ``sum``, Sum of values
     ``mean``, Mean of values
     ``mad``, Mean absolute deviation
@@ -541,7 +541,7 @@ will exclude NAs on Series input by default:
    np.mean(df['one'].values)
 
 ``Series`` also has a method :meth:`~Series.nunique` which will return the
-number of unique non-na values:
+number of unique non-NA values:
 
 .. ipython:: python
 

doc/source/io.rst

@@ -137,7 +137,6 @@ usecols : array-like or callable, default ``None``
 
   Using this parameter results in much faster parsing time and lower memory usage.
 as_recarray : boolean, default ``False``
-
   .. deprecated:: 0.18.2
 
      Please call ``pd.read_csv(...).to_records()`` instead.
@@ -193,7 +192,6 @@ skiprows : list-like or integer, default ``None``
 skipfooter : int, default ``0``
   Number of lines at bottom of file to skip (unsupported with engine='c').
 skip_footer : int, default ``0``
-
   .. deprecated:: 0.19.0
 
      Use the ``skipfooter`` parameter instead, as they are identical
@@ -208,13 +206,11 @@ low_memory : boolean, default ``True``
   use the ``chunksize`` or ``iterator`` parameter to return the data in chunks.
   (Only valid with C parser)
 buffer_lines : int, default None
-
   .. deprecated:: 0.19.0
 
      Argument removed because its value is not respected by the parser
 
 compact_ints : boolean, default False
-
   .. deprecated:: 0.19.0
 
      Argument moved to ``pd.to_numeric``
@@ -223,7 +219,6 @@ compact_ints : boolean, default False
   parser will attempt to cast it as the smallest integer ``dtype`` possible, either
   signed or unsigned depending on the specification from the ``use_unsigned`` parameter.
 use_unsigned : boolean, default False
-
   .. deprecated:: 0.18.2
 
      Argument moved to ``pd.to_numeric``

doc/source/missing_data.rst

@@ -36,7 +36,7 @@ When / why does data become missing?
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 Some might quibble over our usage of *missing*. By "missing" we simply mean
-**NA** or "not present for whatever reason". Many data sets simply arrive with
+**NA** ("not available") or "not present for whatever reason". Many data sets simply arrive with
 missing data, either because it exists and was not collected or it never
 existed. For example, in a collection of financial time series, some of the time
 series might start on different dates. Thus, values prior to the start date

doc/source/whatsnew/v0.10.0.txt

@@ -128,15 +128,45 @@ labeled the aggregated group with the end of the interval: the next day).
   ``notnull``. That they ever were was a relic of early pandas. This behavior
   can be re-enabled globally by the ``mode.use_inf_as_null`` option:
 
-.. ipython:: python
+.. code-block:: ipython
 
-    s = pd.Series([1.5, np.inf, 3.4, -np.inf])
-	pd.isnull(s)
-    s.fillna(0)
-    pd.set_option('use_inf_as_null', True)
-	pd.isnull(s)
-    s.fillna(0)
-	pd.reset_option('use_inf_as_null')
+    In [6]: s = pd.Series([1.5, np.inf, 3.4, -np.inf])
+
+    In [7]: pd.isnull(s)
+    Out[7]:
+    0    False
+    1    False
+    2    False
+    3    False
+    Length: 4, dtype: bool
+
+    In [8]: s.fillna(0)
+    Out[8]:
+    0    1.500000
+    1         inf
+    2    3.400000
+    3        -inf
+    Length: 4, dtype: float64
+
+    In [9]: pd.set_option('use_inf_as_null', True)
+
+    In [10]: pd.isnull(s)
+    Out[10]:
+    0    False
+    1     True
+    2    False
+    3     True
+    Length: 4, dtype: bool
+
+    In [11]: s.fillna(0)
+    Out[11]:
+    0    1.5
+    1    0.0
+    2    3.4
+    3    0.0
+    Length: 4, dtype: float64
+
+    In [12]: pd.reset_option('use_inf_as_null')
 
 - Methods with the ``inplace`` option now all return ``None`` instead of the
   calling object. E.g. code written like ``df = df.fillna(0, inplace=True)``

doc/source/whatsnew/v0.4.x.txt

@@ -9,7 +9,7 @@ New Features
 - Added Python 3 support using 2to3 (:issue:`200`)
 - :ref:`Added <dsintro.name_attribute>` ``name`` attribute to ``Series``, now
   prints as part of ``Series.__repr__``
-- :ref:`Added <missing.isnull>` instance methods ``isnull`` and ``notnull`` to
+- :ref:`Added <missing.isna>` instance methods ``isnull`` and ``notnull`` to
   Series (:issue:`209`, :issue:`203`)
 - :ref:`Added <basics.align>` ``Series.align`` method for aligning two series
   with choice of join method (ENH56_)

pandas/core/config_init.py

@@ -398,8 +398,8 @@ def table_schema_cb(key):
 
 use_inf_as_na_doc = """
 : boolean
-    True means treat None, NaN, INF, -INF as na (old way),
-    False means None and NaN are null, but INF, -INF are not na
+    True means treat None, NaN, INF, -INF as NA (old way),
+    False means None and NaN are null, but INF, -INF are not NA
     (new way).
 """