DOC: fix doc build warnings

Author: Jeff Reback <[email protected]>

Closes #12545 from jreback/docs and squashes the following commits:

54919a4 [Jeff Reback] DOC: fix doc build warnings

Author: jreback

doc/source/basics.rst

@@ -370,6 +370,7 @@ be broadcast:
 or it can return False if broadcasting can not be done:
 
 .. ipython:: python
+   :okwarning:
 
     np.array([1, 2, 3]) == np.array([1, 2])
 
@@ -1757,7 +1758,7 @@ but occasionally has non-dates intermixed and you want to represent as missing.
                  'foo', 1.0, 1, pd.Timestamp('20010104'),
                  '20010105'], dtype='O')
    s
-   s.convert_objects(convert_dates='coerce')
+   pd.to_datetime(s, errors='coerce')
 
 In addition, :meth:`~DataFrame.convert_objects` will attempt the *soft* conversion of any *object* dtypes, meaning that if all
 the objects in a Series are of the same type, the Series will have that dtype.

doc/source/enhancingperf.rst

@@ -98,6 +98,7 @@ First we're going to need to import the cython magic function to ipython (for
 cython versions >=0.21 you can use ``%load_ext Cython``):
 
 .. ipython:: python
+   :okwarning:
 
    %load_ext cythonmagic
 

doc/source/indexing.rst

@@ -1625,6 +1625,7 @@ This is the correct access method
 This *can* work at times, but is not guaranteed, and so should be avoided
 
 .. ipython:: python
+   :okwarning:
 
    dfc = dfc.copy()
    dfc['A'][0] = 111

doc/source/options.rst

@@ -107,6 +107,7 @@ All options also have a default value, and you can use ``reset_option`` to do ju
 It's also possible to reset multiple options at once (using a regex):
 
 .. ipython:: python
+   :okwarning:
 
    pd.reset_option("^display")
 
@@ -499,5 +500,3 @@ Enabling ``display.unicode.ambiguous_as_wide`` lets pandas to figure these chara
 
    pd.set_option('display.unicode.east_asian_width', False)
    pd.set_option('display.unicode.ambiguous_as_wide', False)
-
-

doc/source/r_interface.rst

@@ -136,6 +136,7 @@ DataFrames into the equivalent R object (that is, **data.frame**):
 
 .. ipython:: python
 
+   import pandas.rpy.common as com
    df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6], 'C':[7,8,9]},
                      index=["one", "two", "three"])
    r_dataframe = com.convert_to_r_dataframe(df)
@@ -154,6 +155,7 @@ R matrices bear no information on the data type):
 
 .. ipython:: python
 
+   import pandas.rpy.common as com
    r_matrix = com.convert_to_r_matrix(df)
 
    print(type(r_matrix))

doc/source/text.rst

@@ -9,7 +9,7 @@
    randn = np.random.randn
    np.set_printoptions(precision=4, suppress=True)
    from pandas.compat import lrange
-   options.display.max_rows=15
+   pd.options.display.max_rows=15
 
 ======================
 Working with Text Data
@@ -375,53 +375,54 @@ Method Summary
 .. csv-table::
     :header: "Method", "Description"
     :widths: 20, 80
-
-    :meth:`~Series.str.cat`,Concatenate strings
-    :meth:`~Series.str.split`,Split strings on delimiter
-    :meth:`~Series.str.rsplit`,Split strings on delimiter working from the end of the string
-    :meth:`~Series.str.get`,Index into each element (retrieve i-th element)
-    :meth:`~Series.str.join`,Join strings in each element of the Series with passed separator
-    :meth:`~Series.str.get_dummies`,Split strings on delimiter, returning DataFrame of dummy variables
-    :meth:`~Series.str.contains`,Return boolean array if each string contains pattern/regex
-    :meth:`~Series.str.replace`,Replace occurrences of pattern/regex with some other string
-    :meth:`~Series.str.repeat`,Duplicate values (``s.str.repeat(3)`` equivalent to ``x * 3``)
-    :meth:`~Series.str.pad`,"Add whitespace to left, right, or both sides of strings"
-    :meth:`~Series.str.center`,Equivalent to ``str.center``
-    :meth:`~Series.str.ljust`,Equivalent to ``str.ljust``
-    :meth:`~Series.str.rjust`,Equivalent to ``str.rjust``
-    :meth:`~Series.str.zfill`,Equivalent to ``str.zfill``
-    :meth:`~Series.str.wrap`,Split long strings into lines with length less than a given width
-    :meth:`~Series.str.slice`,Slice each string in the Series
-    :meth:`~Series.str.slice_replace`,Replace slice in each string with passed value
-    :meth:`~Series.str.count`,Count occurrences of pattern
-    :meth:`~Series.str.startswith`,Equivalent to ``str.startswith(pat)`` for each element
-    :meth:`~Series.str.endswith`,Equivalent to ``str.endswith(pat)`` for each element
-    :meth:`~Series.str.findall`,Compute list of all occurrences of pattern/regex for each string
-    :meth:`~Series.str.match`,"Call ``re.match`` on each element, returning matched groups as list"
-    :meth:`~Series.str.extract`,"Call ``re.search`` on each element, returning DataFrame with one row for each element and one column for each regex capture group"
-    :meth:`~Series.str.extractall`,"Call ``re.findall`` on each element, returning DataFrame with one row for each match and one column for each regex capture group"
-    :meth:`~Series.str.len`,Compute string lengths
-    :meth:`~Series.str.strip`,Equivalent to ``str.strip``
-    :meth:`~Series.str.rstrip`,Equivalent to ``str.rstrip``
-    :meth:`~Series.str.lstrip`,Equivalent to ``str.lstrip``
-    :meth:`~Series.str.partition`,Equivalent to ``str.partition``
-    :meth:`~Series.str.rpartition`,Equivalent to ``str.rpartition``
-    :meth:`~Series.str.lower`,Equivalent to ``str.lower``
-    :meth:`~Series.str.upper`,Equivalent to ``str.upper``
-    :meth:`~Series.str.find`,Equivalent to ``str.find``
-    :meth:`~Series.str.rfind`,Equivalent to ``str.rfind``
-    :meth:`~Series.str.index`,Equivalent to ``str.index``
-    :meth:`~Series.str.rindex`,Equivalent to ``str.rindex``
-    :meth:`~Series.str.capitalize`,Equivalent to ``str.capitalize``
-    :meth:`~Series.str.swapcase`,Equivalent to ``str.swapcase``
-    :meth:`~Series.str.normalize`,Return Unicode normal form. Equivalent to ``unicodedata.normalize``
-    :meth:`~Series.str.translate`,Equivalent to ``str.translate``
-    :meth:`~Series.str.isalnum`,Equivalent to ``str.isalnum``
-    :meth:`~Series.str.isalpha`,Equivalent to ``str.isalpha``
-    :meth:`~Series.str.isdigit`,Equivalent to ``str.isdigit``
-    :meth:`~Series.str.isspace`,Equivalent to ``str.isspace``
-    :meth:`~Series.str.islower`,Equivalent to ``str.islower``
-    :meth:`~Series.str.isupper`,Equivalent to ``str.isupper``
-    :meth:`~Series.str.istitle`,Equivalent to ``str.istitle``
-    :meth:`~Series.str.isnumeric`,Equivalent to ``str.isnumeric``
-    :meth:`~Series.str.isdecimal`,Equivalent to ``str.isdecimal``
+    :delim: ;
+
+    :meth:`~Series.str.cat`;Concatenate strings
+    :meth:`~Series.str.split`;Split strings on delimiter
+    :meth:`~Series.str.rsplit`;Split strings on delimiter working from the end of the string
+    :meth:`~Series.str.get`;Index into each element (retrieve i-th element)
+    :meth:`~Series.str.join`;Join strings in each element of the Series with passed separator
+    :meth:`~Series.str.get_dummies`;Split strings on the delimiter returning DataFrame of dummy variables
+    :meth:`~Series.str.contains`;Return boolean array if each string contains pattern/regex
+    :meth:`~Series.str.replace`;Replace occurrences of pattern/regex with some other string
+    :meth:`~Series.str.repeat`;Duplicate values (``s.str.repeat(3)`` equivalent to ``x * 3``)
+    :meth:`~Series.str.pad`;"Add whitespace to left, right, or both sides of strings"
+    :meth:`~Series.str.center`;Equivalent to ``str.center``
+    :meth:`~Series.str.ljust`;Equivalent to ``str.ljust``
+    :meth:`~Series.str.rjust`;Equivalent to ``str.rjust``
+    :meth:`~Series.str.zfill`;Equivalent to ``str.zfill``
+    :meth:`~Series.str.wrap`;Split long strings into lines with length less than a given width
+    :meth:`~Series.str.slice`;Slice each string in the Series
+    :meth:`~Series.str.slice_replace`;Replace slice in each string with passed value
+    :meth:`~Series.str.count`;Count occurrences of pattern
+    :meth:`~Series.str.startswith`;Equivalent to ``str.startswith(pat)`` for each element
+    :meth:`~Series.str.endswith`;Equivalent to ``str.endswith(pat)`` for each element
+    :meth:`~Series.str.findall`;Compute list of all occurrences of pattern/regex for each string
+    :meth:`~Series.str.match`;"Call ``re.match`` on each element, returning matched groups as list"
+    :meth:`~Series.str.extract`;"Call ``re.search`` on each element, returning DataFrame with one row for each element and one column for each regex capture group"
+    :meth:`~Series.str.extractall`;"Call ``re.findall`` on each element, returning DataFrame with one row for each match and one column for each regex capture group"
+    :meth:`~Series.str.len`;Compute string lengths
+    :meth:`~Series.str.strip`;Equivalent to ``str.strip``
+    :meth:`~Series.str.rstrip`;Equivalent to ``str.rstrip``
+    :meth:`~Series.str.lstrip`;Equivalent to ``str.lstrip``
+    :meth:`~Series.str.partition`;Equivalent to ``str.partition``
+    :meth:`~Series.str.rpartition`;Equivalent to ``str.rpartition``
+    :meth:`~Series.str.lower`;Equivalent to ``str.lower``
+    :meth:`~Series.str.upper`;Equivalent to ``str.upper``
+    :meth:`~Series.str.find`;Equivalent to ``str.find``
+    :meth:`~Series.str.rfind`;Equivalent to ``str.rfind``
+    :meth:`~Series.str.index`;Equivalent to ``str.index``
+    :meth:`~Series.str.rindex`;Equivalent to ``str.rindex``
+    :meth:`~Series.str.capitalize`;Equivalent to ``str.capitalize``
+    :meth:`~Series.str.swapcase`;Equivalent to ``str.swapcase``
+    :meth:`~Series.str.normalize`;Return Unicode normal form. Equivalent to ``unicodedata.normalize``
+    :meth:`~Series.str.translate`;Equivalent to ``str.translate``
+    :meth:`~Series.str.isalnum`;Equivalent to ``str.isalnum``
+    :meth:`~Series.str.isalpha`;Equivalent to ``str.isalpha``
+    :meth:`~Series.str.isdigit`;Equivalent to ``str.isdigit``
+    :meth:`~Series.str.isspace`;Equivalent to ``str.isspace``
+    :meth:`~Series.str.islower`;Equivalent to ``str.islower``
+    :meth:`~Series.str.isupper`;Equivalent to ``str.isupper``
+    :meth:`~Series.str.istitle`;Equivalent to ``str.istitle``
+    :meth:`~Series.str.isnumeric`;Equivalent to ``str.isnumeric``
+    :meth:`~Series.str.isdecimal`;Equivalent to ``str.isdecimal``

doc/source/whatsnew/v0.10.0.txt

@@ -292,6 +292,7 @@ Updated PyTables Support
    store.select('df')
 
 .. ipython:: python
+   :okwarning:
 
    wp = Panel(randn(2, 5, 4), items=['Item1', 'Item2'],
           major_axis=date_range('1/1/2000', periods=5),

doc/source/whatsnew/v0.15.0.txt

@@ -420,7 +420,7 @@ Rolling/Expanding Moments improvements
 
   New behavior
 
-  .. ipython:: python
+  .. code-block:: python
 
      In [10]: pd.rolling_window(s, window=3, win_type='triang', center=True)
      Out[10]:

doc/source/whatsnew/v0.15.1.txt

@@ -110,19 +110,18 @@ API changes
 
   .. code-block:: python
 
-    In [8]: s.loc[3.5:1.5]
-    KeyError: 3.5
+     In [8]: s.loc[3.5:1.5]
+     KeyError: 3.5
 
   current behavior:
 
   .. ipython:: python
 
-    s.loc[3.5:1.5]
-
+     s.loc[3.5:1.5]
 
 - ``io.data.Options`` has been fixed for a change in the format of the Yahoo Options page (:issue:`8612`), (:issue:`8741`)
 
-  .. note:: 
+  .. note::
 
     As a result of a change in Yahoo's option page layout, when an expiry date is given,
     ``Options`` methods now return data for a single expiry date.  Previously, methods returned all
@@ -146,6 +145,7 @@ API changes
   Current behavior:
 
   .. ipython:: python
+     :okwarning:
 
      from pandas.io.data import Options
      aapl = Options('aapl','yahoo')
@@ -274,4 +274,3 @@ Bug Fixes
 - Bug in Setting by indexer to a scalar value with a mixed-dtype `Panel4d` was failing (:issue:`8702`)
 - Bug where ``DataReader``'s would fail if one of the symbols passed was invalid.  Now returns data for valid symbols and np.nan for invalid (:issue:`8494`)
 - Bug in ``get_quote_yahoo`` that wouldn't allow non-float return values (:issue:`5229`).
-

doc/source/whatsnew/v0.17.0.txt

@@ -723,6 +723,7 @@ be broadcast:
 or it can return False if broadcasting can not be done:
 
 .. ipython:: python
+   :okwarning:
 
    np.array([1, 2, 3]) == np.array([1, 2])
 

doc/source/whatsnew/v0.18.0.txt

@@ -192,6 +192,7 @@ In v0.18.0, the ``expand`` argument was added to
 Currently the default is ``expand=None`` which gives a ``FutureWarning`` and uses ``expand=False``. To avoid this warning, please explicitly specify ``expand``.
 
 .. ipython:: python
+   :okwarning:
 
    pd.Series(['a1', 'b2', 'c3']).str.extract('[ab](\d)', expand=None)
 
@@ -608,26 +609,25 @@ Changes to msgpack
 
 Forward incompatible changes in ``msgpack`` writing format were made over 0.17.0 and 0.18.0; older versions of pandas cannot read files packed by newer versions (:issue:`12129`, `10527`)
 
-Bug in ``to_msgpack`` and ``read_msgpack`` introduced in 0.17.0 and fixed in 0.18.0, caused files packed in Python 2 unreadable by Python 3 (:issue:`12142`)
+Bug in ``to_msgpack`` and ``read_msgpack`` introduced in 0.17.0 and fixed in 0.18.0, caused files packed in Python 2 unreadable by Python 3 (:issue:`12142`). The following table describes the backward and forward compat of msgpacks.
 
 .. warning::
 
-   As a result of a number of issues:
-
    +----------------------+------------------------+
    | Packed with          | Can be unpacked with   |
    +======================+========================+
    | pre-0.17 / Python 2  | any                    |
    +----------------------+------------------------+
    | pre-0.17 / Python 3  | any                    |
    +----------------------+------------------------+
-   | 0.17 / Python 2      | - 0.17 / Python 2      |
+   | 0.17 / Python 2      | - ==0.17 / Python 2    |
    |                      | - >=0.18 / any Python  |
    +----------------------+------------------------+
    | 0.17 / Python 3      | >=0.18 / any Python    |
    +----------------------+------------------------+
    | 0.18                 | >= 0.18                |
-   +======================+========================+
+   +----------------------+------------------------+
+
 
    0.18.0 is backward-compatible for reading files packed by older versions, except for files packed with 0.17 in Python 2, in which case only they can only be unpacked in Python 2.
 
@@ -780,7 +780,7 @@ Now, you can write ``.resample`` as a 2-stage operation like groupby, which
 yields a ``Resampler``.
 
 .. ipython:: python
-
+   :okwarning:
 
    r = df.resample('2s')
    r
@@ -872,9 +872,28 @@ in an inplace change to the ``DataFrame``. (:issue:`9297`)
 .. ipython:: python
 
    df = pd.DataFrame({'a': np.linspace(0, 10, 5), 'b': range(5)})
-   df.eval('c = a + b')
    df
 
+.. ipython:: python
+   :suppress:
+
+   df.eval('c = a + b', inplace=True)
+
+.. code-block:: python
+
+   In [12]: df.eval('c = a + b')
+   FutureWarning: eval expressions containing an assignment currentlydefault to operating inplace.
+   This will change in a future version of pandas, use inplace=True to avoid this warning.
+
+   In [13]: df
+   Out[13]:
+         a  b     c
+   0   0.0  0   0.0
+   1   2.5  1   3.5
+   2   5.0  2   7.0
+   3   7.5  3  10.5
+   4  10.0  4  14.0
+
 In version 0.18.0, a new ``inplace`` keyword was added to choose whether the
 assignment should be done inplace or return a copy.
 
@@ -941,7 +960,7 @@ Other API Changes
 - ``DataFrame.to_latex()`` now supports non-ascii encodings (eg utf-8) in Python 2 with the parameter ``encoding`` (:issue:`7061`)
 - ``pandas.merge()`` and ``DataFrame.merge()`` will show a specific error message when trying to merge with an object that is not of type ``DataFrame`` or a subclass (:issue:`12081`)
 - ``DataFrame.unstack`` and ``Series.unstack`` now take ``fill_value`` keyword to allow direct replacement of missing values when an unstack results in missing values in the resulting ``DataFrame``. As an added benefit, specifying ``fill_value`` will preserve the data type of the original stacked data.  (:issue:`9746`)
-- As part of the new API for :ref:`window functions <whatsnew_0180.enhancements.moments>` and :ref:`resampling <whatsnew_0180.breaking.resample>`, aggregation functions have been clarified, raising more informative error messages on invalid aggregations. (:issue:`9052`). A full set of examples are presented in :ref:`groupby <groupby.aggregation>`.
+- As part of the new API for :ref:`window functions <whatsnew_0180.enhancements.moments>` and :ref:`resampling <whatsnew_0180.breaking.resample>`, aggregation functions have been clarified, raising more informative error messages on invalid aggregations. (:issue:`9052`). A full set of examples are presented in :ref:`groupby <groupby.aggregate>`.
 - Statistical functions for ``NDFrame`` objects will now raise if non-numpy-compatible arguments are passed in for ``**kwargs`` (:issue:`12301`)
 - ``.to_latex`` and ``.to_html`` gain a ``decimal`` parameter like ``.to_csv``; the default is ``'.'`` (:issue:`12031`)
 - More helpful error message when constructing a ``DataFrame`` with empty data but with indices (:issue:`8020`)