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DOC: whatsnew typos
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jreback committed Jul 26, 2017
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70 changes: 34 additions & 36 deletions doc/source/whatsnew/v0.21.0.txt
Original file line number Diff line number Diff line change
Expand Up @@ -134,72 +134,70 @@ Dtype Conversions
^^^^^^^^^^^^^^^^^

- Previously assignments, ``.where()`` and ``.fillna()`` with a ``bool`` assignment, would coerce to
same type (e.g. int / float), or raise for datetimelikes. These will now preseve the bools with ``object`` dtypes. (:issue:`16821`).
same the type (e.g. int / float), or raise for datetimelikes. These will now preseve the bools with ``object`` dtypes. (:issue:`16821`).

.. ipython:: python
.. ipython:: python

s = Series([1, 2, 3])
s = Series([1, 2, 3])

.. code-block:: python
.. code-block:: python

In [5]: s[1] = True
In [5]: s[1] = True

In [6]: s
Out[6]:
0 1
1 1
2 3
dtype: int64
In [6]: s
Out[6]:
0 1
1 1
2 3
dtype: int64

New Behavior
New Behavior

.. ipython:: python
.. ipython:: python

s[1] = True
s
s[1] = True
s

- Previously as assignment to a datetimelike with a non-datetimelike would coerce the
- Previously, as assignment to a datetimelike with a non-datetimelike would coerce the
non-datetime-like item being assigned (:issue:`14145`).

.. ipython:: python
.. ipython:: python

s = pd.Series([pd.Timestamp('2011-01-01'), pd.Timestamp('2012-01-01')])
s = pd.Series([pd.Timestamp('2011-01-01'), pd.Timestamp('2012-01-01')])

.. code-block:: python
.. code-block:: python

In [1]: s[1] = 1
In [1]: s[1] = 1

In [2]: s
Out[2]:
0 2011-01-01 00:00:00.000000000
1 1970-01-01 00:00:00.000000001
dtype: datetime64[ns]
In [2]: s
Out[2]:
0 2011-01-01 00:00:00.000000000
1 1970-01-01 00:00:00.000000001
dtype: datetime64[ns]

These now coerce to ``object`` dtype.
These now coerce to ``object`` dtype.

.. ipython:: python
.. ipython:: python

s[1] = 1
s
s[1] = 1
s

- Additional bug fixes w.r.t. dtype conversions.

- Inconsistent behavior in ``.where()`` with datetimelikes which would raise rather than coerce to ``object`` (:issue:`16402`)
- Bug in assignment against ``int64`` data with ``np.ndarray`` with ``float64`` dtype may keep ``int64`` dtype (:issue:`14001`)
- Inconsistent behavior in ``.where()`` with datetimelikes which would raise rather than coerce to ``object`` (:issue:`16402`)
- Bug in assignment against ``int64`` data with ``np.ndarray`` with ``float64`` dtype may keep ``int64`` dtype (:issue:`14001`)

.. _whatsnew_0210.api.na_changes:

NA naming Changes
^^^^^^^^^^^^^^^^^

In orde to promote more consistency among the pandas API, we have added additional top-level
In order to promote more consistency among the pandas API, we have added additional top-level
functions :func:`isna` and :func:`notna` that are aliases for :func:`isnull` and :func:`notnull`.
The naming scheme is now more consistent with methods like ``.dropna()`` and ``.fillna()``. Furthermore
in all cases where ``.isnull()`` and ``.notnull()`` methods are defined, these have additional methods
named ``.isna()`` and ``.notna()``, these are included for classes ``Categorical``,
``Index``, ``Series``, and ``DataFrame``. (:issue:`15001`).

The configuration option ``mode.use_inf_as_null``is deprecated, and ``mode.use_inf_as_na`` is added as a replacement.
The configuration option ``pd.options.mode.use_inf_as_null`` is deprecated, and ``pd.options.mode.use_inf_as_na`` is added as a replacement.

.. _whatsnew_0210.api:

Expand Down Expand Up @@ -281,7 +279,7 @@ I/O

- Bug in :func:`read_csv` in which columns were not being thoroughly de-duplicated (:issue:`17060`)
- Bug in :func:`read_csv` in which non integer values for the header argument generated an unhelpful / unrelated error message (:issue:`16338`)
- Bug in :func:`read_csv` in which memory management issues in exception handling, under certain conditions, would cause the interpreter to segfault (:issue:`14696, :issue:`16798`).
- Bug in :func:`read_csv` in which memory management issues in exception handling, under certain conditions, would cause the interpreter to segfault (:issue:`14696`, :issue:`16798`).
- Bug in :func:`read_csv` when called with ``low_memory=False`` in which a CSV with at least one column > 2GB in size would incorrectly raise a ``MemoryError`` (:issue:`16798`).
- Bug in :func:`read_stata` where value labels could not be read when using an iterator (:issue:`16923`)
- Bug in :func:`read_html` where import check fails when run in multiple threads (:issue:`16928`)
Expand Down

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