Merge branch 'master' of https://github.com/pandas-dev/pandas into knf

Author: jbrockmendel

doc/source/conf.py

@@ -315,7 +315,6 @@
    import numpy as np
    import pandas as pd
 
-   randn = np.random.randn
    np.random.seed(123456)
    np.set_printoptions(precision=4, suppress=True)
    pd.options.display.max_rows = 15

doc/source/whatsnew/index.rst

@@ -24,6 +24,7 @@ Version 0.25
 .. toctree::
    :maxdepth: 2
 
+   v0.25.2
    v0.25.1
    v0.25.0
 

doc/source/whatsnew/v0.10.0.rst

@@ -498,7 +498,7 @@ Here is a taste of what to expect.
 
 .. code-block:: ipython
 
-  In [58]: p4d = Panel4D(randn(2, 2, 5, 4),
+  In [58]: p4d = Panel4D(np.random.randn(2, 2, 5, 4),
     ....:       labels=['Label1','Label2'],
     ....:       items=['Item1', 'Item2'],
     ....:       major_axis=date_range('1/1/2000', periods=5),

doc/source/whatsnew/v0.25.1.rst

@@ -1,56 +1,44 @@
 .. _whatsnew_0251:
 
-What's new in 0.25.1 (July XX, 2019)
-------------------------------------
+What's new in 0.25.1 (August 21, 2019)
+--------------------------------------
 
-Enhancements
-~~~~~~~~~~~~
-
-
-.. _whatsnew_0251.enhancements.other:
+These are the changes in pandas 0.25.1. See :ref:`release` for a full changelog
+including other versions of pandas.
 
-Other enhancements
-^^^^^^^^^^^^^^^^^^
+I/O and LZMA
+~~~~~~~~~~~~
 
--
--
--
+Some users may unknowingly have an incomplete Python installation lacking the `lzma` module from the standard library. In this case, `import pandas` failed due to an `ImportError` (:issue: `27575`).
+Pandas will now warn, rather than raising an `ImportError` if the `lzma` module is not present. Any subsequent attempt to use `lzma` methods will raise a `RuntimeError`.
+A possible fix for the lack of the `lzma` module is to ensure you have the necessary libraries and then re-install Python.
+For example, on MacOS installing Python with `pyenv` may lead to an incomplete Python installation due to unmet system dependencies at compilation time (like `xz`). Compilation will succeed, but Python might fail at run time. The issue can be solved by installing the necessary dependencies and then re-installing Python.
 
 .. _whatsnew_0251.bug_fixes:
 
 Bug fixes
 ~~~~~~~~~
 
-
 Categorical
 ^^^^^^^^^^^
 
-- Bug in :meth:`Categorical.fillna` would replace all values, not just those that are ``NaN`` (:issue:`26215`)
--
+- Bug in :meth:`Categorical.fillna` that would replace all values, not just those that are ``NaN`` (:issue:`26215`)
 
 Datetimelike
 ^^^^^^^^^^^^
+
 - Bug in :func:`to_datetime` where passing a timezone-naive :class:`DatetimeArray` or :class:`DatetimeIndex` and ``utc=True`` would incorrectly return a timezone-naive result (:issue:`27733`)
 - Bug in :meth:`Period.to_timestamp` where a :class:`Period` outside the :class:`Timestamp` implementation bounds (roughly 1677-09-21 to 2262-04-11) would return an incorrect :class:`Timestamp` instead of raising ``OutOfBoundsDatetime`` (:issue:`19643`)
--
--
-
-Timedelta
-^^^^^^^^^
-
--
--
--
+- Bug in iterating over :class:`DatetimeIndex` when the underlying data is read-only (:issue:`28055`)
 
 Timezones
 ^^^^^^^^^
 
 - Bug in :class:`Index` where a numpy object array with a timezone aware :class:`Timestamp` and ``np.nan`` would not return a :class:`DatetimeIndex` (:issue:`27011`)
--
--
 
 Numeric
 ^^^^^^^
+
 - Bug in :meth:`Series.interpolate` when using a timezone aware :class:`DatetimeIndex` (:issue:`27548`)
 - Bug when printing negative floating point complex numbers would raise an ``IndexError`` (:issue:`27484`)
 - Bug where :class:`DataFrame` arithmetic operators such as :meth:`DataFrame.mul` with a :class:`Series` with axis=1 would raise an ``AttributeError`` on :class:`DataFrame` larger than the minimum threshold to invoke numexpr (:issue:`27636`)
@@ -60,23 +48,11 @@ Conversion
 ^^^^^^^^^^
 
 - Improved the warnings for the deprecated methods :meth:`Series.real` and :meth:`Series.imag` (:issue:`27610`)
--
--
-
-Strings
-^^^^^^^
-
--
--
--
-
 
 Interval
 ^^^^^^^^
+
 - Bug in :class:`IntervalIndex` where `dir(obj)` would raise ``ValueError`` (:issue:`27571`)
--
--
--
 
 Indexing
 ^^^^^^^^
@@ -85,92 +61,55 @@ Indexing
 - Break reference cycle involving :class:`Index` and other index classes to allow garbage collection of index objects without running the GC. (:issue:`27585`, :issue:`27840`)
 - Fix regression in assigning values to a single column of a DataFrame with a ``MultiIndex`` columns (:issue:`27841`).
 - Fix regression in ``.ix`` fallback with an ``IntervalIndex`` (:issue:`27865`).
--
 
 Missing
 ^^^^^^^
 
-- Bug in :func:`pandas.isnull` or :func:`pandas.isna` when the input is a type e.g. `type(pandas.Series())` (:issue:`27482`)
--
--
-
-MultiIndex
-^^^^^^^^^^
-
--
--
--
+- Bug in :func:`pandas.isnull` or :func:`pandas.isna` when the input is a type e.g. ``type(pandas.Series())`` (:issue:`27482`)
 
 I/O
 ^^^
+
 - Avoid calling ``S3File.s3`` when reading parquet, as this was removed in s3fs version 0.3.0 (:issue:`27756`)
 - Better error message when a negative header is passed in :func:`pandas.read_csv` (:issue:`27779`)
-- Follow the ``min_rows`` display option (introduced in v0.25.0) correctly in the html repr in the notebook (:issue:`27991`).
--
+- Follow the ``min_rows`` display option (introduced in v0.25.0) correctly in the HTML repr in the notebook (:issue:`27991`).
 
 Plotting
 ^^^^^^^^
 
-- Added a pandas_plotting_backends entrypoint group for registering plot backends. See :ref:`extending.plotting-backends` for more (:issue:`26747`).
+- Added a ``pandas_plotting_backends`` entrypoint group for registering plot backends. See :ref:`extending.plotting-backends` for more (:issue:`26747`).
 - Fixed the re-instatement of Matplotlib datetime converters after calling
-  `pandas.plotting.deregister_matplotlib_converters()` (:issue:`27481`).
--
+  :meth:`pandas.plotting.deregister_matplotlib_converters` (:issue:`27481`).
 - Fix compatibility issue with matplotlib when passing a pandas ``Index`` to a plot call (:issue:`27775`).
--
 
 Groupby/resample/rolling
 ^^^^^^^^^^^^^^^^^^^^^^^^
 
+- Fixed regression in :meth:`pands.core.groupby.DataFrameGroupBy.quantile` raising when multiple quantiles are given (:issue:`27526`)
 - Bug in :meth:`pandas.core.groupby.DataFrameGroupBy.transform` where applying a timezone conversion lambda function would drop timezone information (:issue:`27496`)
 - Bug in :meth:`pandas.core.groupby.GroupBy.nth` where ``observed=False`` was being ignored for Categorical groupers (:issue:`26385`)
 - Bug in windowing over read-only arrays (:issue:`27766`)
 - Fixed segfault in `pandas.core.groupby.DataFrameGroupBy.quantile` when an invalid quantile was passed (:issue:`27470`)
--
 
 Reshaping
 ^^^^^^^^^
 
 - A ``KeyError`` is now raised if ``.unstack()`` is called on a :class:`Series` or :class:`DataFrame` with a flat :class:`Index` passing a name which is not the correct one (:issue:`18303`)
+- Bug :meth:`merge_asof` could not merge :class:`Timedelta` objects when passing `tolerance` kwarg (:issue:`27642`)
 - Bug in :meth:`DataFrame.crosstab` when ``margins`` set to ``True`` and ``normalize`` is not ``False``, an error is raised. (:issue:`27500`)
 - :meth:`DataFrame.join` now suppresses the ``FutureWarning`` when the sort parameter is specified (:issue:`21952`)
 - Bug in :meth:`DataFrame.join` raising with readonly arrays (:issue:`27943`)
 
 Sparse
 ^^^^^^
-- Bug in reductions for :class:`Series` with Sparse dtypes (:issue:`27080`)
--
--
--
-
-
-Build Changes
-^^^^^^^^^^^^^
-
--
--
--
-
-ExtensionArray
-^^^^^^^^^^^^^^
 
--
--
--
+- Bug in reductions for :class:`Series` with Sparse dtypes (:issue:`27080`)
 
 Other
 ^^^^^
-- Bug in :meth:`Series.replace` and :meth:`DataFrame.replace` when replacing timezone-aware timestamps using a dict-like replacer (:issue:`27720`)
--
--
--
-
-I/O and LZMA
-~~~~~~~~~~~~
 
-Some users may unknowingly have an incomplete Python installation, which lacks the `lzma` module from the standard library. In this case, `import pandas` failed due to an `ImportError` (:issue: `27575`).
-Pandas will now warn, rather than raising an `ImportError` if the `lzma` module is not present. Any subsequent attempt to use `lzma` methods will raise a `RuntimeError`.
-A possible fix for the lack of the `lzma` module is to ensure you have the necessary libraries and then re-install Python.
-For example, on MacOS installing Python with `pyenv` may lead to an incomplete Python installation due to unmet system dependencies at compilation time (like `xz`). Compilation will succeed, but Python might fail at run time. The issue can be solved by installing the necessary dependencies and then re-installing Python.
+- Bug in :meth:`Series.replace` and :meth:`DataFrame.replace` when replacing timezone-aware timestamps using a dict-like replacer (:issue:`27720`)
+- Bug in :meth:`Series.rename` when using a custom type indexer. Now any value that isn't callable or dict-like is treated as a scalar. (:issue:`27814`)
 
 .. _whatsnew_0.251.contributors:
 

doc/source/whatsnew/v0.25.2.rst

@@ -0,0 +1,110 @@
+.. _whatsnew_0252:
+
+What's new in 0.25.2 (October XX, 2019)
+---------------------------------------
+
+These are the changes in pandas 0.25.2. See :ref:`release` for a full changelog
+including other versions of pandas.
+
+.. _whatsnew_0252.bug_fixes:
+
+Bug fixes
+~~~~~~~~~
+
+Categorical
+^^^^^^^^^^^
+
+-
+
+Datetimelike
+^^^^^^^^^^^^
+
+-
+-
+-
+
+Timezones
+^^^^^^^^^
+
+-
+
+Numeric
+^^^^^^^
+
+-
+-
+-
+-
+
+Conversion
+^^^^^^^^^^
+
+-
+
+Interval
+^^^^^^^^
+
+-
+
+Indexing
+^^^^^^^^
+
+-
+-
+-
+-
+
+Missing
+^^^^^^^
+
+-
+
+I/O
+^^^
+
+-
+-
+-
+
+Plotting
+^^^^^^^^
+
+-
+-
+-
+
+Groupby/resample/rolling
+^^^^^^^^^^^^^^^^^^^^^^^^
+
+-
+-
+-
+-
+-
+
+Reshaping
+^^^^^^^^^
+
+-
+-
+-
+-
+-
+
+Sparse
+^^^^^^
+
+-
+
+Other
+^^^^^
+
+-
+-
+
+.. _whatsnew_0.252.contributors:
+
+Contributors
+~~~~~~~~~~~~
+
+.. contributors:: v0.25.1..HEAD

pandas/_libs/tslib.pyx

@@ -71,7 +71,7 @@ cdef inline object create_time_from_ts(
 
 @cython.wraparound(False)
 @cython.boundscheck(False)
-def ints_to_pydatetime(int64_t[:] arr, object tz=None, object freq=None,
+def ints_to_pydatetime(const int64_t[:] arr, object tz=None, object freq=None,
                        str box="datetime"):
     """
     Convert an i8 repr to an ndarray of datetimes, date, time or Timestamp

pandas/core/arrays/base.py

@@ -514,7 +514,7 @@ def fillna(self, value=None, method=None, limit=None):
 
     def dropna(self):
         """
-        Return ExtensionArray without NA values
+        Return ExtensionArray without NA values.
 
         Returns
         -------
@@ -957,7 +957,7 @@ def _concat_same_type(
         cls, to_concat: Sequence[ABCExtensionArray]
     ) -> ABCExtensionArray:
         """
-        Concatenate multiple array
+        Concatenate multiple array.
 
         Parameters
         ----------

pandas/core/arrays/datetimes.py

@@ -1158,7 +1158,7 @@ def tz_localize(self, tz, ambiguous="raise", nonexistent="raise", errors=None):
     def to_pydatetime(self):
         """
         Return Datetime Array/Index as object ndarray of datetime.datetime
-        objects
+        objects.
 
         Returns
         -------
@@ -1283,7 +1283,7 @@ def to_perioddelta(self, freq):
         """
         Calculate TimedeltaArray of difference between index
         values and index converted to PeriodArray at specified
-        freq. Used for vectorized offsets
+        freq. Used for vectorized offsets.
 
         Parameters
         ----------

pandas/core/arrays/period.py

@@ -426,7 +426,7 @@ def __array__(self, dtype=None):
     @property
     def is_leap_year(self):
         """
-        Logical indicating if the date belongs to a leap year
+        Logical indicating if the date belongs to a leap year.
         """
         return isleapyear_arr(np.asarray(self.year))
 

pandas/core/frame.py

@@ -3098,7 +3098,7 @@ def _ensure_valid_index(self, value):
         passed value.
         """
         # GH5632, make sure that we are a Series convertible
-        if not len(self.index) and is_list_like(value):
+        if not len(self.index) and is_list_like(value) and len(value):
             try:
                 value = Series(value)
             except (ValueError, NotImplementedError, TypeError):