python3-pandas: Upgrade 1.2.0 -> 1.2.1

Upgrade to release 1.2.1:

- Fixed regression in to_csv() that created corrupted zip files
  when there were more rows than chunksize
- Fixed regression in to_csv() opening codecs.StreamReaderWriter
  in binary mode instead of in text mode
- Fixed regression in read_csv() and other read functions were
  the encoding error policy (errors) did not default to "replace"
  when no encoding was specified
- Fixed regression in read_excel() with non-rawbyte file handles
- Fixed regression in DataFrame.to_stata() not removing the
  created file when an error occured
- Fixed regression in DataFrame.__setitem__ raising ValueError
  when expanding DataFrame and new column is from type "0 - name"
- Fixed regression in setting with DataFrame.loc() raising
  ValueError when DataFrame has unsorted MultiIndex columns and
  indexer is a scalar
- Fixed regression in setting with DataFrame.loc() raising
  KeyError with MultiIndex and list-like columns indexer enlarging
  DataFrame
- Fixed regression in groupby() with Categorical grouping column
  not showing unused categories for grouped.indices
- Fixed regression in GroupBy.sem() where the presence of
  non-numeric columns would cause an error instead of being
  dropped
- Fixed regression in DataFrameGroupBy.diff() raising for int8 and
  int16 columns
- Fixed regression in DataFrame.groupby() when aggregating an
  ExtensionDType that could fail for non-numeric values
- Fixed regression in Rolling.skew() and Rolling.kurt() modifying
  the object inplace
- Fixed regression in DataFrame.any() and DataFrame.all() not
  returning a result for tz-aware datetime64 columns
- Fixed regression in DataFrame.apply() with axis=1 using str
  accessor in apply function
- Fixed regression in DataFrame.replace() raising ValueError when
  DataFrame has dtype bytes
- Fixed regression in Series.fillna() that raised RecursionError
  with datetime64[ns, UTC] dtype
- Fixed regression in comparisons between NaT and datetime.date
  objects incorrectly returning True
- Fixed regression in calling NumPy accumulate() ufuncs on
  DataFrames, e.g. np.maximum.accumulate(df)
- Fixed regression in repr of float-like strings of an object
  dtype having trailing 0’s truncated after the decimal
- Fixed regression that raised AttributeError with PyArrow
  versions [0.16.0, 1.0.0)
- Fixed regression in pandas.testing.assert_frame_equal() raising
  TypeError with check_like=True when Index or columns have mixed
  dtype

Signed-off-by: Leon Anavi <leon.anavi@konsulko.com>
Acked-by: Trevor Gamblin <trevor.gamblin@windriver.com>
Signed-off-by: Khem Raj <raj.khem@gmail.com>

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