Hello community, here is the log from the commit of package python-pandas for openSUSE:Factory checked in at 2017-12-19 10:58:17 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Comparing /work/SRC/openSUSE:Factory/python-pandas (Old) and /work/SRC/openSUSE:Factory/.python-pandas.new (New) ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Package is "python-pandas" Tue Dec 19 10:58:17 2017 rev:7 rq:557957 version:0.21.1 Changes: -------- --- /work/SRC/openSUSE:Factory/python-pandas/python-pandas-doc.changes 2017-11-10 14:57:08.088648054 +0100 +++ /work/SRC/openSUSE:Factory/.python-pandas.new/python-pandas-doc.changes 2017-12-19 10:58:19.997796956 +0100 @@ -1,0 +2,128 @@ +Sat Dec 16 23:04:54 UTC 2017 - [email protected] + +- update to version 0.21.1: + * Highlights include: + + Temporarily restore matplotlib datetime plotting + functionality. This should resolve issues for users who + implicitly relied on pandas to plot datetimes with + matplotlib. See here. + + Improvements to the Parquet IO functions introduced in + 0.21.0. See here. + * Improvements to the Parquet IO functionality + + DataFrame.to_parquet() will now write non-default indexes when + the underlying engine supports it. The indexes will be preserved + when reading back in with read_parquet() (GH18581). + + read_parquet() now allows to specify the columns to read from a + parquet file (GH18154) + + read_parquet() now allows to specify kwargs which are passed to + the respective engine (GH18216) + * Other Enhancements + + Timestamp.timestamp() is now available in Python 2.7. (GH17329) + + Grouper and TimeGrouper now have a friendly repr output + (GH18203). + * Deprecations + + pandas.tseries.register has been renamed to + pandas.plotting.register_matplotlib_converters`() (GH18301) + * Performance Improvements + + Improved performance of plotting large series/dataframes + (GH18236). + * Conversion + + Bug in TimedeltaIndex subtraction could incorrectly overflow + when NaT is present (GH17791) + + Bug in DatetimeIndex subtracting datetimelike from DatetimeIndex + could fail to overflow (GH18020) + + Bug in IntervalIndex.copy() when copying and IntervalIndex with + non-default closed (GH18339) + + Bug in DataFrame.to_dict() where columns of datetime that are + tz-aware were not converted to required arrays when used with + orient='records', raising"TypeError` (GH18372) + + Bug in DateTimeIndex and date_range() where mismatching tz-aware + start and end timezones would not raise an err if end.tzinfo is + None (GH18431) + + Bug in Series.fillna() which raised when passed a long integer + on Python 2 (GH18159). + * Indexing + + Bug in a boolean comparison of a datetime.datetime and a + datetime64[ns] dtype Series (GH17965) + + Bug where a MultiIndex with more than a million records was not + raising AttributeError when trying to access a missing attribute + (GH18165) + + Bug in IntervalIndex constructor when a list of intervals is + passed with non-default closed (GH18334) + + Bug in Index.putmask when an invalid mask passed (GH18368) + + Bug in masked assignment of a timedelta64[ns] dtype Series, + incorrectly coerced to float (GH18493) + * I/O + + Bug in class:~pandas.io.stata.StataReader not converting + date/time columns with display formatting addressed + (GH17990). Previously columns with display formatting were + normally left as ordinal numbers and not converted to datetime + objects. + + Bug in read_csv() when reading a compressed UTF-16 encoded file + (GH18071) + + Bug in read_csv() for handling null values in index columns when + specifying na_filter=False (GH5239) + + Bug in read_csv() when reading numeric category fields with high + cardinality (GH18186) + + Bug in DataFrame.to_csv() when the table had MultiIndex columns, + and a list of strings was passed in for header (GH5539) + + Bug in parsing integer datetime-like columns with specified + format in read_sql (GH17855). + + Bug in DataFrame.to_msgpack() when serializing data of the + numpy.bool_ datatype (GH18390) + + Bug in read_json() not decoding when reading line deliminted + JSON from S3 (GH17200) + + Bug in pandas.io.json.json_normalize() to avoid modification of + meta (GH18610) + + Bug in to_latex() where repeated multi-index values were not + printed even though a higher level index differed from the + previous row (GH14484) + + Bug when reading NaN-only categorical columns in HDFStore + (GH18413) + + Bug in DataFrame.to_latex() with longtable=True where a latex + multicolumn always spanned over three columns (GH17959) + * Plotting + + Bug in DataFrame.plot() and Series.plot() with DatetimeIndex + where a figure generated by them is not pickleable in Python 3 + (GH18439) + * Groupby/Resample/Rolling + + Bug in DataFrame.resample(...).apply(...) when there is a + callable that returns different columns (GH15169) + + Bug in DataFrame.resample(...) when there is a time change (DST) + and resampling frequecy is 12h or higher (GH15549) + + Bug in pd.DataFrameGroupBy.count() when counting over a + datetimelike column (GH13393) + + Bug in rolling.var where calculation is inaccurate with a + zero-valued array (GH18430) + * Reshaping + + Error message in pd.merge_asof() for key datatype mismatch now + includes datatype of left and right key (GH18068) + + Bug in pd.concat when empty and non-empty DataFrames or Series + are concatenated (GH18178 GH18187) + + Bug in DataFrame.filter(...) when unicode is passed as a + condition in Python 2 (GH13101) + + Bug when merging empty DataFrames when np.seterr(divide='raise') + is set (GH17776) + * Numeric + + Bug in pd.Series.rolling.skew() and rolling.kurt() with all + equal values has floating issue (GH18044) + + Bug in TimedeltaIndex subtraction could incorrectly overflow + when NaT is present (GH17791) + + Bug in DatetimeIndex subtracting datetimelike from DatetimeIndex + could fail to overflow (GH18020) + * Categorical + + Bug in DataFrame.astype() where casting to ‘category’ on an + empty DataFrame causes a segmentation fault (GH18004) + + Error messages in the testing module have been improved when + items have different CategoricalDtype (GH18069) + + CategoricalIndex can now correctly take a + pd.api.types.CategoricalDtype as its dtype (GH18116) + + Bug in Categorical.unique() returning read-only codes array when + all categories were NaN (GH18051) + + Bug in DataFrame.groupby(axis=1) with a CategoricalIndex + (GH18432) + * String + + Series.str.split() will now propogate NaN values across all + expanded columns instead of None (GH18450) + +------------------------------------------------------------------- python-pandas.changes: same change Old: ---- pandas-0.21.0.tar.gz New: ---- pandas-0.21.1.tar.gz ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Other differences: ------------------ ++++++ python-pandas-doc.spec ++++++ --- /var/tmp/diff_new_pack.1SBcGA/_old 2017-12-19 10:58:21.125742505 +0100 +++ /var/tmp/diff_new_pack.1SBcGA/_new 2017-12-19 10:58:21.125742505 +0100 @@ -18,7 +18,7 @@ %{?!python_module:%define python_module() python-%{**} python3-%{**}} Name: python-pandas-doc -Version: 0.21.0 +Version: 0.21.1 Release: 0 Summary: Documentation for python-pandas License: BSD-3-Clause python-pandas.spec: same change ++++++ pandas-0.21.0.tar.gz -> pandas-0.21.1.tar.gz ++++++ /work/SRC/openSUSE:Factory/python-pandas/pandas-0.21.0.tar.gz /work/SRC/openSUSE:Factory/.python-pandas.new/pandas-0.21.1.tar.gz differ: char 5, line 1
