• Bug in iloc indexing when positional indexer matched Int64Index of the corresponding axis and no re- ordering happened (GH6612) • Bug in fillna with limit and value specified • Bug in DataFrame.to_stata which returns a boolean indexer. (Their distinction is strictness: match relies on re.match while contains relies on re.search.) In this release, the deprecated behavior is the default, but the new behavior or DataFrame of cleaned-up or more useful strings, without necessitating get() to access tuples or re.match objects. Named groups like 50 Chapter 1. What’s New pandas: powerful Python data analysis

. . . . . . 2011 34.19.4.40pandas.api.types.is_re . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2011 34.19.4.41pandas.api.types.is_re_compilable . . . . . . . . . . . . . . . . . . who relied on those converters being present for regular matplotlib.pyplot plotting methods, so we’re temporarily reverting that change; pandas 0.21.1 again registers the converters on import, just like restore any converters we overwrote when registering them (GH18301). We’re working with the matplotlib developers to make this easier. We’re trying to balance user convenience (auto- matically registering the

. . . . . . 1864 34.16.4.40pandas.api.types.is_re . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1864 34.16.4.41pandas.api.types.is_re_compilable . . . . . . . . . . . . . . . . . . method, see here. • Series.str.replace() now accepts a callable, as replacement, which is passed to re.sub (GH15055) • Series.str.replace() now accepts a compiled regular expression as a pattern (GH15446) (GH15536) 1.3. v0.20.1 (May 5, 2017) 21 pandas: powerful Python data analysis toolkit, Release 0.20.3 • Re-enable the parse_dates keyword of pd.read_excel() to parse string columns as dates (GH14326) • Added

• Bug in iloc indexing when positional indexer matched Int64Index of the corresponding axis and no re- ordering happened (GH6612) • Bug in fillna with limit and value specified • Bug in DataFrame.to_stata which returns a boolean indexer. (Their distinction is strictness: match relies on re.match while contains relies on re.search.) In this release, the deprecated behavior is the default, but the new behavior or DataFrame of cleaned-up or more useful strings, without necessitating get() to access tuples or re.match objects. Named groups like In [88]: Series([’a1’, ’b2’, ’c3’]).str.extract( ....: ’(?P[ab])(

• Bug in iloc indexing when positional indexer matched Int64Index of the corresponding axis and no re- ordering happened (GH6612) • Bug in fillna with limit and value specified • Bug in DataFrame.to_stata which returns a boolean indexer. (Their distinction is strictness: match relies on re.match while contains relies on re.search.) In this release, the deprecated behavior is the default, but the new behavior or DataFrame of cleaned-up or more useful strings, without necessitating get() to access tuples or re.match objects. Named groups like In [88]: Series([’a1’, ’b2’, ’c3’]).str.extract( ....: ’(?P[ab])(

. . . . . . 1731 34.16.4.40pandas.api.types.is_re . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1732 34.16.4.41pandas.api.types.is_re_compilable . . . . . . . . . . . . . . . . . . Release 0.20.2 • Series.str.replace() now accepts a callable, as replacement, which is passed to re.sub (GH15055) • Series.str.replace() now accepts a compiled regular expression as a pattern (GH15446) • DataFrame.to_latex() and DataFrame.to_string() now allow optional header aliases. (GH15536) • Re-enable the parse_dates keyword of pd.read_excel() to parse string columns as dates (GH14326) • Added

which returns a boolean indexer. (Their distinction is strictness: match relies on re.match while contains relies on re.search.) In this release, the deprecated behavior is the default, but the new behavior or DataFrame of cleaned-up or more useful strings, without necessitating get() to access tuples or re.match objects. Named groups like In [88]: Series([’a1’, ’b2’, ’c3’]).str.extract( ....: ’(?P[ab])( method, isin for DataFrames, which plays nicely with boolean indexing. The argument to isin, what we’re comparing the DataFrame to, can be a DataFrame, Series, dict, or array of values. See the docs for

installation you’re currently using. In Linux/Mac you can run which python on your terminal and it will tell you which Python installation you’re using. If it’s something like “/usr/bin/python”, you’re using the time and energy to help make open source pandas possible. Thanks to all of our contributors. If you’re interested in contributing, please visit the contributing guide. pandas is a NumFOCUS sponsored project meant to provide some examples of how various SQL operations would be performed using pandas. If you’re new to pandas, you might want to first read through 10 Minutes to pandas to familiarize yourself with

installation you’re currently using. In Linux/Mac you can run which python on your terminal and it will tell you which Python installation you’re using. If it’s something like “/usr/bin/python”, you’re using the time and energy to help make open source pandas possible. Thanks to all of our contributors. If you’re interested in contributing, please visit the contributing guide. pandas is a NumFOCUS sponsored project meant to provide some examples of how various SQL operations would be performed using pandas. If you’re new to pandas, you might want to first read through 10 Minutes to pandas to familiarize yourself with

installation you’re currently using. In Linux/Mac you can run which python on your terminal and it will tell you which Python installation you’re using. If it’s something like “/usr/bin/python”, you’re using the time and energy to help make open source pandas possible. Thanks to all of our contributors. If you’re interested in contributing, please visit the contributing guide. pandas is a NumFOCUS sponsored project meant to provide some examples of how various SQL operations would be performed using pandas. If you’re new to pandas, you might want to first read through 10 Minutes to pandas to familiarize yourself with