DateOffset(years=1) Out[68]: Timestamp('2016-10-09 20:59:45.919984') Changes to Index Comparisons Operator equal on Index should behavior similarly to Series (GH9947, GH10637) Starting in v0.17.0, comparing side is a DataFrame (GH11014) • Bug that returns None and does not raise NotImplementedError when operator functions (e.g. .add) of Panel are not implemented (GH7692) • Bug in line and kde plot cannot accept fixes along some new features (pipe() method), enhancements, and performance improvements. We recommend that all users upgrade to this version. Highlights include: • A new pipe method, see here • Documentation

for specifying categoricals . . . . . . . . . . . . . . . . . 11 1.2.1.7 GroupBy objects now have a pipe method . . . . . . . . . . . . . . . . . . . . . 12 1.2.1.8 Categorical.rename_categories accepts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199 1.13.1.1 Pipe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199 1.13.1.2 label-based slicing . . . . . . . . . . . . . . . . . . . . . . . . . . . 390 1.34.4 Changes to Series [] operator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 391 1.34.5 Other API Changes

[45]: result Out[45]: [ A B C 0 1 1 2 [1 rows x 3 columns]] 1.1.7 New Styler.pipe() method The Styler class has gained a pipe() method. This provides a convenient way to apply users’ predefined styling '{:,}', 'X': '{:.1%}'}) ....: .set_properties(**{'text-align': 'right'})) ....: In [48]: df.style.pipe(format_and_align).set_caption('Summary of results.') Out[48]: Similar methods already exist for other classes in pandas, including DataFrame.pipe(), GroupBy.pipe(), and Resampler.pipe(). 1.1.8 Renaming names in a MultiIndex DataFrame.rename_axis() now supports

incompatible API changes 15 pandas: powerful Python data analysis toolkit, Release 0.25.0 The in operator (__contains__) now only returns True for exact matches to Intervals in the IntervalIndex, whereas MultiIndex (GH26944) • Bug in Categorical and CategoricalIndex with Interval values when using the in operator (__contains) with objects that are not comparable to the values in the Interval (GH23705) • Bug Categorical incorrectly raising ValueError instead of TypeError when a list is passed using the in operator (__contains__) (GH21729) • Bug in setting a new value in a Series with a Timedelta object incorrectly

incompatible API changes 15 pandas: powerful Python data analysis toolkit, Release 0.25.1 The in operator (__contains__) now only returns True for exact matches to Intervals in the IntervalIndex, whereas MultiIndex (GH26944) • Bug in Categorical and CategoricalIndex with Interval values when using the in operator (__contains) with objects that are not comparable to the values in the Interval (GH23705) • Bug Categorical incorrectly raising ValueError instead of TypeError when a list is passed using the in operator (__contains__) (GH21729) • Bug in setting a new value in a Series with a Timedelta object incorrectly

returning a Series when there was a column named sparse rather than the accessor (GH30758) • Fixed operator.xor() with a boolean-dtype SparseArray. Now returns a sparse result, rather than object dtype (GH31025) entire DataFrame or Series, row- or column-wise, or elementwise. 1. Tablewise Function Application: pipe() 2. Row or Column-wise Function Application: apply() 3. Aggregation API: agg() and transform() passed into functions. However, if the function needs to be called in a chain, consider using the pipe() method. First some setup: In [138]: def extract_city_name(df): .....: """ .....: Chicago, IL

features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122 Pipe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122 label-based slicing . . . . . . . . . . . . . . . . . . . . . . . . . . . 313 1.27.4 Changes to Series [] operator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 314 1.27.5 Other API Changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 554 13.14.5 Special use of the == operator with list objects . . . . . . . . . . . . . . . . . . . . . . . 555 13.14.6 Boolean Operators .

features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123 Pipe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123 label-based slicing . . . . . . . . . . . . . . . . . . . . . . . . . . . 314 1.28.4 Changes to Series [] operator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 315 1.28.5 Other API Changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 556 13.14.5 Special use of the == operator with list objects . . . . . . . . . . . . . . . . . . . . . . . 557 13.14.6 Boolean Operators .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1251 3.3.5 Binary operator functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1252 3.3.6 Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1745 3.4.5 Binary operator functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1745 3.4.6 Function filtering by rows for which the class is either 2 or 3 and combining the two statements with an | (or) operator: In [18]: class_23 = titanic[(titanic["Pclass"] == 2) | (titanic["Pclass"] == 3)] (continues on

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1251 3.3.5 Binary operator functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1252 3.3.6 Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1745 3.4.5 Binary operator functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1745 3.4.6 Function filtering by rows for which the class is either 2 or 3 and combining the two statements with an | (or) operator: In [18]: class_23 = titanic[(titanic["Pclass"] == 2) | (titanic["Pclass"] == 3)] In [19]: class_23