isin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 435 2.5.15 The where() Method and Masking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 438 2.5.16 Setting pandas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2691 4.1.1 Where to start? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2692 produce new objects and leave the input data untouched. In general we like to favor immutability where sensible. Getting support The first stop for pandas issues and ideas is the Github Issue Tracker

isin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 435 2.5.15 The where() Method and Masking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 438 2.5.16 Setting pandas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2691 4.1.1 Where to start? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2692 produce new objects and leave the input data untouched. In general we like to favor immutability where sensible. Getting support The first stop for pandas issues and ideas is the Github Issue Tracker

Out[11]: 0 abc 1 2 def Length: 3, dtype: string The usual string accessor methods work. Where appropriate, the return type of the Series or columns of a DataFrame will also have string dtype. dtype('O') This fixes an inconsistency between resample and groupby. This also fixes a potential bug, where the values of the result might change depending on how the results are cast back to the original dtype cat() does not accept list-likes within list-likes anymore (GH27611) • Series.where() with Categorical dtype (or DataFrame.where() with Categorical column) no longer allows setting new categories (GH24114)

isin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 417 2.5.15 The where() Method and Masking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 419 2.5.16 Setting pandas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2613 4.1.1 Where to start? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2614 produce new objects and leave the input data untouched. In general we like to favor immutability where sensible. Getting support The first stop for pandas issues and ideas is the Github Issue Tracker

isin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 371 2.5.15 The where() Method and Masking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 373 2.5.16 The query() pandas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2419 4.1.1 Where to start? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2420 produce new objects and leave the input data untouched. In general we like to favor immutability where sensible. Getting support The first stop for pandas issues and ideas is the Github Issue Tracker

isin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 438 2.5.15 The where() Method and Masking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 440 2.5.16 Setting pandas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2785 4.1.1 Where to start? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2786 produce new objects and leave the input data untouched. In general we like to favor immutability where sensible. Getting support The first stop for pandas issues and ideas is the Github Issue Tracker

isin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 371 2.5.15 The where() Method and Masking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 373 2.5.16 The query() pandas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2419 4.1.1 Where to start? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2420 produce new objects and leave the input data untouched. In general we like to favor immutability where sensible. Getting support The first stop for pandas issues and ideas is the Github Issue Tracker

isin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 437 2.5.15 The where() Method and Masking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 440 2.5.16 Setting pandas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2783 4.1.1 Where to start? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2784 produce new objects and leave the input data untouched. In general we like to favor immutability where sensible. Getting support The first stop for pandas issues and ideas is the Github Issue Tracker

Pass the desired columns names as the **kwargs to .agg. The values of **kwargs should be tuples where the first element is the column selection, and the second element is the aggregation function to apply different than the existing matplotlib one. Use pandas.set_option('plotting.backend', '') where where() and DataFrame.mask() (GH17744) • Removed the previously deprecated ordered and categories keyword

isin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 374 2.5.15 The where() Method and Masking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 376 2.5.16 Setting pandas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2469 4.1.1 Where to start? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2470 produce new objects and leave the input data untouched. In general we like to favor immutability where sensible. Getting support The first stop for pandas issues and ideas is the Github Issue Tracker