read_excel() supports reading OpenDocument tables. Specify engine='odf' to enable. Consult the IO User Guide for more details (GH9070) • Interval, IntervalIndex, and IntervalArray have gained an is_empty attribute func (GH26372) • Most Pandas classes had a __bytes__ method, which was used for getting a python2-style bytestring repre- sentation of the object. This method has been removed as a part of dropping Python2 large data frames. This feature requires version 0.10.0 of the pandas-gbq library as well as the google-cloud-bigquery-storage and fastavro libraries. (GH26104) • Fixed memory leak in DataFrame.to_json()

read_excel() supports reading OpenDocument tables. Specify engine='odf' to enable. Consult the IO User Guide for more details (GH9070) • Interval, IntervalIndex, and IntervalArray have gained an is_empty attribute func (GH26372) • Most Pandas classes had a __bytes__ method, which was used for getting a python2-style bytestring repre- sentation of the object. This method has been removed as a part of dropping Python2 large data frames. This feature requires version 0.10.0 of the pandas-gbq library as well as the google-cloud-bigquery-storage and fastavro libraries. (GH26104) • Fixed memory leak in DataFrame.to_json()

Python programming language. To the getting started guides To the user guide To the reference guide To the development guide CONTENTS 1 pandas: powerful Python data analysis toolkit, Release 1.0.0 Kleene logic). For example: In [8]: pd.NA | True Out[8]: True For more, see NA section in the user guide on missing data. 1.3.2 Dedicated string data type We’ve added StringDtype, an extension type dedicated engine='ods' when sheet_name argument references a non-existent sheet (GH27676) • Bug in pandas.io.formats.style.Styler() formatting for floating values not displaying decimals correctly (GH13257) • Bug in DataFrame

tutorials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147 2 User Guide 149 2.1 10 minutes to pandas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393 2.4.17 Google BigQuery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 401 2.4 objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 505 2.7.2 Database-style DataFrame or named Series joining/merging . . . . . . . . . . . . . . . . . 519 2.7.3 Timeseries

tutorials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147 2 User Guide 149 2.1 10 minutes to pandas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393 2.4.17 Google BigQuery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 401 2.4 objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 505 2.7.2 Database-style DataFrame or named Series joining/merging . . . . . . . . . . . . . . . . . 519 2.7.3 Timeseries

tutorials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110 2 User Guide 113 2.1 10 minutes to pandas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 331 2.4.15 Google BigQuery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 339 2.4 objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 436 2.7.2 Database-style DataFrame or named Series joining/merging . . . . . . . . . . . . . . . . . 448 2.7.3 Timeseries

tutorials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110 2 User Guide 113 2.1 10 minutes to pandas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 331 2.4.15 Google BigQuery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 339 2.4 objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 436 2.7.2 Database-style DataFrame or named Series joining/merging . . . . . . . . . . . . . . . . . 448 2.7.3 Timeseries

tutorials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142 2 User Guide 145 2.1 10 minutes to pandas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 377 2.4.17 Google BigQuery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 384 2.4 objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 483 2.7.2 Database-style DataFrame or named Series joining/merging . . . . . . . . . . . . . . . . . 496 2.7.3 Timeseries

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 222 2 User Guide 225 2.1 IO tools (text, CSV, HDF5, ...) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 326 2.1.15 Google BigQuery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 334 2.1 objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 430 2.4.2 Database-style DataFrame or named Series joining/merging . . . . . . . . . . . . . . . . . 443 2.4.3 Timeseries

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 222 2 User Guide 225 2.1 IO tools (text, CSV, HDF5, ...) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 326 2.1.15 Google BigQuery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 334 2.1 objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 430 2.4.2 Database-style DataFrame or named Series joining/merging . . . . . . . . . . . . . . . . . 442 2.4.3 Timeseries