. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 596 11 Options and Settings 599 xiii 11.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Locations and Names . . . . . . . . . . . . . . . . . . . . . . . 1028 24.1.1.3 General Parsing Configuration . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1029 24.1.1.4 NA and Missing Data Handling notna(), these are included for classes Categorical, Index, Series, and DataFrame. (GH15001). The configuration option pd.options.mode.use_inf_as_null is deprecated, and pd.options.mode. use_inf_as_na is added

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 568 11 Options and Settings 571 11.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Locations and Names . . . . . . . . . . . . . . . . . . . . . . . 994 24.1.1.3 General Parsing Configuration . . . . . . . . . . . . . . . . . . . . . . . . . . . . 995 24.1.1.4 NA and Missing Data Handling where the where clause is not a string-like (GH12027) • The pandas.options.display.mpl_style configuration has been deprecated and will be removed in a future version of pandas. This functionality is better

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 566 11 Options and Settings 569 11.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . and Names . . . . . . . . . . . . . . . . . . . . . . . 990 xviii 24.1.1.3 General Parsing Configuration . . . . . . . . . . . . . . . . . . . . . . . . . . . . 991 24.1.1.4 NA and Missing Data Handling where the where clause is not a string-like (GH12027) • The pandas.options.display.mpl_style configuration has been deprecated and will be removed in a future version of pandas. This functionality is better

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 917 2.22 Options and settings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 917 2.22.1 average gratuity by size of the party and sex of the server. In Excel, we use the following configuration for the PivotTable: The equivalent in pandas: In [66]: pd.pivot_table( ....: tips, values="tip" will cause data to be overwritten if there are duplicate names in the columns. General parsing configuration dtype [Type name or dict of column -> type, default None] Data type for data or columns. E.g

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 918 2.22 Options and settings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 918 2.22.1 average gratuity by size of the party and sex of the server. In Excel, we use the following configuration for the PivotTable: The equivalent in pandas: In [66]: pd.pivot_table( ....: tips, values="tip" will cause data to be overwritten if there are duplicate names in the columns. General parsing configuration dtype [Type name or dict of column -> type, default None] Data type for data or columns. E.g

will cause data to be overwritten if there are duplicate names in the columns. General parsing configuration dtype [Type name or dict of column -> type, default None] Data type for data or columns. E.g np.int32} (unsupported with engine='python'). Use str or object together with suitable na_values settings to preserve and not interpret dtype. New in version 0.20.0: support for the Python parser. engine constructor. writer = pd.ExcelWriter('path_to_file.xlsx', engine='xlsxwriter') # Or via pandas configuration. from pandas import options # noqa: E402 options.io.excel.xlsx.writer = 'xlsxwriter' df.to_excel('path_to_file

will cause data to be overwritten if there are duplicate names in the columns. General parsing configuration dtype [Type name or dict of column -> type, default None] Data type for data or columns. E.g np.int32} (unsupported with engine='python'). Use str or object together with suitable na_values settings to preserve and not interpret dtype. New in version 0.20.0: support for the Python parser. engine constructor. writer = pd.ExcelWriter('path_to_file.xlsx', engine='xlsxwriter') # Or via pandas configuration. from pandas import options # noqa: E402 options.io.excel.xlsx.writer = 'xlsxwriter' df.to_excel('path_to_file

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 914 2.2.21 Options and settings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 929 2.2.22 Enhancing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2894 3.14 Options and settings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2894 3.14 average gratuity by size of the party and sex of the server. In Excel, we use the following configuration for the PivotTable: The equivalent in pandas: In [66]: pd.pivot_table( ....: tips, values="tip"

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 323 11 Options and Settings 325 11.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . DataFrame. See the FAQ for more. (GH6852). A new display option display.memory_usage (see Options and Settings) sets the default behavior of the memory_usage argument in the df.info() method. By default display ignoring full line comments in the read_csv() text parser. – New documentation section on Options and Settings. – Lots of bug fixes. • Enhancements • API Changes • Performance Improvements 1.4. v0.14.1

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 315 11 Options and Settings 317 11.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . DataFrame. See the FAQ for more. (GH6852). A new display option display.memory_usage (see Options and Settings) sets the default behavior of the memory_usage argument in the df.info() method. By default display ignoring full line comments in the read_csv() text parser. – New documentation section on Options and Settings. – Lots of bug fixes. • Enhancements • API Changes • Performance Improvements • Experimental