Available options:

• compute.[use_bottleneck, use_numba, use_numexpr]

• display.[chop_threshold, colheader_justify, column_space, date_dayfirst, date_yearfirst, encoding, expand_frame_repr, float_format]

• display.html.[border, table_schema, use_mathjax]

• display.[large_repr]

• display.latex.[escape, longtable, multicolumn, multicolumn_format, multirow, repr]

• display.[max_categories, max_columns, max_colwidth, max_info_columns, max_info_rows, max_rows, max_seq_items, memory_usage, min_rows, multi_sparse, notebook_repr_html, pprint_nest_depth, precision, show_dimensions]

• display.unicode.[ambiguous_as_wide, east_asian_width]

• display.[width]

• io.excel.ods.[reader, writer]

• io.excel.xls.[reader, writer]

• io.excel.xlsb.[reader]

• io.excel.xlsm.[reader, writer]

• io.excel.xlsx.[reader, writer]

• io.hdf.[default_format, dropna_table]

• io.parquet.[engine]

• mode.[chained_assignment, sim_interactive, use_inf_as_na, use_inf_as_null]

• plotting.[backend]

• plotting.matplotlib.[register_converters]

Parameters：pat：str

Regexp which should match a single option. Note: partial matches are supported for convenience, but unless you use the full option name (e.g. x.y.z.option_name), your code may break in future versions if new options with similar names are introduced.

value：object，New value of option.

Returns：?None

Raises： OptionError if no such option exists

Notes

The available options with its descriptions:

compute.use_bottleneckbool

Use the bottleneck library to accelerate if it is installed, the default is True Valid values: False,True [default: True] [currently: True]

compute.use_numbabool

Use the numba engine option for select operations if it is installed, the default is False Valid values: False,True [default: False] [currently: False]

compute.use_numexprbool

Use the numexpr library to accelerate computation if it is installed, the default is True Valid values: False,True [default: True] [currently: True]

display.chop_thresholdfloat or None

if set to a float value, all float values smaller then the given threshold will be displayed as exactly 0 by repr and friends. [default: None] [currently: None]

display.colheader_justify‘left’/’right’

Controls the justification of column headers. used by DataFrameFormatter. [default: right] [currently: right]

display.column_space No description available.

[default: 12] [currently: 12]

display.date_dayfirstboolean

When True, prints and parses dates with the day first, eg 20/01/2005 [default: False] [currently: False]

display.date_yearfirstboolean

When True, prints and parses dates with the year first, eg 2005/01/20 [default: False] [currently: False]

display.encodingstr/unicode

Defaults to the detected encoding of the console. Specifies the encoding to be used for strings returned by to_string, these are generally strings meant to be displayed on the console. [default: utf-8] [currently: utf-8]

display.expand_frame_reprboolean

Whether to print out the full DataFrame repr for wide DataFrames across multiple lines,?max_columns?is still respected, but the output will wrap-around across multiple “pages” if its width exceeds?display.width. [default: True] [currently: True]

display.float_formatcallable

The callable should accept a floating point number and return a string with the desired format of the number. This is used in some places like SeriesFormatter. See formats.format.EngFormatter for an example. [default: None] [currently: None]

display.html.borderint

A?border=value?attribute is inserted in the?<table>?tag for the DataFrame HTML repr. [default: 1] [currently: 1]

display.html.table_schemaboolean

Whether to publish a Table Schema representation for frontends that support it. (default: False) [default: False] [currently: False]

display.html.use_mathjaxboolean

When True, Jupyter notebook will process table contents using MathJax, rendering mathematical expressions enclosed by the dollar symbol. (default: True) [default: True] [currently: True]

display.large_repr‘truncate’/’info’

For DataFrames exceeding max_rows/max_cols, the repr (and HTML repr) can show a truncated table (the default from 0.13), or switch to the view from df.info() (the behaviour in earlier versions of pandas). [default: truncate] [currently: truncate]

display.latex.escapebool

This specifies if the to_latex method of a Dataframe uses escapes special characters. Valid values: False,True [default: True] [currently: True]

display.latex.longtable :bool

This specifies if the to_latex method of a Dataframe uses the longtable format. Valid values: False,True [default: False] [currently: False]

display.latex.multicolumnbool

This specifies if the to_latex method of a Dataframe uses multicolumns to pretty-print MultiIndex columns. Valid values: False,True [default: True] [currently: True]

display.latex.multicolumn_formatbool

This specifies if the to_latex method of a Dataframe uses multicolumns to pretty-print MultiIndex columns. Valid values: False,True [default: l] [currently: l]

display.latex.multirowbool

This specifies if the to_latex method of a Dataframe uses multirows to pretty-print MultiIndex rows. Valid values: False,True [default: False] [currently: False]

display.latex.reprboolean

Whether to produce a latex DataFrame representation for jupyter environments that support it. (default: False) [default: False] [currently: False]

display.max_categoriesint

This sets the maximum number of categories pandas should output when printing out a?Categorical?or a Series of dtype “category”. [default: 8] [currently: 8]

display.max_columnsint

If max_cols is exceeded, switch to truncate view. Depending on?large_repr, objects are either centrally truncated or printed as a summary view. ‘None’ value means unlimited.

In case python/IPython is running in a terminal and?large_repr?equals ‘truncate’ this can be set to 0 and pandas will auto-detect the width of the terminal and print a truncated object which fits the screen width. The IPython notebook, IPython qtconsole, or IDLE do not run in a terminal and hence it is not possible to do correct auto-detection. [default: 0] [currently: 0]

display.max_colwidthint or None

The maximum width in characters of a column in the repr of a pandas data structure. When the column overflows, a “…” placeholder is embedded in the output. A ‘None’ value means unlimited. [default: 50] [currently: 50]

display.max_info_columnsint

max_info_columns is used in DataFrame.info method to decide if per column information will be printed. [default: 100] [currently: 100]

display.max_info_rowsint or None

df.info() will usually show null-counts for each column. For large frames this can be quite slow. max_info_rows and max_info_cols limit this null check only to frames with smaller dimensions than specified. [default: 1690785] [currently: 1690785]

display.max_rowsint

If max_rows is exceeded, switch to truncate view. Depending on?large_repr, objects are either centrally truncated or printed as a summary view. ‘None’ value means unlimited.

In case python/IPython is running in a terminal and?large_repr?equals ‘truncate’ this can be set to 0 and pandas will auto-detect the height of the terminal and print a truncated object which fits the screen height. The IPython notebook, IPython qtconsole, or IDLE do not run in a terminal and hence it is not possible to do correct auto-detection. [default: 60] [currently: 15]

display.max_seq_itemsint or None

when pretty-printing a long sequence, no more then?max_seq_items?will be printed. If items are omitted, they will be denoted by the addition of “…” to the resulting string.

If set to None, the number of items to be printed is unlimited. [default: 100] [currently: 100]

display.memory_usagebool, string or None

This specifies if the memory usage of a DataFrame should be displayed when df.info() is called. Valid values True,False,’deep’ [default: True] [currently: True]

display.min_rowsint

The numbers of rows to show in a truncated view (when?max_rows?is exceeded). Ignored when?max_rows?is set to None or 0. When set to None, follows the value of?max_rows. [default: 10] [currently: 10]

display.multi_sparseboolean

“sparsify” MultiIndex display (don’t display repeated elements in outer levels within groups) [default: True] [currently: True]

display.notebook_repr_htmlboolean

When True, IPython notebook will use html representation for pandas objects (if it is available). [default: True] [currently: True]

display.pprint_nest_depthint

Controls the number of nested levels to process when pretty-printing [default: 3] [currently: 3]

display.precisionint

Floating point output precision (number of significant digits). This is only a suggestion [default: 6] [currently: 6]

display.show_dimensionsboolean or ‘truncate’

Whether to print out dimensions at the end of DataFrame repr. If ‘truncate’ is specified, only print out the dimensions if the frame is truncated (e.g. not display all rows and/or columns) [default: truncate] [currently: truncate]

display.unicode.ambiguous_as_wideboolean

Whether to use the Unicode East Asian Width to calculate the display text width. Enabling this may affect to the performance (default: False) [default: False] [currently: False]

display.unicode.east_asian_widthboolean

Whether to use the Unicode East Asian Width to calculate the display text width. Enabling this may affect to the performance (default: False) [default: False] [currently: False]

display.widthint

Width of the display in characters. In case python/IPython is running in a terminal this can be set to None and pandas will correctly auto-detect the width. Note that the IPython notebook, IPython qtconsole, or IDLE do not run in a terminal and hence it is not possible to correctly detect the width. [default: 80] [currently: 80]

io.excel.ods.readerstring

The default Excel reader engine for ‘ods’ files. Available options: auto, odf. [default: auto] [currently: auto]

io.excel.ods.writerstring

The default Excel writer engine for ‘ods’ files. Available options: auto, odf. [default: auto] [currently: auto]

io.excel.xls.readerstring

The default Excel reader engine for ‘xls’ files. Available options: auto, xlrd. [default: auto] [currently: auto]

io.excel.xls.writerstring

The default Excel writer engine for ‘xls’ files. Available options: auto, xlwt. [default: auto] [currently: auto]

io.excel.xlsb.readerstring

The default Excel reader engine for ‘xlsb’ files. Available options: auto, pyxlsb. [default: auto] [currently: auto]

io.excel.xlsm.readerstring

The default Excel reader engine for ‘xlsm’ files. Available options: auto, xlrd, openpyxl. [default: auto] [currently: auto]

io.excel.xlsm.writerstring

The default Excel writer engine for ‘xlsm’ files. Available options: auto, openpyxl. [default: auto] [currently: auto]

io.excel.xlsx.readerstring

The default Excel reader engine for ‘xlsx’ files. Available options: auto, xlrd, openpyxl. [default: auto] [currently: auto]

io.excel.xlsx.writerstring

The default Excel writer engine for ‘xlsx’ files. Available options: auto, openpyxl, xlsxwriter. [default: auto] [currently: auto]

io.hdf.default_formatformat

default format writing format, if None, then put will default to ‘fixed’ and append will default to ‘table’ [default: None] [currently: None]

io.hdf.dropna_tableboolean

drop ALL nan rows when appending to a table [default: False] [currently: False]

io.parquet.enginestring

The default parquet reader/writer engine. Available options: ‘auto’, ‘pyarrow’, ‘fastparquet’, the default is ‘auto’ [default: auto] [currently: auto]

mode.chained_assignmentstring

Raise an exception, warn, or no action if trying to use chained assignment, The default is warn [default: warn] [currently: warn]

mode.sim_interactiveboolean

Whether to simulate interactive mode for purposes of testing [default: False] [currently: False]

mode.use_inf_as_naboolean

True means treat None, NaN, INF, -INF as NA (old way), False means None and NaN are null, but INF, -INF are not NA (new way). [default: False] [currently: False]

mode.use_inf_as_nullboolean

use_inf_as_null had been deprecated and will be removed in a future version. Use?use_inf_as_na?instead. [default: False] [currently: False] (Deprecated, use?mode.use_inf_as_na?instead.)

plotting.backendstr

The plotting backend to use. The default value is “matplotlib”, the backend provided with pandas. Other backends can be specified by providing the name of the module that implements the backend. [default: matplotlib] [currently: matplotlib]

plotting.matplotlib.register_convertersbool or ‘auto’.

Whether to register converters with matplotlib’s units registry for dates, times, datetimes, and Periods. Toggling to False will remove the converters, restoring any converters that pandas overwrote. [default: auto] [currently: auto]

?