pandas.set_option函数的参数解释
pandas.set_option(pat, value) = <pandas._config.config.CallableDynamicDoc object>
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]
