# compute.use_bottleneck: bool
#     Use the bottleneck library to accelerate if it is installed,
#     the default is True
#     Valid values: False,True
#compute.use_bottleneck: True

# compute.use_numexpr: bool
#     Use the numexpr library to accelerate computation if it is installed,
#     the default is True
#     Valid values: False,True
#compute.use_numexpr: True

# display.chop_threshold: float 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.
#display.chop_threshold: None

# display.colheader_justify: 'left'/'right'
#     Controls the justification of column headers. used by DataFrameFormatter.
#display.colheader_justify: right

# display.column_space
#display.column_space: 12

# display.date_dayfirst: boolean
#     When True, prints and parses dates with the day first, eg 20/01/2005
#display.date_dayfirst: False

# display.date_yearfirst: boolean
#     When True, prints and parses dates with the year first, eg 2005/01/20
#display.date_yearfirst: False

# display.encoding: str/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.
#display.encoding: UTF-8

# display.expand_frame_repr: boolean
#     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`.
#display.expand_frame_repr: True

# display.float_format: callable
#     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.
#display.float_format: None

# display.html.border: int
#     A ``border=value`` attribute is inserted in the ``<table>`` tag
#     for the DataFrame HTML repr.
#display.html.border: 1

# display.html.table_schema: boolean
#     Whether to publish a Table Schema representation for frontends
#     that support it.
#     (default: False)
#display.html.table_schema: False

# display.html.use_mathjax: boolean
#     When True, Jupyter notebook will process table contents using MathJax,
#     rendering mathematical expressions enclosed by the dollar symbol.
#     (default: True)
#display.html.use_mathjax: 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).
#display.large_repr: truncate

# display.latex.escape: bool
#     This specifies if the to_latex method of a Dataframe uses escapes special
#     characters.
#     Valid values: False,True
#display.latex.escape: True

# display.latex.longtable:bool
#     This specifies if the to_latex method of a Dataframe uses the longtable
#     format.
#     Valid values: False,True
#display.latex.longtable: False

# display.latex.multicolumn: bool
#     This specifies if the to_latex method of a Dataframe uses multicolumns
#     to pretty-print MultiIndex columns.
#     Valid values: False,True
#display.latex.multicolumn: True

# display.latex.multicolumn_format: bool
#     This specifies if the to_latex method of a Dataframe uses multicolumns
#     to pretty-print MultiIndex columns.
#     Valid values: False,True
#display.latex.multicolumn_format: l

# display.latex.multirow: bool
#     This specifies if the to_latex method of a Dataframe uses multirows
#     to pretty-print MultiIndex rows.
#     Valid values: False,True
#display.latex.multirow: False

# display.latex.repr: boolean
#     Whether to produce a latex DataFrame representation for jupyter
#     environments that support it.
#     (default: False)
#display.latex.repr: False

# display.max_categories: int
#     This sets the maximum number of categories pandas should output when
#     printing out a `Categorical` or a Series of dtype "category".
#display.max_categories: 8

# display.max_columns: int
#     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.
#display.max_columns: 0

# display.max_colwidth: int
#     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.
#display.max_colwidth: 50

# display.max_info_columns: int
#     max_info_columns is used in DataFrame.info method to decide if
#     per column information will be printed.
#display.max_info_columns: 100

# display.max_info_rows: int 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.
#display.max_info_rows: 1690785

# display.max_rows: int
#     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.
#display.max_rows: 60

# display.max_seq_items: int 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.
#display.max_seq_items: 100

# display.memory_usage: bool, 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'
#display.memory_usage: True

# display.multi_sparse: boolean
#     "sparsify" MultiIndex display (don't display repeated
#     elements in outer levels within groups)
#display.multi_sparse: True

# display.notebook_repr_html: boolean
#     When True, IPython notebook will use html representation for
#     pandas objects (if it is available).
#display.notebook_repr_html: True

# display.pprint_nest_depth: int
#     Controls the number of nested levels to process when pretty-printing
#display.pprint_nest_depth: 3

# display.precision: int
#     Floating point output precision (number of significant digits). This is
#     only a suggestion
#display.precision: 6

# display.show_dimensions: boolean 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)
#display.show_dimensions: truncate

# display.unicode.ambiguous_as_wide: boolean
#     Whether to use the Unicode East Asian Width to calculate the display text
#     width.
#     Enabling this may affect to the performance (default: False)
#display.unicode.ambiguous_as_wide: False

# display.unicode.east_asian_width: boolean
#     Whether to use the Unicode East Asian Width to calculate the display text
#     width.
#     Enabling this may affect to the performance (default: False)
#display.unicode.east_asian_width: False

# display.width: int
#     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.
#display.width: 80

# html.border: int
#     A ``border=value`` attribute is inserted in the ``<table>`` tag
#     for the DataFrame HTML repr.
# DEPRECATED
#html.border: 1

# io.excel.xls.writer: string
#     The default Excel writer engine for 'xls' files. Available options:
#     auto, xlwt.
#io.excel.xls.writer: auto

# io.excel.xlsm.writer: string
#     The default Excel writer engine for 'xlsm' files. Available options:
#     auto, openpyxl.
#io.excel.xlsm.writer: auto

# io.excel.xlsx.writer: string
#     The default Excel writer engine for 'xlsx' files. Available options:
#     auto, openpyxl, xlsxwriter.
#io.excel.xlsx.writer: auto

# io.hdf.default_format: format
#     default format writing format, if None, then
#     put will default to 'fixed' and append will default to 'table'
#io.hdf.default_format: None

# io.hdf.dropna_table: boolean
#     drop ALL nan rows when appending to a table
#io.hdf.dropna_table: False

# io.parquet.engine: string
#     The default parquet reader/writer engine. Available options:
#     'auto', 'pyarrow', 'fastparquet', the default is 'auto'
#io.parquet.engine: auto

# mode.chained_assignment: string
#     Raise an exception, warn, or no action if trying to use chained assignment,
#     The default is warn
#mode.chained_assignment: warn

# mode.sim_interactive: boolean
#     Whether to simulate interactive mode for purposes of testing
#mode.sim_interactive: False

# mode.use_inf_as_na: boolean
#     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).
#mode.use_inf_as_na: False

# mode.use_inf_as_null: boolean
#     use_inf_as_null had been deprecated and will be removed in a future
#     version. Use `use_inf_as_na` instead.
# DEPRECATED
#mode.use_inf_as_null: False

# plotting.matplotlib.register_converters: bool
#     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.
#plotting.matplotlib.register_converters: True