return val raise Exception("matplotlib has not been imported. aborting") import matplotlib.pyplot as plt if val == "default": style_backup = dict([(k, plt.rcParams[k]) for k in mpl_stylesheet]) plt.rcParams.update(mpl_stylesheet) elif not val: if style_backup: plt.rcParams.update(style_backup) return val with cf.config_prefix("display"): cf.register_option("precision", 6, pc_precision_doc, validator=is_int) cf.register_option("float_format", None, float_format_doc, validator=is_one_of_factory([None, is_callable])) cf.register_option("column_space", 12, validator=is_int) cf.register_option("max_info_rows", 1690785, pc_max_info_rows_doc, validator=is_instance_factory((int, type(None)))) cf.register_option("max_rows", 60, pc_max_rows_doc, validator=is_instance_factory([type(None), int])) cf.register_option("max_categories", 8, pc_max_categories_doc, validator=is_int) cf.register_option("max_colwidth", 50, max_colwidth_doc, validator=is_int) cf.register_option("max_columns", 20, pc_max_cols_doc, validator=is_instance_factory([type(None), int])) cf.register_option("large_repr", "truncate", pc_large_repr_doc, validator=is_one_of_factory(["truncate", "info"])) cf.register_option("max_info_columns", 100, pc_max_info_cols_doc, validator=is_int) cf.register_option("colheader_justify", "right", colheader_justify_doc, validator=is_text) cf.register_option("notebook_repr_html", True, pc_nb_repr_h_doc, validator=is_bool) cf.register_option("date_dayfirst", False, pc_date_dayfirst_doc, validator=is_bool) cf.register_option("date_yearfirst", False, pc_date_yearfirst_doc, validator=is_bool) cf.register_option("pprint_nest_depth", 3, pc_pprint_nest_depth, validator=is_int)
use_numexpr_doc = """ : bool Use the numexpr library to accelerate computation if it is installed, the default is True Valid values: False,True """ def use_numexpr_cb(key): from pandas.core.computation import expressions expressions.set_use_numexpr(cf.get_option(key)) with cf.config_prefix('compute'): cf.register_option('use_bottleneck', True, use_bottleneck_doc, validator=is_bool, cb=use_bottleneck_cb) cf.register_option('use_numexpr', True, use_numexpr_doc, validator=is_bool, cb=use_numexpr_cb) # # options from the "display" namespace pc_precision_doc = """ : int
return val raise Exception("matplotlib has not been imported. aborting") import matplotlib.pyplot as plt if val == 'default': style_backup = dict([(k, plt.rcParams[k]) for k in mpl_stylesheet]) plt.rcParams.update(mpl_stylesheet) elif not val: if style_backup: plt.rcParams.update(style_backup) return val with cf.config_prefix('display'): cf.register_option('precision', 6, pc_precision_doc, validator=is_int) cf.register_option('float_format', None, float_format_doc, validator=is_one_of_factory([None, is_callable])) cf.register_option('column_space', 12, validator=is_int) cf.register_option('max_info_rows', 1690785, pc_max_info_rows_doc, validator=is_instance_factory((int, type(None)))) cf.register_option('max_rows', 60, pc_max_rows_doc, validator=is_instance_factory([type(None), int])) cf.register_option('max_categories', 8, pc_max_categories_doc, validator=is_int) cf.register_option('max_colwidth', 50, max_colwidth_doc, validator=is_int) cf.register_option('max_columns', 20, pc_max_cols_doc, validator=is_instance_factory([type(None), int])) cf.register_option('large_repr', 'truncate', pc_large_repr_doc, validator=is_one_of_factory(['truncate', 'info']))
If set to None, the number of items to be printed is unlimited. """ pc_max_info_rows_doc = """ : int or None max_info_rows is the maximum number of rows for which a frame will perform a null check on its columns when repr'ing To a console. The default is 1,000,000 rows. So, if a DataFrame has more 1,000,000 rows there will be no null check performed on the columns and thus the representation will take much less time to display in an interactive session. A value of None means always perform a null check when repr'ing. """ with cf.config_prefix('display'): cf.register_option('precision', 7, pc_precision_doc, validator=is_int) cf.register_option('float_format', None, float_format_doc) cf.register_option('column_space', 12, validator=is_int) cf.register_option('max_info_rows', 1000000, pc_max_info_rows_doc, validator=is_instance_factory((int, type(None)))) cf.register_option('max_rows', 100, pc_max_rows_doc, validator=is_int) cf.register_option('max_colwidth', 50, max_colwidth_doc, validator=is_int) cf.register_option('max_columns', 20, pc_max_cols_doc, validator=is_int) cf.register_option('max_info_columns', 100, pc_max_info_cols_doc, validator=is_int) cf.register_option('colheader_justify',
use_numexpr_doc = """ : bool Use the numexpr library to accelerate computation if it is installed, the default is True Valid values: False,True """ def use_numexpr_cb(key): from pandas.core.computation import expressions expressions.set_use_numexpr(cf.get_option(key)) with cf.config_prefix('compute'): cf.register_option('use_bottleneck', True, use_bottleneck_doc, validator=is_bool, cb=use_bottleneck_cb) cf.register_option('use_numexpr', True, use_numexpr_doc, validator=is_bool, cb=use_numexpr_cb) # # options from the "display" namespace pc_precision_doc = """ : int Floating point output precision (number of significant digits). This is only a suggestion """ pc_colspace_doc = """ : int
if not val: # starting up, we get reset to None return val raise Exception("matplotlib has not been imported. aborting") import matplotlib.pyplot as plt if val == 'default': style_backup = dict([(k, plt.rcParams[k]) for k in mpl_stylesheet]) plt.rcParams.update(mpl_stylesheet) elif not val: if style_backup: plt.rcParams.update(style_backup) return val with cf.config_prefix('display'): cf.register_option('precision', 6, pc_precision_doc, validator=is_int) cf.register_option('float_format', None, float_format_doc, validator=is_one_of_factory([None, is_callable])) cf.register_option('column_space', 12, validator=is_int) cf.register_option('max_info_rows', 1690785, pc_max_info_rows_doc, validator=is_instance_factory((int, type(None)))) cf.register_option('max_rows', 60, pc_max_rows_doc, validator=is_instance_factory([type(None), int])) cf.register_option('max_categories', 8, pc_max_categories_doc, validator=is_int) cf.register_option('max_colwidth', 50, max_colwidth_doc, validator=is_int) cf.register_option('max_columns', 20, pc_max_cols_doc, validator=is_instance_factory([type(None), int])) cf.register_option('large_repr', 'truncate', pc_large_repr_doc, validator=is_one_of_factory(['truncate', 'info']))
pc_expand_repr_doc=""" : boolean Default False Whether to print out the full DataFrame repr for wide DataFrames across multiple lines. If False, the summary representation is shown. """ pc_line_width_doc=""" : int Default 80 When printing wide DataFrames, this is the width of each line. """ with cf.config_prefix('print'): cf.register_option('precision', 7, pc_precision_doc, validator=is_int) cf.register_option('float_format', None, float_format_doc) cf.register_option('column_space', 12, validator=is_int) cf.register_option('max_rows', 100, pc_max_rows_doc, validator=is_int) cf.register_option('max_colwidth', 50, max_colwidth_doc, validator=is_int) cf.register_option('max_columns', 20, pc_max_cols_doc, validator=is_int) cf.register_option('colheader_justify', 'right', colheader_justify_doc, validator=is_text) cf.register_option('notebook_repr_html', True, pc_nb_repr_h_doc, validator=is_bool) cf.register_option('date_dayfirst', False, pc_date_dayfirst_doc, validator=is_bool) cf.register_option('date_yearfirst', False, pc_date_yearfirst_doc, validator=is_bool) cf.register_option('pprint_nest_depth', 3, pc_pprint_nest_depth,
return val raise Exception("matplotlib has not been imported. aborting") import matplotlib.pyplot as plt if val == 'default': style_backup = dict([(k,plt.rcParams[k]) for k in mpl_stylesheet]) plt.rcParams.update(mpl_stylesheet) elif not val: if style_backup: plt.rcParams.update(style_backup) return val with cf.config_prefix('display'): cf.register_option('precision', 7, pc_precision_doc, validator=is_int) cf.register_option('float_format', None, float_format_doc) cf.register_option('column_space', 12, validator=is_int) cf.register_option('max_info_rows', 1690785, pc_max_info_rows_doc, validator=is_instance_factory((int, type(None)))) cf.register_option('max_rows', 100, pc_max_rows_doc, validator=is_int) cf.register_option('max_colwidth', 50, max_colwidth_doc, validator=is_int) cf.register_option('max_columns', 20, pc_max_cols_doc, validator=is_int) cf.register_option('max_info_columns', 100, pc_max_info_cols_doc, validator=is_int) cf.register_option('colheader_justify', 'right', colheader_justify_doc, validator=is_text) cf.register_option('notebook_repr_html', True, pc_nb_repr_h_doc, validator=is_bool) cf.register_option('date_dayfirst', False, pc_date_dayfirst_doc,
""" pc_multi_sparse_doc = """ : boolean Default True, "sparsify" MultiIndex display (don't display repeated elements in outer levels within groups) """ pc_encoding_doc = """ : 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. """ with cf.config_prefix("print_config"): cf.register_option("precision", 7, pc_precision_doc, validator=is_int) cf.register_option("digits", 7, validator=is_int) cf.register_option("float_format", None) cf.register_option("column_space", 12, validator=is_int) cf.register_option("max_rows", 200, pc_max_rows_doc, validator=is_int) cf.register_option("max_colwidth", 50, validator=is_int) cf.register_option("max_columns", 0, pc_max_cols_doc, validator=is_int) cf.register_option("colheader_justify", "right", validator=is_text) cf.register_option("notebook_repr_html", True, pc_nb_repr_h_doc, validator=is_bool) cf.register_option("date_dayfirst", False, pc_date_dayfirst_doc, validator=is_bool) cf.register_option("date_yearfirst", False, pc_date_yearfirst_doc, validator=is_bool) cf.register_option("pprint_nest_depth", 3, pc_pprint_nest_depth, validator=is_int) cf.register_option("multi_sparse", True, pc_multi_sparse_doc, validator=is_bool) cf.register_option("encoding", detect_console_encoding(), pc_encoding_doc, validator=is_text)
""" pc_multi_sparse_doc = """ : boolean Default True, "sparsify" MultiIndex display (don't display repeated elements in outer levels within groups) """ pc_encoding_doc = """ : 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. """ with cf.config_prefix('print_config'): cf.register_option('precision', 7, pc_precision_doc, validator=is_int) cf.register_option('digits', 7, validator=is_int) cf.register_option('float_format', None) cf.register_option('column_space', 12, validator=is_int) cf.register_option('max_rows', 200, pc_max_rows_doc, validator=is_int) cf.register_option('max_colwidth', 50, validator=is_int) cf.register_option('max_columns', 0, pc_max_cols_doc, validator=is_int) cf.register_option('colheader_justify', 'right', validator=is_text) cf.register_option('notebook_repr_html', True, pc_nb_repr_h_doc, validator=is_bool) cf.register_option('date_dayfirst', False, pc_date_dayfirst_doc,
If False, the summary representation is shown. """ pc_line_width_doc = """ : int Default 80 When printing wide DataFrames, this is the width of each line. """ pc_chop_threshold_doc = """ : float or None Default 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. """ with cf.config_prefix("display"): cf.register_option("precision", 7, pc_precision_doc, validator=is_int) cf.register_option("float_format", None, float_format_doc) cf.register_option("column_space", 12, validator=is_int) cf.register_option("max_rows", 100, pc_max_rows_doc, validator=is_int) cf.register_option("max_colwidth", 50, max_colwidth_doc, validator=is_int) cf.register_option("max_columns", 20, pc_max_cols_doc, validator=is_int) cf.register_option("max_info_columns", 100, pc_max_info_cols_doc, validator=is_int) cf.register_option("colheader_justify", "right", colheader_justify_doc, validator=is_text) cf.register_option("notebook_repr_html", True, pc_nb_repr_h_doc, validator=is_bool) cf.register_option("date_dayfirst", False, pc_date_dayfirst_doc, validator=is_bool) cf.register_option("date_yearfirst", False, pc_date_yearfirst_doc, validator=is_bool) cf.register_option("pprint_nest_depth", 3, pc_pprint_nest_depth, validator=is_int) cf.register_option("multi_sparse", True, pc_multi_sparse_doc, validator=is_bool) cf.register_option("encoding", detect_console_encoding(), pc_encoding_doc, validator=is_text) cf.register_option("expand_frame_repr", True, pc_expand_repr_doc)
""" max_colwidth_doc = """ : 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. """ colheader_justify_doc = """ : 'left'/'right' Controls the justification of column headers. used by DataFrameFormatter. """ with cf.config_prefix('print'): cf.register_option('precision', 7, pc_precision_doc, validator=is_int) cf.register_option('digits', 7, validator=is_int) cf.register_option('float_format', None, float_format_doc) cf.register_option('column_space', 12, validator=is_int) cf.register_option('max_rows', 200, pc_max_rows_doc, validator=is_int) cf.register_option('max_colwidth', 50, max_colwidth_doc, validator=is_int) cf.register_option('max_columns', 0, pc_max_cols_doc, validator=is_int) cf.register_option('colheader_justify', 'right', colheader_justify_doc, validator=is_text) cf.register_option('notebook_repr_html', True, pc_nb_repr_h_doc, validator=is_bool)