Example #1
0
            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)
Example #2
0

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
Example #3
0
            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']))
Example #4
0
    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',
Example #5
0

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
Example #6
0
        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']))
Example #7
0
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,
Example #8
0
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,
Example #9
0
            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,
Example #10
0
"""

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)
Example #11
0

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
Example #12
0
"""

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,
Example #13
0
    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)
Example #14
0
"""

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)