/pandas/core/api.py
Python | 81 lines | 59 code | 17 blank | 5 comment | 2 complexity | b2b6e5d4532ebb0101b4c1791c64345f MD5 | raw file
- # pylint: disable=W0614,W0401,W0611
- # flake8: noqa
- import numpy as np
- from pandas.core.algorithms import factorize, unique, value_counts
- from pandas.core.dtypes.missing import isna, isnull, notna, notnull
- from pandas.core.categorical import Categorical
- from pandas.core.groupby import Grouper
- from pandas.io.formats.format import set_eng_float_format
- from pandas.core.index import (Index, CategoricalIndex, Int64Index,
- UInt64Index, RangeIndex, Float64Index,
- MultiIndex, IntervalIndex,
- TimedeltaIndex, DatetimeIndex,
- PeriodIndex, NaT)
- from pandas.core.indexes.period import Period, period_range, pnow
- from pandas.core.indexes.timedeltas import Timedelta, timedelta_range
- from pandas.core.indexes.datetimes import Timestamp, date_range, bdate_range
- from pandas.core.indexes.interval import Interval, interval_range
- from pandas.core.series import Series
- from pandas.core.frame import DataFrame
- from pandas.core.panel import Panel, WidePanel
- from pandas.core.panel4d import Panel4D
- from pandas.core.reshape.reshape import (
- pivot_simple as pivot, get_dummies,
- lreshape, wide_to_long)
- from pandas.core.indexing import IndexSlice
- from pandas.core.tools.numeric import to_numeric
- from pandas.tseries.offsets import DateOffset
- from pandas.core.tools.datetimes import to_datetime
- from pandas.core.tools.timedeltas import to_timedelta
- # see gh-14094.
- from pandas.util._depr_module import _DeprecatedModule
- _removals = ['day', 'bday', 'businessDay', 'cday', 'customBusinessDay',
- 'customBusinessMonthEnd', 'customBusinessMonthBegin',
- 'monthEnd', 'yearEnd', 'yearBegin', 'bmonthEnd', 'bmonthBegin',
- 'cbmonthEnd', 'cbmonthBegin', 'bquarterEnd', 'quarterEnd',
- 'byearEnd', 'week']
- datetools = _DeprecatedModule(deprmod='pandas.core.datetools',
- removals=_removals)
- from pandas.core.config import (get_option, set_option, reset_option,
- describe_option, option_context, options)
- # deprecation, xref #13790
- def match(*args, **kwargs):
- import warnings
- warnings.warn("pd.match() is deprecated and will be removed "
- "in a future version",
- FutureWarning, stacklevel=2)
- from pandas.core.algorithms import match
- return match(*args, **kwargs)
- def groupby(*args, **kwargs):
- import warnings
- warnings.warn("pd.groupby() is deprecated and will be removed; "
- "Please use the Series.groupby() or "
- "DataFrame.groupby() methods",
- FutureWarning, stacklevel=2)
- return args[0].groupby(*args[1:], **kwargs)
- # deprecation, xref
- class TimeGrouper(object):
- def __new__(cls, *args, **kwargs):
- from pandas.core.resample import TimeGrouper
- import warnings
- warnings.warn("pd.TimeGrouper is deprecated and will be removed; "
- "Please use pd.Grouper(freq=...)",
- FutureWarning, stacklevel=2)
- return TimeGrouper(*args, **kwargs)