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Method to_period

pandas/core/frame.py:16299–16374  ·  view source on GitHub ↗

Convert DataFrame from DatetimeIndex to PeriodIndex. Convert DataFrame from DatetimeIndex to PeriodIndex with desired frequency (inferred from index if not passed). Either index of columns can be converted, depending on `axis` argument. Parameters -

(
        self,
        freq: Frequency | None = None,
        axis: Axis = 0,
        copy: bool | lib.NoDefault = lib.no_default,
    )

Source from the content-addressed store, hash-verified

16297 return new_obj
16298
16299 def to_period(
16300 self,
16301 freq: Frequency | None = None,
16302 axis: Axis = 0,
16303 copy: bool | lib.NoDefault = lib.no_default,
16304 ) -> DataFrame:
16305 """
16306 Convert DataFrame from DatetimeIndex to PeriodIndex.
16307
16308 Convert DataFrame from DatetimeIndex to PeriodIndex with desired
16309 frequency (inferred from index if not passed). Either index of columns can be
16310 converted, depending on `axis` argument.
16311
16312 Parameters
16313 ----------
16314 freq : str, default
16315 Frequency of the PeriodIndex.
16316 axis : {0 or 'index', 1 or 'columns'}, default 0
16317 The axis to convert (the index by default).
16318 copy : bool, default False
16319 This keyword is now ignored; changing its value will have no
16320 impact on the method.
16321
16322 .. deprecated:: 3.0.0
16323
16324 This keyword is ignored and will be removed in pandas 4.0. Since
16325 pandas 3.0, this method always returns a new object using a lazy
16326 copy mechanism that defers copies until necessary
16327 (Copy-on-Write). See the `user guide on Copy-on-Write
16328 <https://pandas.pydata.org/docs/dev/user_guide/copy_on_write.html>`__
16329 for more details.
16330
16331 Returns
16332 -------
16333 DataFrame
16334 The DataFrame with the converted PeriodIndex.
16335
16336 See Also
16337 --------
16338 Series.to_period: Equivalent method for Series.
16339 Series.dt.to_period: Convert DateTime column values.
16340
16341 Examples
16342 --------
16343 >>> idx = pd.to_datetime(
16344 ... [
16345 ... "2001-03-31 00:00:00",
16346 ... "2002-05-31 00:00:00",
16347 ... "2003-08-31 00:00:00",
16348 ... ]
16349 ... )
16350
16351 >>> idx
16352 DatetimeIndex(['2001-03-31', '2002-05-31', '2003-08-31'],
16353 dtype='datetime64[us]', freq=None)
16354
16355 >>> idx.to_period("M")
16356 PeriodIndex(['2001-03', '2002-05', '2003-08'], dtype='period[M]')

Callers 4

test_to_periodMethod · 0.95

Calls 3

_get_axis_nameMethod · 0.80
copyMethod · 0.45

Tested by 4

test_to_periodMethod · 0.76