pandas.DataFrame.to_period#

DataFrame.to_period(freq=None, axis=0, copy=None)[source] #

Convert DataFrame from DatetimeIndex to PeriodIndex.

Convert DataFrame from DatetimeIndex to PeriodIndex with desired frequency (inferred from index if not passed).

Parameters:

freqstr, default

Frequency of the PeriodIndex.

axis{0 or ‘index’, 1 or ‘columns’}, default 0

The axis to convert (the index by default).

copybool, default True

If False then underlying input data is not copied.

Note

The copy keyword will change behavior in pandas 3.0. Copy-on-Write will be enabled by default, which means that all methods with a copy keyword will use a lazy copy mechanism to defer the copy and ignore the copy keyword. The copy keyword will be removed in a future version of pandas.

You can already get the future behavior and improvements through enabling copy on write pd.options.mode.copy_on_write = True

Returns:

DataFrame

The DataFrame has a PeriodIndex.

Examples

>>> idx = pd.to_datetime(
...  [
...  "2001年03月31日 00:00:00",
...  "2002年05月31日 00:00:00",
...  "2003年08月31日 00:00:00",
...  ]
... )

>>> idx
DatetimeIndex(['2001年03月31日', '2002年05月31日', '2003年08月31日'],
dtype='datetime64[ns]', freq=None)

>>> idx.to_period("M")
PeriodIndex(['2001-03', '2002-05', '2003-08'], dtype='period[M]')

For the yearly frequency

>>> idx.to_period("Y")
PeriodIndex(['2001', '2002', '2003'], dtype='period[Y-DEC]')