Home - News ( United States | United Kingdom | Italy | Germany ) - Football scores

Showing content from https://pandas.pydata.org/pandas-docs/stable/reference/api/../api/pandas.DataFrame.to_period.html below:

pandas.DataFrame.to_period — pandas 2.3.1 documentation

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(
...     [
...         "2001-03-31 00:00:00",
...         "2002-05-31 00:00:00",
...         "2003-08-31 00:00:00",
...     ]
... )

>>> idx
DatetimeIndex(['2001-03-31', '2002-05-31', '2003-08-31'],
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]')

RetroSearch is an open source project built by @garambo | Open a GitHub Issue

Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo

HTML: 3.2 | Encoding: UTF-8 | Version: 0.7.4