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

Showing content from https://pandas.pydata.org/pandas-docs/stable/reference/api/../api/pandas.Series.dt.normalize.html below:

pandas.Series.dt.normalize — pandas 2.3.1 documentation

Series.dt.normalize(*args, **kwargs)[source]#

Convert times to midnight.

The time component of the date-time is converted to midnight i.e. 00:00:00. This is useful in cases, when the time does not matter. Length is unaltered. The timezones are unaffected.

This method is available on Series with datetime values under the .dt accessor, and directly on Datetime Array/Index.

Returns:

DatetimeArray, DatetimeIndex or Series

The same type as the original data. Series will have the same name and index. DatetimeIndex will have the same name.

See also

floor

Floor the datetimes to the specified freq.

ceil

Ceil the datetimes to the specified freq.

round

Round the datetimes to the specified freq.

Examples

>>> idx = pd.date_range(start='2014-08-01 10:00', freq='h',
...                     periods=3, tz='Asia/Calcutta')
>>> idx
DatetimeIndex(['2014-08-01 10:00:00+05:30',
               '2014-08-01 11:00:00+05:30',
               '2014-08-01 12:00:00+05:30'],
                dtype='datetime64[ns, Asia/Calcutta]', freq='h')
>>> idx.normalize()
DatetimeIndex(['2014-08-01 00:00:00+05:30',
               '2014-08-01 00:00:00+05:30',
               '2014-08-01 00:00:00+05:30'],
               dtype='datetime64[ns, Asia/Calcutta]', freq=None)

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