Pandas Series: dt.normalize() function

Series.dt.normalize() function

The dt.normalize() function is used to 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.

Syntax:

Series.dt.normalize(self, *args, **kwargs)

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.

Example:

Python-Pandas Code:

import numpy as np
import pandas as pd
idx = pd.date_range(start='2019-08-01 10:00', freq='H',
                    periods=3, tz='Asia/Calcutta')
idx

Output:

DatetimeIndex(['2019-08-01 10:00:00+05:30', '2019-08-01 11:00:00+05:30',
               '2019-08-01 12:00:00+05:30'],
              dtype='datetime64[ns, Asia/Calcutta]', freq='H')

Python-Pandas Code:

import numpy as np
import pandas as pd
idx = pd.date_range(start='2019-08-01 10:00', freq='H',
                    periods=3, tz='Asia/Calcutta')
idx.normalize()

Output:

DatetimeIndex(['2019-08-01 00:00:00+05:30', '2019-08-01 00:00:00+05:30',
               '2019-08-01 00:00:00+05:30'],
              dtype='datetime64[ns, Asia/Calcutta]', freq=None)

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