# dask.dataframe.Series.dt.normalize

#### dataframe.Series.dt.normalize() → Self

Convert times to midnight.

This docstring was copied from pandas.core.indexes.accessors.CombinedDatetimelikeProperties.normalize.

Some inconsistencies with the Dask version may exist.

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`](dask.dataframe.Series.dt.floor.html.md#dask.dataframe.Series.dt.floor)
: Floor the datetimes to the specified freq.

[`ceil`](dask.dataframe.Series.dt.ceil.html.md#dask.dataframe.Series.dt.ceil)
: Ceil the datetimes to the specified freq.

[`round`](dask.dataframe.Series.dt.round.html.md#dask.dataframe.Series.dt.round)
: Round the datetimes to the specified freq.

### Examples

```pycon
>>> 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[us, 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[us, Asia/Calcutta]', freq=None)
```

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