def normalize(self):
"""
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.DatetimeIndex(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)
"""
new_values = conversion.normalize_i8_timestamps(self.asi8, self.tz)
return type(self)(new_values, freq='infer').tz_localize(self.tz)
def normalize(self):
"""
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.DatetimeIndex(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)
"""
new_values = conversion.normalize_i8_timestamps(self.asi8, self.tz)
return type(self)(new_values, freq='infer').tz_localize(self.tz)