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    * [ pandas.PeriodIndex ](pandas.PeriodIndex.html)
    * [ pandas.PeriodIndex.day ](pandas.PeriodIndex.day.html)
    * [ pandas.PeriodIndex.dayofweek ](pandas.PeriodIndex.dayofweek.html)
    * [ pandas.PeriodIndex.day_of_week ](pandas.PeriodIndex.day_of_week.html)
    * [ pandas.PeriodIndex.dayofyear ](pandas.PeriodIndex.dayofyear.html)
    * [ pandas.PeriodIndex.day_of_year ](pandas.PeriodIndex.day_of_year.html)
    * [ pandas.PeriodIndex.days_in_month ](pandas.PeriodIndex.days_in_month.html)
    * [ pandas.PeriodIndex.daysinmonth ](pandas.PeriodIndex.daysinmonth.html)
    * [ pandas.PeriodIndex.end_time ](pandas.PeriodIndex.end_time.html)
    * [ pandas.PeriodIndex.freq ](pandas.PeriodIndex.freq.html)
    * [ pandas.PeriodIndex.freqstr ](pandas.PeriodIndex.freqstr.html)
    * [ pandas.PeriodIndex.hour ](pandas.PeriodIndex.hour.html)
    * [ pandas.PeriodIndex.is_leap_year ](pandas.PeriodIndex.is_leap_year.html)
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    * [ pandas.PeriodIndex.weekday ](pandas.PeriodIndex.weekday.html)
    * [ pandas.PeriodIndex.weekofyear ](pandas.PeriodIndex.weekofyear.html)
    * [ pandas.PeriodIndex.year ](pandas.PeriodIndex.year.html)
    * [ pandas.PeriodIndex.asfreq ](pandas.PeriodIndex.asfreq.html)
    * [ pandas.PeriodIndex.strftime ](pandas.PeriodIndex.strftime.html)
    * [ pandas.PeriodIndex.to_timestamp ](pandas.PeriodIndex.to_timestamp.html)
    * [ pandas.PeriodIndex.from_fields ](pandas.PeriodIndex.from_fields.html)
    * [ pandas.PeriodIndex.from_ordinals ](pandas.PeriodIndex.from_ordinals.html)
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  * [ Missing values ](../missing_value.html)

  * [ __ ](../../index.html)
  * [ API reference ](../index.html)
  * __
  * [ pandas.DatetimeIndex ](pandas.DatetimeIndex.html)
  * pandas.Datet... 

#  pandas.DatetimeIndex.date  #

_ property  _ DatetimeIndex.  date  [ [source]  ](https://github.com/pandas-
dev/pandas/blob/v2.2.2/pandas/core/indexes/extension.py#L67-L75) #

    

Returns numpy array of python [ ` datetime.date  `
](https://docs.python.org/3/library/datetime.html#datetime.date "\(in Python
v3.12\)") objects.

Namely, the date part of Timestamps without time and timezone information.

Examples

For Series:

    
    
    >>> s = pd.Series(["1/1/2020 10:00:00+00:00", "2/1/2020 11:00:00+00:00"])
    >>> s = pd.to_datetime(s)
    >>> s
    0   2020-01-01 10:00:00+00:00
    1   2020-02-01 11:00:00+00:00
    dtype: datetime64[ns, UTC]
    >>> s.dt.date
    0    2020-01-01
    1    2020-02-01
    dtype: object
    

For DatetimeIndex:

    
    
    >>> idx = pd.DatetimeIndex(["1/1/2020 10:00:00+00:00",
    ...                         "2/1/2020 11:00:00+00:00"])
    >>> idx.date
    array([datetime.date(2020, 1, 1), datetime.date(2020, 2, 1)], dtype=object)
    

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