pandas.DatetimeIndex.mean#

DatetimeIndex.mean(*, skipna=True, axis=0)[source] #

Return the mean value of the Array.

Parameters:

skipnabool, default True

Whether to ignore any NaT elements.

axisint, optional, default 0

Returns:

scalar

Timestamp or Timedelta.

See also

numpy.ndarray.mean

Returns the average of array elements along a given axis.

Series.mean

Return the mean value in a Series.

Notes

mean is only defined for Datetime and Timedelta dtypes, not for Period.

Examples

For pandas.DatetimeIndex:

>>> idx = pd.date_range('2001年01月01日 00:00', periods=3)
>>> idx
DatetimeIndex(['2001年01月01日', '2001年01月02日', '2001年01月03日'],
 dtype='datetime64[ns]', freq='D')
>>> idx.mean()
Timestamp('2001年01月02日 00:00:00')

For pandas.TimedeltaIndex:

>>> tdelta_idx = pd.to_timedelta([1, 2, 3], unit='D')
>>> tdelta_idx
TimedeltaIndex(['1 days', '2 days', '3 days'],
 dtype='timedelta64[ns]', freq=None)
>>> tdelta_idx.mean()
Timedelta('2 days 00:00:00')