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# pandas.DataFrame.between_time

DataFrame.between_time(start_time, end_time, inclusive='both', axis=None)

  Select values between particular times of the day (e.g., 9:00-9:30 AM).

  By setting `start_time` to be later than `end_time`, you can get the times that are not between the two times.

  Parameters:
    start_timedatetime.time or str

      Initial time as a time filter limit.

    end_timedatetime.time or str

      End time as a time filter limit.

    inclusive{“both”, “neither”, “left”, “right”}, default “both”

      Include boundaries; whether to set each bound as closed or open.

    axis{0 or ‘index’, 1 or ‘columns’}, default 0

      Determine range time on index or columns value. For Series this parameter is unused and defaults to 0.

  Returns:
    Series or DataFrame

      Data from the original object filtered to the specified dates range.

  Raises:
    TypeError

      If the index is not a `DatetimeIndex`

  See also

  `at_time`

    Select values at a particular time of the day.

  `first`

    Select initial periods of time series based on a date offset.

  `last`

    Select final periods of time series based on a date offset.

  `DatetimeIndex.indexer_between_time`

    Get just the index locations for values between particular times of the day.

  Examples

      >>> i = pd.date_range('2018-04-09', periods=4, freq='1D20min')
      >>> ts = pd.DataFrame({'A': [1, 2, 3, 4]}, index=i)
      >>> ts
                           A
      2018-04-09 00:00:00  1
      2018-04-10 00:20:00  2
      2018-04-11 00:40:00  3
      2018-04-12 01:00:00  4

      >>> ts.between_time('0:15', '0:45')
                           A
      2018-04-10 00:20:00  2
      2018-04-11 00:40:00  3

  You get the times that are not between two times by setting `start_time` later than `end_time`:

      >>> ts.between_time('0:45', '0:15')
                           A
      2018-04-09 00:00:00  1
      2018-04-12 01:00:00  4