Skip to main content
`Ctrl`+`K`

# pandas.infer_freq

pandas.infer_freq(index)

  Infer the most likely frequency given the input index.

  This method attempts to deduce the most probable frequency (e.g., ‘D’ for daily, ‘H’ for hourly) from a sequence of datetime-like objects. It is particularly useful when the frequency of a time series is not explicitly set or known but can be inferred from its values.

  Parameters:
    index DatetimeIndex, TimedeltaIndex, Series or array-like

      If passed a Series will use the values of the series (NOT THE INDEX).

  Returns:
    str or None

      None if no discernible frequency.

  Raises:
    TypeError

      If the index is not datetime-like.

    ValueError

      If there are fewer than three values.

  See also

  `date_range`

    Return a fixed frequency DatetimeIndex.

  `timedelta_range`

    Return a fixed frequency TimedeltaIndex with day as the default.

  `period_range`

    Return a fixed frequency PeriodIndex.

  `DatetimeIndex.freq`

    Return the frequency object if it is set, otherwise None.

  Examples

      >>> idx = pd.date_range(start="2020/12/01", end="2020/12/30", periods=30)
      >>> pd.infer_freq(idx)
      'D'