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# pandas.Series.quantile

Series.quantile(q=0.5, interpolation='linear')

  Return value at the given quantile.

  This method computes the value below which a given fraction of the data falls. When multiple quantiles are requested, a Series indexed by the quantile values is returned.

  Parameters:
    q float or array-like, default 0.5 (50% quantile)

      The quantile(s) to compute, which can lie in range: 0 <= q <= 1.

    interpolation{‘linear’, ‘lower’, ‘higher’, ‘midpoint’, ‘nearest’}

      This optional parameter specifies the interpolation method to use, when the desired quantile lies between two data points i and j:

      > - linear: i + (j - i) * (x-i)/(j-i), where (x-i)/(j-i) is the fractional part of the index surrounded by i > j.

      > - lower: i.

      > - higher: j.

      > - nearest: i or j whichever is nearest.

      > - midpoint: (i + j) / 2.

  Returns:
    float or Series

      If `q` is an array, a Series will be returned where the index is `q` and the values are the quantiles, otherwise a float will be returned.

  See also

  `core.window.Rolling.quantile`

    Calculate the rolling quantile.

  `numpy.percentile`

    Returns the q-th percentile(s) of the array elements.

  Examples

      >>> s = pd.Series([1, 2, 3, 4])
      >>> s.quantile(0.5)
      2.5
      >>> s.quantile([0.25, 0.5, 0.75])
      0.25    1.75
      0.50    2.50
      0.75    3.25
      dtype: float64