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

Return value at the given quantile.

qfloat 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) * fraction, where fraction is the fractional part of the index surrounded by i and j.

  • lower: i.

  • higher: j.

  • nearest: i or j whichever is nearest.

  • midpoint: (i + j) / 2.

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


Calculate the rolling quantile.


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


>>> s = pd.Series([1, 2, 3, 4])
>>> s.quantile(.5)
>>> s.quantile([.25, .5, .75])
0.25    1.75
0.50    2.50
0.75    3.25
dtype: float64