pandas.Series.quantile

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

Return value at the given quantile.

Parameters:

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) * (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