pandas.Series.quantile — pandas 2.2.3 documentation (original) (raw)

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

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(.5) 2.5 s.quantile([.25, .5, .75]) 0.25 1.75 0.50 2.50 0.75 3.25 dtype: float64