pandas.Series.quantile — pandas 0.24.0rc1 documentation (original) (raw)

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

Return value at the given quantile.

Parameters:	q : float or array-like, default 0.5 (50% quantile) 0 <= q <= 1, the quantile(s) to compute interpolation : {‘linear’, ‘lower’, ‘higher’, ‘midpoint’, ‘nearest’} New in version 0.18.0. 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.
Returns:	quantile : float or Series if q is an array, a Series will be returned where the index is q and the values are the quantiles.

Parameters:

q : float or array-like, default 0.5 (50% quantile) 0 <= q <= 1, the quantile(s) to compute interpolation : {‘linear’, ‘lower’, ‘higher’, ‘midpoint’, ‘nearest’} New in version 0.18.0. 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.

Returns:

quantile : float or Series if q is an array, a Series will be returned where the index is q and the values are the quantiles.

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