Series.quantile()

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

Return value at the given quantile, a la numpy.percentile.

Parameters:

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.

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.

>>> s = 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

Links:

doc_Pandas

2017-01-12 04:54:30

Comments