scoreatpercentile#
- scipy.stats.scoreatpercentile(a, per, limit=(), interpolation_method='fraction', axis=None)[source]#
Calculate the score at a given percentile of the input sequence.
For example, the score at
per=50is the median. If the desired quantile lies between two data points, we interpolate between them, according to the value of interpolation. If the parameter limit is provided, it should be a tuple (lower, upper) of two values.- Parameters:
- aarray_like
A 1-D array of values from which to extract score.
- perarray_like
Percentile(s) at which to extract score. Values should be in range [0,100].
- limittuple, optional
Tuple of two scalars, the lower and upper limits within which to compute the percentile. Values of a outside this (closed) interval will be ignored.
- interpolation_method{‘fraction’, ‘lower’, ‘higher’}, optional
Specifies the interpolation method to use, when the desired quantile lies between two data points i and j The following options are available (default is ‘fraction’):
‘fraction’:
i + (j - i) * fractionwherefractionis the fractional part of the index surrounded byiandj‘lower’:
i‘higher’:
j
- axisint, optional
Axis along which the percentiles are computed. Default is None. If None, compute over the whole array a.
- Returns:
- scorefloat or ndarray
Score at percentile(s).
See also
Notes
This function will become obsolete in the future. For NumPy 1.9 and higher,
numpy.percentileprovides all the functionality thatscoreatpercentileprovides. And it’s significantly faster. Therefore it’s recommended to usenumpy.percentilefor users that have numpy >= 1.9.Examples
>>> import numpy as np >>> from scipy import stats >>> a = np.arange(100) >>> stats.scoreatpercentile(a, 50) 49.5