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) * fractionwhere- fractionis the fractional part of the index surrounded by- iand- j
- ‘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 that- scoreatpercentileprovides. And it’s significantly faster. Therefore it’s recommended to use- numpy.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