sciPy stats.scoreatpercentile() function | Python (original) (raw)
Last Updated : 13 Feb, 2019
**scipy.stats.scoreatpercentile(a, score, kind='rank')** function helps us to calculate the score at a given percentile of the input array. The score at percentile = 50 is the median. If the desired quantile lies between two data points, we interpolate between them, according to the value of interpolation.
Parameters : arr : [array_like] input array. per : [array_like] Percentile at which we need the score. limit : [tuple] the lower and upper limits within which to compute the percentile.axis : [int] axis along which we need to calculate the score. Results : Score at Percentile relative to the array element.
Code #1:
Python3 1== `
scoreatpercentile
from scipy import stats import numpy as np
1D array
arr = [20, 2, 7, 1, 7, 7, 34, 3]
print("arr : ", arr)
print ("\nScore at 50th percentile : ", stats.scoreatpercentile(arr, 50))
print ("\nScore at 90th percentile : ", stats.scoreatpercentile(arr, 90))
print ("\nScore at 10th percentile : ", stats.scoreatpercentile(arr, 10))
print ("\nScore at 100th percentile : ", stats.scoreatpercentile(arr, 100))
print ("\nScore at 30th percentile : ", stats.scoreatpercentile(arr, 30))
`
Output:
arr : [20, 2, 7, 1, 7, 7, 34, 3]
Score at 50th percentile : 7.0
Score at 90th percentile : 24.2
Score at 10th percentile : 1.7
Score at 100th percentile : 34.0
Score at 30th percentile : 3.4
Code #2:
Python3 1== `
scoreatpercentile
from scipy import stats import numpy as np
arr = [[14, 17, 12, 33, 44],
[15, 6, 27, 8, 19],
[23, 2, 54, 1, 4, ]]
print("arr : ", arr)
print ("\nScore at 50th percentile : ", stats.scoreatpercentile(arr, 50))
print ("\nScore at 50th percentile : ", stats.scoreatpercentile(arr, 50, axis = 1))
print ("\nScore at 50th percentile : ", stats.scoreatpercentile(arr, 50, axis = 0))
`
Output:
arr : [[14, 17, 12, 33, 44], [15, 6, 27, 8, 19], [23, 2, 54, 1, 4]]
Score at 50th percentile : 15.0
Score at 50th percentile : [ 17. 15. 4.]
Score at 50th percentile : [ 15. 6. 27. 8. 19.]