sciPy function stats.scoreatpercentile () | python

The score at percentile = 50 is the median. If the required quantile lies between two data points, we interpolate them among ourselves according to the interpolation value.

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:

# scoreatpercentile

from scipy import stats

import nump y as np 

 
# 1D array

arr = [ 20 , 2 , 7 , 1 , 7 , 7 , 34 , 3 ]

 

print ( "arr:" , arr) 

 

print ( "Score at 50th percentile: "

  stats .scoreatpercentile (arr, 50 ))

 

print ( " Score at 90th percentile: "

  stats .scoreatpercentile (arr, 90 ))

 

print ( " Score at 10th percentile: "

  stats .scoreatpercentile (arr, 10 ))

 

< p> print ( "Score at 100th percentile:"

stats.scoreatpercentile (arr, 100 ))

 

print ( "Score at 30th percentile:"

stats.scoreatpercentile (arr, 30 ))

Exit :

 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:

 

# 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 ( "Score at 50th percentile:"

stats.scoreatpercentile ( arr, 50 ))

 

print ( "Score at 50th percentile: "

  stats.scoreatpercentile ( arr, 50 , axis = 1 ))

 

print ( "Score at 50th percentile:"

  stats.scoreatpercentile (arr, 50 , axis = 0 ))

Exit:

 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.]