# sciPy function stats.scoreatpercentile () | python

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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.] `

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