sciPy stats.trimboth() function | Python
Last Updated :
20 Feb, 2019
scipy.stats.trimboth(a, proportiontocut, axis=0) function slices off the portion of elements in the array from both the ends.
Parameters :
arr : [array_like] Input array or object to trim.
axis : Axis along which the mean is to be computed. By default axis = 0.
proportiontocut : Proportion (in range 0-1) of data to trim of each end.
Results : trimmed array elements from both the ends in the given proportion.
Code #1: Working
import numpy as np
from scipy import stats
arr1 = [ 0 , 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 ]
print ( "\narr1 : " , arr1)
print ( "\nclipped arr1 : \n" , stats.trimboth(arr1, proportiontocut = . 3 ))
print ( "\nclipped arr1 : \n" , stats.trimboth(arr1, proportiontocut = . 1 ))
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Output :
arr1 : [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
clipped arr1 :
[3 4 5 6]
clipped arr1 :
[1 3 2 4 5 6 7 8]
Code #2:
import numpy as np
from scipy import stats
arr1 = [[ 0 , 12 , 21 , 3 , 14 ],
[ 53 , 16 , 37 , 85 , 39 ]]
print ( "\narr1 : " , arr1)
print ( "\nclipped arr1 : \n" ,
stats.trimboth(arr1, proportiontocut = . 3 ))
print ( "\nclipped arr1 : \n" ,
stats.trimboth(arr1, proportiontocut = . 1 ))
print ( "\nclipped arr1 : \n" ,
stats.trimboth(arr1, proportiontocut = . 1 , axis = 1 ))
print ( "\nclipped arr1 : \n" ,
stats.trimboth(arr1, proportiontocut = . 1 , axis = 0 ))
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Output :
arr1 : [[0, 12, 21, 3, 14], [53, 16, 37, 85, 39]]
clipped arr1 :
[[ 0 12 21 3 14]
[53 16 37 85 39]]
clipped arr1 :
[[ 0 12 21 3 14]
[53 16 37 85 39]]
clipped arr1 :
[[ 0 3 12 14 21]
[16 37 39 53 85]]
clipped arr1 :
[[ 0 12 21 3 14]
[53 16 37 85 39]]
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