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

Python3 1==

# stats.trimboth() method   
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))

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:

Python3 1==

# stats.trimboth() method   
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))

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]]