# sciPy function stats.trimboth () | python

scipy.stats.trimboth (a, proportional cut, axis = 0) function cuts off part of the elements in the array from both 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: Work

 ` # stats.trimboth () method ` ` import ` ` numpy as np ` ` from ` ` scipy ` ` import ` ` stats `   ` arr1 ` ` = ` ` [` ` 0 ` `, ` ` 1 ` `, ` ` 2 ` `, ` ` 3 , 4 , 5 , 6 , 7 , 8 , 9 ] ``      print ( "arr1:" , arr1)   print ( "clipped arr1:" , stats.trimboth (arr1, proportiontocut = . 3 )) print ( "clipped arr1:" , 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:

 ` # stats.trimboth () method ` ` import ` ` numpy as np ` ` from ` ` scipy ` ` import ` ` stats `     ` arr1 ` ` = ` ` [[` ` 0 ` `, ` ` 12 ` `, ` ` 21 ` `, ` ` 3 ` `, ` ` 14 ` ` ], ` ` [` ` 53 ` `, ` ` 16 ` `, ` ` 37 ` `, ` ` 85 ` `, ` ` 39 ` `]] `   ` print ` ` (` ` "arr1:" ` `, arr1) `   ` print ` ` (` ` "clipped arr1:" ` `, ` ` stats.trimboth (arr1, proportiontocut ` ` = ` `. ` ` 3 ` `)) `   ` print ` ` (` ` "clipped arr1:" ` `, ` ` stats.trimboth (arr1, proportiontocut ` ` = ` `. ` ` 1 ` `)) ` ` `  ` print ` ` (` ` "clipped arr1:" ` `, ` ` s tats.trimboth (arr1, proportiontocut ` ` = ` `. ` ` 1 ` `, axis ` ` = ` ` 1 ` `)) `   ` print ` ` (` `" clipped arr1: "` `, ` ` ` ` 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]] cli pped 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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