# sciPy stats.trimboth() function | Python

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

 `# 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:

 `# 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]]
```

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