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  2. sciPy stats.tmean () | python

sciPy stats.tmean () | python



This is the formula —

Parameters:
array: Input array or object having the elements to calculate the trimmed mean.
axis: Axis along which the trimmed mean is to be computed. By default axis = 0.
limits: Lower and upper bound of the array to consider, values ​​less than the lower limit or greater than the upper limit will be ignored. If limits is None [default], then all values ​​are used.

Returns: Trimmed mean of the array elements based on the set parameters.

Code # 1:

# Truncated mean

 

from scipy import stats

import numpy as np 

 
# array elements in the range from 0 to 19

x = np.arange ( 20 )

 

print ( "Trimmed Mean:" , stats.tmean (x)) 

 

 

print ( "Trimmed Mean by setting limit:" , 

  stats.tmean (x, ( 2 , 10 )))

Exit:

 Trimmed Mean: 9.5 Trimmed Mean by setting limit: 6.0

Code # 2: with multidimensional data, the () axis works

Exit:

 Trimmed Mean is with default axis = 0: 42.8333333333

# Truncated mean

 

from scipy import stats

import numpy as np 

  

arr1 = [[ 1 , 3 , 27 ], 

  [ 5 , 3 , 18 ], 

[ 17 , 16 , 333 ], 

[ 3 , 6 , 82 ]] 

 

 
# using axis = 0

print ( "Trimmed Mean is with default axis = 0:" , 

stats.tmean (arr1, axis = 1 ))