scipy.stats.tmin (array, lowerlimit = None, axis = 0, inclusive = True) calculates the truncated minimum of array elements, and also ignores values ​​lying outside specified limits, along a specified axis.

Parameters:
array: Input array or object having the elements to calculate the minimum .
axis: [Default is zero] Input array or object having the elements to calculate the minimum.
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.
inclusive: Decide whether to include the values ​​equal to lower or upper bound, or to exclude them while calculation.

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

Code # 1:

# Low cut   from scipy import stats import numpy as np    # array elements in the range from 0 to 19 x = [ 1 , 3 , 27 , 56 , 2 , 4 , 13 , 3 , 6 ]   print ( "Trimmed Minimum:" , stats.tmin (x))      print ( " Trimmed Minimum by setting limit: " ,    stats.tmin (x, ( 5 )) )

Exit:

 Trimmed Minimum : 1 Trimmed Minimum by setting limit: 6 

Code # 2: Check various parameters

# Cropped minimum   from scipy import stats import numpy as np    # array elements ranging from 0 to 19 x = [[ 1 , 3 , 27 ],  [ 3 , 4 , 7 ],  [ 7 , 6 , 3 ],    [ 3 , 6 , 8 ]]   print ( "Trimmed Minimum:" , stats.tmin (x))     # setting the axis print ( " Trimmed Minimum by setting axis: " ,  stats.tmin (x, axis = 1 ))   print ( "Trimmed Minimum by setting axis:" ,  stats.tmin (x, axis = 0 ))    # mouth Limit setting print ( "Trimmed Minimum by setting limit: " ,    stats.tmin (x, ( 5 ), axis = 1 ))     print ( "Trimmed Minimum by setting limit:" ,    stats.tmin (x, ( 5 ), axis = 0 ))

Exit:

 Trimmed M inimum: [1 3 3] Trimmed Minimum by setting axis: [1 3 3 3] Trimmed Minimum by setting axis: [1 3 3] Trimmed Minimum by setting limit: [27 7 6 6] Trimmed Minimum by setting limit: [7 6 7]