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scipy stats.tmin() function | Python

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scipy.stats.tmin(array, lowerlimit=None, axis=0, inclusive=True) function calculates the trimmed minimum of the array elements along with ignoring the values lying outside the specified limits, along the 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:




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


Output:

Trimmed Minimum : 1

Trimmed Minimum by setting limit :  6

 
Code #2: Checking different parameters




# Trimmed 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 axis
print("\nTrimmed Minimum by setting axis : "
      stats.tmin(x, axis = 1))
  
print("\nTrimmed Minimum by setting axis : "
      stats.tmin(x, axis = 0))
  
# setting limit
print("\nTrimmed Minimum by setting limit : "
      stats.tmin(x, (5), axis = 1))
  
  
print("\nTrimmed Minimum by setting limit : "
      stats.tmin(x, (5), axis = 0))


Output:

Trimmed Minimum : [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]


Last Updated : 07 Feb, 2019
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