Open In App
Related Articles

sciPy stats.tmean() | Python

Improve Article
Save Article
Like Article

scipy.stats.tmean(array, limits=None, inclusive=(True, True)) calculates the trimmed mean of the array elements along the specified axis of the array.

It’s 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:

# Trimmed Mean 
from scipy import stats
import numpy as np 
# array elements ranging from 0 to 19
x = np.arange(20)
print("Trimmed Mean :", stats.tmean(x)) 
print("\nTrimmed Mean by setting limit : "
      stats.tmean(x, (2, 10)))


Trimmed Mean : 9.5

Trimmed Mean by setting limit :  6.0

Code #2: With multi-dimensional data, axis() working

# Trimmed 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("\nTrimmed Mean is with default axis = 0 : \n"
      stats.tmean(arr1, axis = 1))


Trimmed Mean is with default axis = 0 : 

Whether you're preparing for your first job interview or aiming to upskill in this ever-evolving tech landscape, GeeksforGeeks Courses are your key to success. We provide top-quality content at affordable prices, all geared towards accelerating your growth in a time-bound manner. Join the millions we've already empowered, and we're here to do the same for you. Don't miss out - check it out now!

Last Updated : 10 Feb, 2019
Like Article
Save Article
Similar Reads
Complete Tutorials