sciPy stats.tstd() function | Python (original) (raw)

Last Updated : 10 Feb, 2019

scipy.stats.tstd(array, limits=None, inclusive=(True, True)) calculates the trimmed standard deviation 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 standard deviation. axis: Axis along which the trimmed standard deviation 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 standard deviation of the array elements based on the set parameters.

Code #1:

Python3 `

Trimmed Standard Deviation

from scipy import stats import numpy as np

array elements ranging from 0 to 19

x = np.arange(20)

print("Trimmed Standard Deviation :", stats.tstd(x))

print("\nTrimmed Standard Deviation by setting limit : ", stats.tstd(x, (2, 10)))

`

Output:

Trimmed Standard Deviation : 5.9160797831

Trimmed Standard Deviation by setting limit : 2.73861278753

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

Python3 `

Trimmed Standard Deviation

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 Standard Deviation is with default axis = 0 : \n", stats.tstd(arr1, axis = 1))

`

Output:

Trimmed Standard Deviation is with default axis = 0 : 94.0423824505