sciPy stats.tstd() function | Python
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:
from scipy import stats
import numpy as np
x = np.arange( 20 )
print ( "Trimmed Standard Deviation :" , stats.tstd(x))
print ( "\nTrimmed Standard Deviation by setting limit : " ,
stats.tstd(x, ( 2 , 10 )))
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Output:
Trimmed Standard Deviation : 5.9160797831
Trimmed Standard Deviation by setting limit : 2.73861278753
Code #2: With multi-dimensional data, axis() working
from scipy import stats
import numpy as np
arr1 = [[ 1 , 3 , 27 ],
[ 5 , 3 , 18 ],
[ 17 , 16 , 333 ],
[ 3 , 6 , 82 ]]
print ( "Trimmed Standard Deviation is with default axis = 0 : \n" ,
stats.tstd(arr1, axis = 1 ))
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Output:
Trimmed Standard Deviation is with default axis = 0 :
94.0423824505
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