scipy.stats.tvar(array, limits=None, inclusive=(1, 1)) function calculates the trimmed variance of the array elements along with ignoring the values lying outside the specified limits.
It’s formula –

Parameters :
array: Input array or object having the elements to calculate the trimmed variance.
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 : Trimmed variance 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 Variance :" , stats.tvar(x))
print ( "\nTrimmed Variance by setting limit : " ,
stats.tvar(x, ( 2 , 10 )))
|
Output:
Trimmed Variance : 35.0
Trimmed Variance by setting limit : 7.5
Code #2: Checking “inclusive” flags
from scipy import stats
import numpy as np
x = np.arange( 20 )
print ( "\nTrimmed Variance by setting limit : " ,
stats.tvar(x, ( 2 , 10 )))
print ( "\nTrimmed Variance by setting limit : " ,
stats.tvar(x, ( 2 , 10 ), ( False , True )))
print ( "\nTrimmed Variance by setting limit : " ,
stats.tvar(x, ( 2 , 12 ), ( True , False )))
|
Output:
Trimmed Variance by setting limit : 7.5
Trimmed Variance by setting limit : 6.0
Trimmed Variance by setting limit : 9.16666666667
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Last Updated :
07 Feb, 2019
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