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:
# Trimmed Variance from scipy import stats
import numpy as np
# array elements ranging from 0 to 19 x = np.arange( 20 )
print ( "Trimmed Variance :" , stats.tvar(x))
print ( "\nTrimmed Variance by setting limit : " ,
stats.tvar(x, ( 2 , 10 )))
|
Trimmed Variance : 35.0 Trimmed Variance by setting limit : 7.5
Code #2: Checking “inclusive” flags
# Trimmed Variance from scipy import stats
import numpy as np
# array elements ranging from 0 to 19 x = np.arange( 20 )
# Setting limits print ( "\nTrimmed Variance by setting limit : " ,
stats.tvar(x, ( 2 , 10 )))
# using flag 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 )))
|
Trimmed Variance by setting limit : 7.5 Trimmed Variance by setting limit : 6.0 Trimmed Variance by setting limit : 9.16666666667