# sciPy stats.tvar() function | Python

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``))) `

Output:

```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``)))  `

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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