Parameters:
array: Input array or object having the elements to calculate the trimmed standard error of the mean .
axis: Axis along which the trimmed standard error of the mean 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 error of the mean of array elements based on the set parameters.

Code # 1:

# Cropped standard error   from scipy import stats import numpy as np    # array elements in the range from 0 to 19 x = np.arange ( 20 )   < code class = "functions"> print ( "Trimmed Standard error:" , stats.tsem (x))      print ( "Trimmed Standard error by setting limit: " ,    stats. tsem (x, ( 2 , 10 )))

Output:

 Trimmed Standard error: 1.32287565553 Trimmed Standard error by setting limit: 0.912870929175 

Code # 2: with multidimensional data, the () axis works

# Cropped standard error   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 error is with default axis = 0:" ,  stats.tsem (arr1, axis = 1 ))

Exit:

 Trimmed Standard error is with default axis = 0: 27.1476974115