numpy.minimum() in Python

Syntax : numpy.minimum(arr1, arr2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, ufunc 'minimum') Parameters : arr1 : [array_like] Input array. arr2 : [array_like] Input array. out : [ndarray, optional] A location into which the result is stored.   -> If provided, it must have a shape that the inputs broadcast to.   -> If not provided or None, a freshly-allocated array is returned. **kwargs : allows you to pass keyword variable length of argument to a function. It is used when we want to handle named argument in a function. where : [array_like, optional]True value means to calculate the universal functions(ufunc) at that position, False value means to leave the value in the output alone. Return : [ndarray or scalar] Result. The minimum of arr1 and arr2, element-wise. This is a scalar if both arr1 and arr2 are scalars.

# Python program explaining # minimum() function import numpy as geek in_num1 = 10 in_num2 = 21 print ("Input number1 : ", in_num1) print ("Input number2 : ", in_num2) out_num = geek.minimum(in_num1, in_num2) print ("minimum of 10 and 21 : ", out_num) 

Input number1 : 10 Input number2 : 21 minimum of 10 and 21 : 10 

# Python program explaining # minimum() function import numpy as geek in_arr1 = [2, 8, 125] in_arr2 = [3, 3, 15] print ("Input array1 : ", in_arr1) print ("Input array2 : ", in_arr2) out_arr = geek.minimum(in_arr1, in_arr2) print ("Output array after selecting minimum: ", out_arr) 

Input array1 : [2, 8, 125] Input array2 : [3, 3, 15] Output array after selecting minimum: [ 2 3 15] 

# Python program explaining # minimum() function import numpy as geek in_arr1 = [geek.nan, 0, geek.nan] in_arr2 = [geek.nan, geek.nan, 0] print ("Input array1 : ", in_arr1) print ("Input array2 : ", in_arr2) out_arr = geek.minimum(in_arr1, in_arr2) print ("Output array after selecting minimum: ", out_arr) 

Input array1 : [nan, 0, nan] Input array2 : [nan, nan, 0] Output array after selecting minimum: [ nan nan nan]