numpy.minimum() in Python Last Updated : 28 Nov, 2018 Comments Improve Suggest changes Like Article Like Report numpy.minimum() function is used to find the element-wise minimum of array elements. It compare two arrays and returns a new array containing the element-wise minima. If one of the elements being compared is a NaN, then that element is returned. If both elements are NaNs then the first is returned. 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. Code #1 : Working Python # 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) Output : Input number1 : 10 Input number2 : 21 minimum of 10 and 21 : 10 Code #2 : Python # 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) Output : Input array1 : [2, 8, 125] Input array2 : [3, 3, 15] Output array after selecting minimum: [ 2 3 15] Code #3 : Python # 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) Output : Input array1 : [nan, 0, nan] Input array2 : [nan, nan, 0] Output array after selecting minimum: [ nan nan nan] Comment More infoAdvertise with us Next Article numpy.minimum() in Python J jana_sayantan Follow Improve Article Tags : Python Python-numpy Python numpy-Mathematical Function Practice Tags : python Similar Reads numpy.fmin() in Python numpy.fmin() function is used to compute element-wise minimum of array elements. This function compare two arrays and returns a new array containing the element-wise minima. If one of the elements being compared is a NaN, then the non-nan element is returned. If both elements are NaNs then the first 2 min read numpy.nanmin() in Python numpy.nanmin()function is used when to returns minimum value of an array or along any specific mentioned axis of the array, ignoring any Nan value. Syntax : numpy.nanmin(arr, axis=None, out=None) Parameters : arr :Input array. axis :Axis along which we want the min value. Otherwise, it will consider 2 min read numpy.amin() in Python The numpy.amin() function returns minimum of an array or minimum along axis(if mentioned). Syntax : numpy.amin(arr, axis = None, out = None, keepdims = <class numpy._globals._NoValue>) Parameters : arr : [array_like]input dataaxis : [int or tuples of int]axis along which we want the min value. 2 min read numpy.argmin() in Python The numpy.argmin() method returns indices of the min element of the array in a particular axis. Syntax : numpy.argmin(array, axis = None, out = None) Parameters : array : Input array to work on axis : [int, optional]Along a specified axis like 0 or 1 out : [array optional]Provides a feature to inser 2 min read numpy.nanargmin() in Python The numpy.nanargmin() function returns indices of the min element of the array in a particular axis ignoring NaNs. The results cannot be trusted if a slice contains only NaNs and Infs. Syntax:  numpy.nanargmin(array, axis = None) Parameters : array : Input array to work on axis : [int, optional]A 2 min read Like