numpy.maximum() in Python Last Updated : 28 Nov, 2018 Comments Improve Suggest changes Like Article Like Report numpy.maximum() function is used to find the element-wise maximum of array elements. It compares two arrays and returns a new array containing the element-wise maxima. 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.maximum(arr1, arr2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, ufunc 'maximum') 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 maximum of arr1 and arr2, element-wise. This is a scalar if both arr1 and arr2 are scalars. Code #1 : Working Python # Python program explaining # maximum() function import numpy as geek in_num1 = 10 in_num2 = 21 print ("Input number1 : ", in_num1) print ("Input number2 : ", in_num2) out_num = geek.maximum(in_num1, in_num2) print ("maximum of 10 and 21 : ", out_num) Output : Input number1 : 10 Input number2 : 21 maximum of 10 and 21 : 21 Code #2 : Python # Python program explaining # maximum() 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.maximum(in_arr1, in_arr2) print ("Output array after selecting maximum: ", out_arr) Output : Input array1 : [2, 8, 125] Input array2 : [3, 3, 15] Output array after selecting maximum: [ 3 8 125] Code #3 : Python # Python program explaining # maximum() 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.maximum(in_arr1, in_arr2) print ("Output array after selecting maximum: ", out_arr) Output : Input array1 : [nan, 0, nan] Input array2 : [nan, nan, 0] Output array after selecting maximum: [ nan nan nan] Comment More infoAdvertise with us Next Article numpy.maximum() in Python J jana_sayantan Follow Improve Article Tags : Python Python-numpy Python numpy-Mathematical Function Practice Tags : python Similar Reads numpy.fmax() in Python numpy.fmax() function is used to compute element-wise maximum of array elements. This function compare two arrays and returns a new array containing the element-wise maxima. 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.nanargmax() in Python The numpy.nanargmax() function returns indices of the max 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.nanargmax(array, axis = None) Parameters : array : Input array to work on axis : [int, optional]Al 2 min read numpy.amax() in Python The numpy.amax() method returns the maximum of an array or maximum along the axis(if mentioned). Syntax: numpy.amax(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 ma 2 min read numpy.maximum_sctype() function – Python numpy.maximum_sctype() function return the scalar type of highest precision of the same kind as the input. Syntax : numpy.maximum_sctype(t) Parameters : t : [dtype or dtype specifier] The input data type. This can be a dtype object or an object that is convertible to a dtype. Return : [dtype] The hi 1 min read numpy.argmax() in Python The numpy.argmax() function returns indices of the max element of the array in a particular axis. Syntax : numpy.argmax(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 ins 3 min read Like