numpy.all() in Python Last Updated : 07 Mar, 2024 Comments Improve Suggest changes Like Article Like Report The numpy.all() function tests whether all array elements along the mentioned axis evaluate to True. Syntax: numpy.all(array, axis = None, out = None, keepdims = class numpy._globals._NoValue at 0x40ba726c) Parameters : array :[array_like]Input array or object whose elements, we need to test. axis : [int or tuple of ints, optional]Axis along which array elements are evaluated. The default (axis = None) is to perform a logical AND over all the dimensions of the input array. Axis may be negative, in which case it counts from the last to the first axis. out : [ndarray, optional]Output array with same dimensions as Input array, placed with result keepdims : [boolean, optional]If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the input array. If the default value is passed, then keepdims will not be passed through to the all method of sub-classes of ndarray, however any non-default value will be. If the sub-classes sum method does not implement keepdims any exceptions will be raised. Return : A new Boolean array as per 'out' parameter Code 1 : Python # Python Program illustrating # numpy.all() method import numpy as geek # Axis = NULL # True False # True True # True : False = False print("Bool Value with axis = NONE : ", geek.all([[True,False],[True,True]])) # Axis = 0 # True False # True True # True : False print("\nBool Value with axis = 0 : ", geek.all([[True,False],[True,True]], axis = 0)) print("\nBool : ", geek.all([-1, 4, 5])) # Not a Number (NaN), positive infinity and negative infinity # evaluate to True because these are not equal to zero. print("\nBool : ", geek.all([1.0, geek.nan])) print("\nBool Value : ", geek.all([[0, 0],[0, 0]])) Output : Bool Value with axis = NONE : False Bool Value with axis = 0 : [ True False] Bool : True Bool : True Bool Value : False Code 2 : Python # Python Program illustrating # numpy.all() method # Parameter : keepdims import numpy as geek # setting keepdims = True print("\nBool Value : ", geek.all([[1, 0],[0, 4]], True)) # setting keepdims = True print("\nBool Value : ", geek.all([[0, 0],[0, 0]], False)) Output : Bool Value : [False False] Bool Value : [False False] VisibleDeprecationWarning: using a boolean instead of an integer will result in an error in the future return umr_all(a, axis, dtype, out, keepdims) Note : These codes won't run on online IDE's. So please, run them on your systems to explore the working. Comment More infoAdvertise with us Next Article numpy.all() in Python M Mohit Gupta_OMG Improve Article Tags : Python Python-numpy Python numpy-Logic Functions Practice Tags : python Similar Reads numpy.any() in Python The numpy.any() function tests whether any array elements along the mentioned axis evaluate to True. Syntax : numpy.any(a, axis = None, out = None, keepdims = class numpy._globals._NoValue at 0x40ba726c) Parameters : array :[array_like]Input array or object whose elements, we need to test. axis : 3 min read Python NumPy Numpy is a general-purpose array-processing package. It provides a high-performance multidimensional array object, and tools for working with these arrays. 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