Numpy Index Of Maximum
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Numpy Index Of Maximum
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NumPy Argmin Get Index Of The Min Value In Arrays Datagy
Def max indices arr k Returns the indices of the k first largest elements of arr in descending order in values assert k Use the axis keyword to get the indices of maximum and minimum values along a specific axis: >>> np . argmax ( a , axis = 0 ) array([[1, 1, 1, 1, 1], [1, 1, 1, 1, 1], [1, 1, 1, 1, 1]]) >>> np . argmax ( a , axis = 1 ) array([[2, 2, 2, 2, 2], [2, 2, 2, 2, 2]]) >>> np . argmax ( a , axis = 2 ) array([[4, 4, 4], [4, 4, 4]]) >>> np . argmin ( a .
Numpy Get Index Of Max Value In Array Data Science Parichay
Numpy Index Of MaximumNumpy has an argmax function that returns just that, although you will have to deal with the nan s manually. nan s always get sorted to the end of an array, so with that in mind you can do: a = np.random.rand(10000) a[np.random.randint(10000, size=(10,))] = np.nan. a = a.reshape(100, 100) def nanargmax(a): idx = np.argmax(a, axis=None) Axis 1 the index of the max element per row will be returned The following code will help you to better understand import numpy as np a np array 1 2 3 4 3 1 This will print the index of the max value for each column print a argmax axis 0 output 1 1 0 This will print the index of the max value for each row print a argmax
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