NumPy argmax()

argmax() Syntax

The syntax of argmax() is:

numpy.argmax(array, axis = None, out = None, keepdims = <no value>)

argmax() Arguments

The argmax() method takes four arguments:

• array - input array
• axis (optional) - axis along which index is returned (int)
• out (optional) - array to store the output
• keepdims (optional) - whether to preserve the input array's dimension (bool)

argmax() Return Value

The argmax() method returns the index of the largest element.

Example 1: argmax() With String

The argmax() method with an array of string or char returns the index of the largest element based on ASCII value.

Output

2

Example 2: argmax() With 2D Array

The axis argument defines how we can handle the index of the largest element in a 2D array.

• If axis = None, the array is flattened and the index of the flattened array is returned.
• If axis = 0, the index of the largest element in each column is returned.
• If axis = 1, the index of the largest element in each row is returned.

Output

Index of the largest element in the flattened array:  2
Index of the largest element in each row (axis 0):  [1 0 0]
Index of the largest element in each row (axis 1):  [2 2]

Example 3: argmax() With 'out' Array

In our previous examples, the argmax() function generated a new array as output.

However, we can use an existing array to store the output using the out argument.

Output

[1 2 0]

Example 4: argmax() With keepdims

When keepdims = True, the dimensions of the resulting array matches the dimension of an input array.

Output

Shape of original array:  (2, 3)

Without keepdims: 
[2 2]
Shape of array: (2,)

With keepdims: 
[[2]
[2]]
Shape of array: (2, 1)

Without keepdims, the result is simply a one-dimensional array of indices.

With keepdims, the resulting array has the same number of dimensions as the input array.

Similarly, with axis = 1 and keepdims = True, the resulting array has the same number of rows as the input array, but its columns have a single element i.e. the index of the largest element in that column.