# How to use numpy.argmax() in Python

In this tutorial, we will learn how to use numpy.argmax() in Python using a few simple examples.

## Using numpy.argmax() in Python

In Python, numpy.argmax() returns the indices of the maximum element of any given array in a particular axis. Let us see how it works with a simple example.

First, we need to import the library numpy into python and declare an array on which we will perform the operations.

# import numpy import numpy as np # declare an array a = [[41,83,46],[8,90,56],[54,76,16]]

Once we have declared an array, we are ready to use the syntax. Here, the syntax numpy.argmax(a, axis) has two parameters **array** and **axis**. Here, array is already declared. As soon as we declare the axis parameter, the array gets divided into rows and columns. Then, numpy checks the rows and columns individually.

**axis = 0 **means that the operation is performed down the columns whereas, **axis = 1 ** means that the operations is performed across the rows.

# Using np.argmax() syntax b = np.argmax(a, axis=0) print(b)

Output:

[2 1 1]

So, here we see that by providing the argument axis = 0, np.argmax() returns the indices of maximum elements of every column in the array. Now, let’s check using the axis = 1 argument.

# Using np.argmax() syntax b = np.argmax(a, axis=1) print(b)

Output:

[1 1 1]

As a result, we can see that this time, np.argmax() returns indices of the maximum element in every row of the given array.

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