One of the most beneficial but straightforward indexing routines in NumPy is the npindex(). This routine provides us iterator that returns the indices of elements in an N-dimensional array.

This short article will discuss the ndindex() routine and its use in NumPy.

## Syntax

The syntax of the ndindex routine is as shown:

1 | class numpy.ndindex(*shape) |

## Parameters

It accepts the shape of the array as a scalar integer or tuple of integers.

## Example #1

Consider the example shown below:

1 2 | for index in np.ndindex(2,3): print(index) |

In this case, we use the ndindex function to get the index of the elements in an array of shapes (2,3).

The above code should return:

1 2 3 4 5 6 | (0, 0) (0, 1) (0, 2) (1, 0) (1, 1) (1, 2) |

## Example #2

We can also pass the shape as a single tuple. For example:

1 2 3 | arr = np.array([[1,2,3], [4,5,6]]) for index in np.ndindex((arr.shape)): print(index) |

Here, we use the arr.shape property as the value of the ndindex() function.

## Closing

In this one, we covered the ndindex() function in NumPy and how to use it. Feel free to explore the docs to learn more.

Happy coding!!