# NumPy indices() Method | Create Array of Indices

Last Updated : 05 Feb, 2024

The indices() method returns an array representing the indices of a grid.

It computes an array where the subarrays contain index values 0, 1, â€¦ varying only along the corresponding axis.

## Python3

 `import` `numpy as np  ` `  `  `gfg ``=` `np.indices((``2``, ``3``)) ` ` `  `print` `(gfg)`

Output :

`[[[0 0 0]  [1 1 1]] [[0 1 2]  [0 1 2]]]`

## Syntax

numpy.indices(dimensions, dtype, sparse = False)

Parameters

• dimensions : [sequence of ints] The shape of the grid.
• dtype: [dtype, optional] Data type of the result.
• sparse: [boolean, optional] Return a sparse representation of the grid instead of a dense representation. Default is False.

Return: [ndarray or tuple of ndarrays] If sparse is False: Returns one array of grid indices, grid.shape = (len(dimensions), ) + tuple(dimensions). If sparse is True: Returns a tuple of arrays, with grid[i].shape = (1, …, 1, dimensions[i], 1, …, 1) with dimensions[i] in the ith place

## How to Generate a Grid of Indices for a Given Shape in NumPy

To generate a grid of indices for a given shape we use numpy.indices() method of the NumPy library in Python.

Let us understand it better with an example:

## Python3

 `import` `numpy as np  ` `  `  `grid ``=` `np.indices((``2``, ``3``)) ` `gfg ``=` `grid[``1``] ` ` `  `print` `(gfg)`

Output :

`[[0 1 2] [0 1 2]]`

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