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# How to get the number of dimensions of a matrix using NumPy in Python?

• Last Updated : 30 Sep, 2022

In this article, we will discuss how to get the number of dimensions of a matrix using NumPy. It can be found using the ndim parameter of the ndarray() method.

Syntax: no_of_dimensions = numpy.ndarray.ndim

Approach:

• Create an n-dimensional matrix using the NumPy package.
• Use ndim attribute available with the NumPy array as numpy_array_name.ndim to get the number of dimensions.
• Alternatively, we can use the shape attribute to get the size of each dimension and then use len() function for the number of dimensions.
• Use numpy.array() function to convert a list to a NumPy array and use one of the above two ways to get the number of dimensions.

## Get the Number of 1-Dimensions of a Matrix

Creating a 1D array using np.arrange and printing the dimension of an array.

## Python3

 `import` `numpy as np` `# create numpy arrays``# 1-d numpy array``_1darr ``=` `np.arange(``4``)     ``print``(_1darr)` `# printing the 1-dimensions numpy array``print``(``"Dimensions in _1darr are: "``, _1darr.ndim)`

Output:

```[0 1 2 3]
Dimensions in _1darr are:  1v```

## Get the Number of 2-Dimensions of a Matrix

Creating a 2D array using np.arrange and printing the dimension of an array.

## Python3

 `import` `numpy as np` `x ``=` `np.arange(``12``).reshape((``3``, ``4``))``print``(``"Matrix: \n"``, x)``  ` `print``(``"Dim: "``, x.ndim)`

Output:

```Matrix:
[[ 0  1  2  3]
[ 4  5  6  7]
[ 8  9 10 11]]
Dim:  2```

## Get the Number of 3-Dimensions of a Matrix

Creating a 3D array using np.arrange and np.reshape. After that, we are printing the dimension of an array using shape and len().

## Python3

 `import` `numpy as np` `# 3-d numpy array``_3darr ``=` `np.arange(``18``).reshape((``3``, ``2``, ``3``)) ` `# printing the dimensions of each numpy array``print``(``"Dimensions in _3darr are: "``, _3darr.ndim)``print``(_3darr)` `# numpy_arr.shape is the number of elements in``# each dimension numpy_arr.shape returns a tuple``# len() of the returned tuple is also gives number``# of dimensions``print``(``"Dimensions in _3darr are: "``, ``len``(_3darr.shape))`

Output:

```Dimensions in _3darr are:  3
[[[ 0  1  2]
[ 3  4  5]]

[[ 6  7  8]
[ 9 10 11]]

[[12 13 14]
[15 16 17]]]
Dimensions in _3darr are:  3```

## Convert a list to a Numpy Array and Get a Dimensions of a Matrix

Creating a list of 1D and 2D, using np.arrange we are converting it into a np.array and printing the dimension of an array.

## Python3

 `import` `numpy as np` `# Use numpy.array() function to convert a list to``# numpy array``__1darr ``=` `np.array([``5``, ``4``, ``1``, ``3``, ``2``])``__2darr ``=` `np.array([[``5``, ``4``],[``1``,``2``], [``4``,``5``]])``print``(``"Dimensions in __1darr are: "``, __1darr.ndim)``print``(``"Dimensions in __2darr are: "``, __2darr.ndim)`

Output:

```Dimensions in __1darr are:  1
Dimensions in __2darr are:  2```

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