Python Shape Of An Array

In this Python tutorial, we will learn the Python shape of an array, and also we will cover these topics:

Python shape of a 2D array
Python shape of a nested array
Python shape and type of N-d array
Python reshape of a multidimensional array
Python shape of a 3D array
Python index array
Python print the shape of a multidimensional array
Python transpose of 1D array
Python change the shape of a 1D array to a 3D array
Python change the shape of an array

Table of Contents

Python shape of a 2D array

Here, we can see shape of a 2D array in python.

In this example, I have imported a module called numpy as np. The NumPy library is used to work with an array.
I have taken a variable as an array and I have assigned an array as array = np.array([[1, 2, 3, 4, 5], [5, 6, 7, 8, 9]]).
And I have used np.array to get the dimensions of an array, the shape property is used to get the current shape of an array. to get the output I have to print(array.shape).

Example:

import numpy as np
array = np.array([[1, 2, 3, 4, 5], [5, 6, 7, 8, 9]])
print(array.shape)

We can see the output (2, 5) because there is 2 array which consists of 5 elements in it, which is the shape of an array. You can refer to the below screenshot for the output.

Python shape of a nested array

Here, we can see how to find the shape of a nested array in python.

In this example, I have imported a module called numpy as np. The NumPy library is used to work with an array and created a variable called an array.
The variable array is assigned as array = np.zeros((5,3)), the np.zeros are used to get an array of a given size and shape filled with zeros.
The ((5,3)) is the size and shape of an array, to get the output I have used print(array).

Example:

import numpy as np
array = np.zeros((5,3))
print(array)

In the below screenshot, you can see the array with size of (5,3) with zeros.

Python shape and type of N-d array

Now we can see how to find the shape and type of N-d array in python.

In this example, I have imported a module called numpy as np. The NumPy library is used to work with an array.
Taken a variable as x and assigned an array as x = np.array([[1, 2, 4],[3, 4, 5],[4, 5, 6]]).
The np.array is used to find the dimension of an array, and variable a = x.shape is used to find the shape of an array and variable b = x.dtype is used to find the type of an array.
To get the output as a shape I have used print(a) and to get the output as a datatype, I have used print(b).

Example:

import numpy as np
x = np.array([[1, 2, 4],[3, 4, 5],[4, 5, 6]])
a = x.shape
b = x.dtype
print(a)
print(b)

In the below screenshot, you can see the shape and datatype of an array as the output.

Python reshape of a multidimensional array

Now, we can see how to reshape of a multidimensional array in python.

In this example, I have imported a module called numpy as np. The NumPy library is used to work with an array.
And assigned a variable x as x = np.array([[ 0, 1, 3, 4],[ 4, 5, 6, 7],[ 8, 9, 10, 11],[12,13,14,15,]]).
The np.array is used to find the dimension of an array, and for the variable array, I have assigned it as array = x.reshape(4, 2, 2).
The reshape() function is used to give a new shape for an array without changing the data.
The (4,2,2) 4 is no of elements in the array 2 is the row and another 2 is a column, to get the output I have used print(array).

Example:

import numpy as np
x = np.array([[ 0,  1, 3, 4],[ 4,  5, 6, 7],[ 8,  9, 10, 11],[12,13,14,15,]])
array = x.reshape(4, 2 , 2)
print(array)

In the below screenshot, you can see the output as reshaped array.

Python reshape of a multidimensional array

Python shape of a 3D array

Here, we can see how to get the shape of a 3D array in python.

In this example, I have imported a module called numpy as np. The NumPy library is used to work with an array.
And assigned a variable array_3d as array_3d = np.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]], [[9, 10], [11, 12]]]).
The np. array is used to get the dimension of the array, to get the output I have used print(array_3d.shape).

Example

import numpy as np
array_3d = np.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]], [[9, 10], [11, 12]]])
print(array_3d.shape)

We can see the shape 3d array as the output in the below screenshot.

Python index array

Here, we can see index array in python.

In this example, I have imported a module called numpy as np. The NumPy library is used to work with an array.
And assigned a variable array as array = np.arange(20,2,-2).
The np.arange is an inbuilt numpy function that returns a ndarray object containing a spaced value with a defined interval.
The (20,2,-2) is the range given between 20 to 2 with the difference value -2.
To get the output I have used print(array).

Example:

import numpy as np
array = np.arange(20,2,-2)
print(array)

We can see the output as the array from range 20 to 2 with 2 difference value between them. You can refer to the below screenshot for the output.

Python print shape of a multidimensional array

Here, we can how to print the shape of a multidimensional array in python.

In this example, I have imported a module called numpy as np. The NumPy library is used to work with an array.
I have taken three variables as array1 = np.array([[1,2]]), and array2 = np.array([[1, 3], [2, 4]]), and array3 = np.array([[1, 3, 5, 7], [2, 4, 6, 8], [3, 6, 9, 12]]) with all the three with different dimensions.
The np.array is used to get the dimension of an array.
To get the ouput I have used print(array1.shape), print(array2.shape), print(array3.shape).

Example:

import numpy as np
array1 = np.array([[1,2]])
array2 = np.array([[1, 3], [2, 4]]) 
array3 = np.array([[1, 3, 5, 7], [2, 4, 6, 8],  [3, 6, 9, 12]]) 
print(array1.shape) 
print(array2.shape) 
print(array3.shape)

In the below screenshot, you can see the shape of multi dimensional array as the output.

Python print the shape of a multidimensional array

Python transpose of 1D array

Now, we can see how to transpose 1D array in python.

In this example, I have imported a module called numpy as np. The NumPy library is used to work with an array.
The variable array is assigned as array = np.arange(4).
The np.arange is an inbuilt numpy function that returns a ndarray object containing a spaced value with a defined interval 4 is the range of an array.
To transpose an array I have used the transpose() function. To get the output I have used print(array.transpose()).

Example:

import numpy as np
array = np.arange(4)
print(array.transpose())

You can see the array of range 4 as the output. You can refer to the below screenshot for the output.

Python change shape of a 1D array to a 3D array

Now, we can see how to change the shape of a 1D array to a 3D array in python.

In this example, I have imported a module called numpy as np and assigned, the variable array as array = np.array([2,4,6,8,10,12,14,16,18,20,22,24]). The np.array is used to get the dimension of an array.
To change the shape of an array I have created another variable as array_3d and assigned array_3d = array.reshape(2, 3, 2).
The reshape() function is used to get the new shape for an array without changing the data. To get the output I have used print(array_3d).

Example:

import numpy as np
array = np.array([2,4,6,8,10,12,14,16,18,20,22,24])
array_3d = array.reshape(2, 3, 2)
print(array_3d)

The input array was of 1d array and in the output you can see 3d array. You can refer to the below screenshot for the output.

Python change shape of an array

Now, we can see how to change the shape of an array in python.

In this example, I have imported a module called numpy as np and assigned, the variable array as array = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]) .
The np.array is used to get the dimension of an array.
To change the shape of an array I have created another variable as newarray and assigned newarray = array.reshape(3, 4). Here 3 is the number of rows and 4 is the number of columns.
The reshape() function is used to get the new shape for an array without changing the data. To get the output, I have used print(newarray).

Example:

import numpy as np
array = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12])
newarray = array.reshape(3, 4)
print(newarray)

The given array is changed to the array of range (3,4). You can refer to the below screenshot for the output.

Python change shape of an array — Python change the shape of an array

You may like the following Python tutorials:

In this tutorial, we have learned about the Python shape of an array, and also we have covered these topics:

Python shape of a 2D array
Python shape of a nested array
Python shape and type of N-d array
Python reshape of a multidimensional array
Python shape of a 3D array
Python index array
Python print the shape of a multidimensional array
Python transpose of 1D array
Python change the shape of a 1D array to a 3D array
Python change the shape of an array

Bijay Kumar

I am Bijay Kumar, a Microsoft MVP in SharePoint. Apart from SharePoint, I started working on Python, Machine learning, and artificial intelligence for the last 5 years. During this time I got expertise in various Python libraries also like Tkinter, Pandas, NumPy, Turtle, Django, Matplotlib, Tensorflow, Scipy, Scikit-Learn, etc… for various clients in the United States, Canada, the United Kingdom, Australia, New Zealand, etc. Check out my profile.

enjoysharepoint.com/