Skip to content
pythoneo

Pythoneo

Online How to Python stuff

How to convert list to Numpy array

Posted on November 28, 2021September 5, 2023 By Pythoneo

In this tutorial, we’ll dive into the art of converting Python lists into Numpy arrays. You’ll discover three distinct approaches to perform this conversion seamlessly.

convert list to numpy array

There are 3 different ways to convert Python list to Numpy array.

Utilizing the array Method

The most straightforward way to transform a Python list into a Numpy array is by utilizing the array method. Simply pass your list as a single parameter to create the desired Numpy array.

import numpy as np

my_list = [1, 2, 3, 4, 5, 6]
my_array = np.array(my_list)
print(f"Numpy array converted "
      f"from Python list: {my_list}")

convert list to numpy array

This method provides a quick and efficient way to convert a list into a Numpy array, perfect for one-dimensional data.

See also  How to resolve ValueError: operands could not be broadcast together with shapes

Leveraging the asarray Method

Another method at your disposal is the asarray method, which achieves the same result by taking your list as a single parameter.

import numpy as np

my_list = [1, 2, 3, 4, 5, 6]
my_array = np.asarray(my_list)
print(f"Numpy array converted "
      f"from Python list: {my_list}")

convert list to numpy array

The asarray method is functionally equivalent to the array method, providing you with flexibility in your conversion approach.

See also  How to plot log values in Numpy and Matplotlib?

Handling Lists of Lists with the concatenate Method

When dealing with more complex tasks, such as converting a list of lists into a Numpy array, the concatenate method becomes your ally. To execute this conversion successfully, specify axis=0 as the parameter, ensuring proper concatenation.

import numpy as np

my_list = [[1, 2, 3], [4, 5], [6, 7, 8, 9]]
my_array = np.concatenate(my_list, axis=0)
print(f"Numpy array converted "
      f"from Python list of lists: {my_list}")

convert list of lists to numpy array

This technique proves invaluable when working with multi-dimensional data structures, offering control over the axis along which concatenation occurs.

See also  How to convert array to binary?

By mastering these three methods, you’ll be well-equipped to convert Python lists into Numpy arrays efficiently, regardless of the complexity of your data.

numpy Tags:array, asarray, concatenate, list

Post navigation

Previous Post: Achieving Passwordless SSH with Paramiko in Python
Next Post: How to calculate moving sum and moving average using Numpy Convolve?

Categories

  • bokeh (1)
  • Django (5)
  • matplotlib (11)
  • numpy (98)
  • OpenCV (6)
  • Pandas (3)
  • paramiko (11)
  • Pillow (3)
  • Plotly (6)
  • Python (28)
  • Scipy (4)
  • Seaborn (10)
  • statistics (7)
  • Tkinter (7)
  • turtle (2)

RSS RSS

  • Creating Histograms with Plotly in Python
  • OpenCV FindContours: Detecting and Analyzing Objects in Images
  • How to create a simple animation in Tkinter
  • Adaptive Thresholding with OpenCV
  • How to install and use paramiko for SSH connections in Python
  • How to automate file transfers with paramiko and SFTP
  • How to Execute Remote Commands with Paramiko and SSHClient
  • Handling Paramiko Errors and Timeouts
  • How to use paramiko with multiprocessing and threading
  • Creating Interactive Bar Charts with Plotly in Python

Tags

arithmetic mean array axis button calculations chart column conversion count data type dictionary dimension draw error files fill float generate grid GUI image index integer list matrix max mean min mode multiply normal distribution plot random reshape rotate round rows size string sum test text time type zero

Copyright © 2023 Pythoneo.

Powered by PressBook WordPress theme

We use cookies on our website to give you the most relevant experience by remembering your preferences and repeat visits. By clicking “Accept”, you consent to the use of ALL the cookies.
Cookie settingsACCEPT
Manage consent

Privacy Overview

This website uses cookies to improve your experience while you navigate through the website. Out of these, the cookies that are categorized as necessary are stored on your browser as they are essential for the working of basic functionalities of the website. We also use third-party cookies that help us analyze and understand how you use this website. These cookies will be stored in your browser only with your consent. You also have the option to opt-out of these cookies. But opting out of some of these cookies may affect your browsing experience.
Necessary
Always Enabled
Necessary cookies are absolutely essential for the website to function properly. This category only includes cookies that ensures basic functionalities and security features of the website. These cookies do not store any personal information.
Non-necessary
Any cookies that may not be particularly necessary for the website to function and is used specifically to collect user personal data via analytics, ads, other embedded contents are termed as non-necessary cookies. It is mandatory to procure user consent prior to running these cookies on your website.
SAVE & ACCEPT
Go to mobile version