Download Jupyter Notebook and Learn Python, R, Julia, and More
How to Download Jupyter Notebook
Jupyter Notebook is a web-based platform that allows you to create and share documents that contain live code, equations, visualizations, and narrative text. It is widely used for data science and machine learning projects, as well as for teaching and learning purposes. In this article, you will learn how to download Jupyter Notebook on your computer and how to use its basic features.
download jupyter notebook
What is Jupyter Notebook?
Jupyter Notebook is an open-source application that lets you write and run code in various programming languages, such as Python, R, Julia, and Scala. You can also use Jupyter Notebook to perform data analysis, data visualization, machine learning, and much more. Some of the benefits of using Jupyter Notebook include:
It is interactive and easy to use. You can execute code cell by cell and see the results immediately.
It supports multiple languages and frameworks. You can switch between different kernels and use libraries like pandas, scikit-learn, TensorFlow, PyTorch, etc.
It is rich in media. You can add text, images, videos, equations, widgets, and other elements to your notebooks using markdown, HTML, or LaTeX.
It is shareable and reproducible. You can save your notebooks as files and share them with others using email, Dropbox, GitHub, or nbviewer. You can also convert your notebooks to other formats like HTML or PDF.
How to Install Jupyter Notebook?
There are different ways to install Jupyter Notebook on your computer. Here are some of the most common methods:
Anaconda is a popular distribution of Python and other packages for scientific computing and data science. It comes with Jupyter Notebook pre-installed. To install Anaconda, follow these steps:
Go to and download the installer for your operating system.
Run the installer and follow the instructions on the screen.
Once Anaconda is installed, you can launch Jupyter Notebook from the Anaconda Navigator or from the command line by typing jupyter notebook.
pip is a package manager for Python that allows you to install and manage software packages written in Python. To install pip, follow these steps:
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Go to and follow the instructions for your operating system.
Once pip is installed, you can install Jupyter Notebook by typing pip install jupyter in the command line.
To launch Jupyter Notebook, type jupyter notebook in the command line.
Using other alternatives
If you don't want to install Jupyter Notebook on your computer, you can use other web-based platforms that offer Jupyter Notebook functionality. Some of these platforms are:
: A free service that allows you to create and run Jupyter notebooks in the cloud. You can also access Google Drive, Google Sheets, and other Google services from Colab.
: A platform for data science and machine learning competitions. You can use Kaggle kernels to create and run Jupyter notebooks online. You can also access datasets, models, and other resources from Kaggle.
: A service that allows you to turn a GitHub repository into a collection of interactive Jupyter notebooks. You can also customize the environment and the dependencies of your notebooks.
How to Launch Jupyter Notebook?
Once you have installed Jupyter Notebook on your computer or chosen an online platform, you can launch it by following these steps:
Open the command line or the terminal and navigate to the folder where you want to create or open your notebooks.
Type jupyter notebook and press enter. This will start the Jupyter Notebook server and open a new tab in your browser.
In the browser, you will see a list of files and folders in your current directory. You can click on any file with the extension .ipynb to open an existing notebook, or click on the New button to create a new notebook.
You can also access Jupyter Notebook from any other browser or device by typing the URL of the server, which is usually followed by a token that is displayed in the command line.
How to Use Jupyter Notebook?
Jupyter Notebook has many features and components that make it a powerful tool for data science and machine learning. Here are some of the basic ones that you should know:
Creating and saving notebooks
A notebook is a document that contains cells of code, text, or media. To create a new notebook, click on the New button and select the kernel (the language or framework) that you want to use. You can also rename your notebook by clicking on the title at the top of the page. To save your notebook, click on the Save button or press Ctrl+S. Your notebook will be saved as a file with the extension .ipynb.
Writing and executing code
To write code in your notebook, you need to use code cells. A code cell is a box where you can type and edit code. To create a new code cell, click on the + button or press B. To execute a code cell, click on the Run button or press Shift+Enter. The output of your code will be displayed below the cell. You can also use keyboard shortcuts, menus, and toolbars to perform various actions on your code cells, such as copying, cutting, pasting, deleting, moving, splitting, merging, etc.
Adding text and media
To add text and media to your notebook, you need to use markdown cells. A markdown cell is a box where you can write text using markdown syntax, which is a simple way to format text using symbols like #, *, _, etc. To create a new markdown cell, click on the + button or press B, and then change the cell type from Code to Markdown. To render a markdown cell, click on the Run button or press Shift+Enter. The formatted text will be displayed below the cell. You can also use HTML or LaTeX tags to add more elements to your text, such as images, videos, equations, etc.
Plotting and visualizing data
To plot and visualize data in your notebook, you need to use libraries that can create plots and charts. Some of the most popular libraries for data visualization are matplotlib, seaborn, and plotly. To use these libraries, you need to import them in your code cells and then call their functions to create the desired plots. For example, to create a scatter plot using matplotlib, you can write something like this:
import matplotlib.pyplot as plt x = [1, 2, 3, 4, 5] y = [2, 4, 6, 8, 10] plt.scatter(x, y) plt.show()
The output of your code will be a plot that will be displayed below the cell. You can also customize your plots by adding titles, labels, legends, colors, etc. You can also use interactive plots that allow you to zoom, pan, hover, etc. by using libraries like plotly or bokeh.
Sharing and exporting notebooks
To share your notebooks with others, you have several options. You can:
Send your notebook file as an attachment via email or other messaging platforms.
Upload your notebook file to a cloud storage service like Dropbox or Google Drive and share the link with others.
Push your notebook file to a version control system like GitHub or Bitbucket and share the repository URL with others.
Use a service like nbviewer or Binder to render your notebook as a static or interactive web page and share the URL with others.
To export your notebooks to other formats, you can use the <cod