How to Install Jupyter Notebook on Mac: Step-by-Step Guide


Installing Jupyter Notebook on Mac: A Comprehensive Guide

Jupyter Notebook is an open-source web application software that allows users to create and share documents that contain live code, equations, visualizations, and narrative text. It has become increasingly popular among data analysts and researchers due to its flexibility and versatility. In this article, we will guide you on how to install Jupyter Notebook on your Mac machine.
Follow the 12 easy steps, complete with explanations, and tips that will help in the process.


Step 1: Install Anaconda
The first step to installing Jupyter Notebook is to download and install the Anaconda distribution. This can be done by visiting the Anaconda website and downloading the appropriate installer. Once the installer has been downloaded, double-click on the file and follow the prompts to install Anaconda.

Step 2: Open the Terminal
After installing Anaconda, you will need to open the Terminal application. This can be done by navigating to Applications > Utilities > Terminal.

Step 3: Update Conda
Once you have the Terminal open, you will need to update Conda. This is done by typing the following command into the Terminal:
conda update conda

Step 4: Create a new environment
You will need to create a new environment for Jupyter Notebook. This step is not mandatory, but it is recommended as it helps to avoid any possible conflicts with other packages. You can create a new environment by typing the following command:
conda create –name jupyter_env

Step 5: Activate the new environment
After creating the new environment, you will need to activate it. This can be done by typing the following command:
source activate jupyter_env

Step 6: Install Jupyter Notebook
You can now install Jupyter Notebook by typing the following command:
conda install jupyter

Step 7: Launch Jupyter Notebook
After installing Jupyter Notebook, you can launch it by typing the following command:
jupyter notebook

Step 8: Open Jupyter Notebook
Opening Jupyter Notebook will launch a new tab in your default browser. If this doesn’t happen automatically, you can access it by navigating to http://localhost:8888/tree in your browser.

Step 9: Create a new notebook
You can create a new notebook by clicking on the “New” button in the top-right corner of the screen and selecting “Python 3” from the dropdown menu.

Step 10: Add code
You can now add code to your notebook by inserting code cells and writing the desired code. You can run the code by clicking the “Run” button or by pressing “Shift+Enter” on your keyboard.

Step 11: Add Markdown
Jupyter Notebook also allows you to add Markdown cells, which enable you to add text, equations, images, and other types of formatting to your notebook. You can add a Markdown cell by selecting “Markdown” from the dropdown menu.

Step 12: Save and share
Once you have completed your notebook, you can save it by clicking “File” > “Save” or by using the “Command+S” shortcut on your keyboard. You can also share your notebook by exporting it as an HTML, PDF, or Markdown file.


Jupyter Notebook is an excellent tool for data scientists and researchers. It is a versatile workspace where you can experiment with different ideas. It comes with various features that can help you to present your ideas in a more interactive and engaging way. The steps given above are simple and easy to follow. However, installation may encounter some errors. Therefore, it is essential to understand the process thoroughly.


1. Check your Internet connection before starting the installation process.
2. Ensure that your Mac meets the minimum hardware requirements to run Jupyter Notebook.
3. Make sure that you have sufficient disk space to accommodate the Anaconda distribution and Jupyter Notebook.
4. Consider using virtual environments to avoid any potential conflicts with other packages.
5. Take advantage of the many resources available online to help with any issues you may encounter during the installation process.
6. Consider using a package manager like Homebrew or MacPorts to install Python and its packages.
7. Don’t forget to update Conda regularly to ensure that you have the latest version of Jupyter Notebook.
8. Use Git to version control your notebooks and share them with others.
9. Explore various Jupyter Notebook extensions to enhance your experience.
10. Follow best practices when coding, such as documenting your code and using descriptive variable names.

In conclusion, installing Jupyter Notebook on your Mac is easy and straightforward. The 12 steps detailed above should guide you through the process with ease. Remember to follow best practices when coding and to take advantage of various resources available online.

Advantages and Disadvantages of Installing Jupyter Notebook on Mac

If you’re looking for an open-source platform to work with data analysis, Jupyter Notebook on Mac could be a good option. Jupyter Notebook allows you to create and share documents containing live code, equations, visualizations, and explanatory text. Here are the advantages and disadvantages of installing Jupyter Notebook on Mac:


  1. Open-source: Jupyter Notebook is free and open-source software, which means you don’t have to pay for it and can modify it according to your needs.

  2. Interactive: Jupyter Notebook provides an interactive computing interface that allows you to execute your code and see the output in real-time.

  3. Easy to use: Jupyter Notebook is a user-friendly interface that is easy to use, even if you have little or no programming experience.

  4. Large community: Jupyter Notebook has a large community of users who can help you troubleshoot and find solutions to problems you may encounter.

  5. Data visualization: Jupyter Notebook allows for easy visualization of data using libraries such as Matplotlib, Seaborn, and Bokeh.

  6. Notebook sharing: Jupyter Notebook makes it easy to share your work with others by allowing you to save your work and share it with others.

  7. Supports multiple languages: Jupyter Notebook supports multiple programming languages such as Python, R, and Julia.

  8. Powerful debugging tools: Jupyter Notebook has powerful debugging tools that allow you to find and fix errors in your code.

  9. Flexible: Jupyter Notebook allows for flexibility in your workflow and can be used for a variety of data analysis tasks.

  10. Cloud-based options: There are cloud-based options such as Google Colab and Azure Notebooks that allow you to work on Jupyter Notebooks without having to install it on your local machine.


  1. Requires installation: To use Jupyter Notebook, you need to install it on your local machine, which can take up space and may require some technical knowledge.

  2. Limited collaboration features: While Jupyter Notebook allows you to share your work with others, its sharing and collaboration features are limited compared to other collaborative tools.

  3. Security concerns: Since Jupyter Notebook allows for the execution of live code, it can pose security risks if not used properly.

  4. Not suitable for large datasets: Jupyter Notebook may not be suitable for working with large datasets as it can slow down the execution of code and take up a lot of memory.

  5. Limited support for data wrangling: While Jupyter Notebook supports data visualization, it has limited support for data wrangling tasks such as cleaning and preprocessing data.

  6. Steep learning curve: If you have little or no programming experience, Jupyter Notebook can have a steep learning curve.

  7. Version control issues: Jupyter Notebook doesn’t work well with version control tools like Git, which can make it difficult to track changes and collaborate with others.

  8. Dependent on third-party libraries: Jupyter Notebook is dependent on third-party libraries for certain functions, which can lead to compatibility issues and errors.

  9. Not suitable for real-time applications: Jupyter Notebook is not suitable for real-time applications as it is a batch processing system.

  10. Difficult to scale: Jupyter Notebook can be difficult to scale up to large-scale projects as it is primarily designed for small to medium-sized projects.


1. What is Jupyter Notebook?

Jupyter Notebook is an interactive development environment (IDE) for executing code, creating visualizations and generating reports through a web-based interface.

2. Can I install Jupyter Notebook on Mac?

Yes, you can install Jupyter Notebook on Mac.

3. What is the easiest way to install Jupyter Notebook on Mac?

The easiest way to install Jupyter Notebook on Mac is by installing the Anaconda distribution, which comes with Jupyter Notebook included.

4. What is Anaconda distribution?

Anaconda distribution is a package manager, environment manager, and Python distribution that includes many commonly used libraries for scientific computing and data science.

5. How do I install Anaconda on Mac?

You can download the Anaconda installer for Mac from the Anaconda website, run the installer, and follow the instructions.

6. Once I have Anaconda installed on my Mac, can I start using Jupyter Notebook?

Yes, once you have Anaconda installed on your Mac, you can start using Jupyter Notebook by launching it from the Anaconda Navigator or by running the command “jupyter notebook” from the Terminal.

7. Is there any other way to install Jupyter Notebook on Mac?

Yes, you can also install Jupyter Notebook on Mac using pip, the Python package installer, by running the command “pip install jupyter” from the Terminal.

8. What are the system requirements for Jupyter Notebook on Mac?

Jupyter Notebook runs on Mac OS X 10.9 or later, and requires at least 1GB of free disk space.

9. Can I use Jupyter Notebook to run code in languages other than Python?

Yes, Jupyter Notebook supports many programming languages, including R, Julia, and Scala, among others.

10. How do I create a new notebook in Jupyter Notebook?

To create a new notebook in Jupyter Notebook, open the dashboard by launching Jupyter Notebook, click on the “New” button in the top right corner, and select the type of notebook you want to create.

11. How do I save and download my notebook in Jupyter Notebook?

To save your notebook in Jupyter Notebook, click on the “Save” icon in the top left corner. To download your notebook, click on “File” in the menu bar, select “Download as” and choose your desired format.

12. How do I install additional libraries in Jupyter Notebook?

To install additional libraries in Jupyter Notebook, you can use pip or conda, depending on the package manager you prefer. For example, to install the pandas library, you can run the command “pip install pandas” or “conda install pandas” from the Terminal.

13. Where can I find more information and resources on Jupyter Notebook?

You can find more information and resources on Jupyter Notebook on the official Jupyter website, on the Jupyter Notebook documentation, and on various online communities and forums dedicated to Jupyter Notebook and data science.


Installing Jupyter Notebook on Mac is a straightforward process that can be easily completed by following the steps outlined in this article. By installing Jupyter Notebook, you will have access to an interactive computing environment that facilitates data science projects and coding tasks. With the ability to create and share documents containing live code, equations, visualizations, and narrative text, Jupyter Notebook is a powerful tool for scientific computing and data analysis.

Whether you are a data scientist, developer, or student, Jupyter Notebook can help you analyze and explore data, develop and test code, and document and share your work. By installing Jupyter Notebook on Mac, you can take advantage of this tool’s robust features and improve your productivity and efficiency.


Thank you for reading this article on how to install Jupyter Notebook on Mac. We hope that this guide has provided you with the information you need to get started with Jupyter Notebook and explore its capabilities. If you have any questions or feedback, please don’t hesitate to leave a comment below. We wish you all the best in your data science and coding endeavors, and we look forward to seeing you again soon!