Data Visualization in Python with Dash

This is the repository for the LinkedIn Learning course Data Visualization in Python with Dash. The full course is available from LinkedIn Learning.

Data is everywhere. It’s fundamental to your business process. It allows you to make sound, well-informed decisions driven by evidence, not just conjecture. But how should you represent it? The answer depends, especially when you’re working with stakeholders who don’t have a technical background. That’s where Dash comes in. It’s a powerful and easy-to-use data visualization tool that can help you make optimal strategic decisions.

In this course, instructor Robin Andrews gives you an overview of everything you need to know to get started using Dash with Python. Discover how to build powerful and attractive data visualizations. Learn about creating plots, styling applications, and adding user interactivity to cultivate more responsive, data-driven relationships. Robin explores strategies to help you get the most out of the Dash experience, and shows you how to deploy your Dash apps to the cloud using Heroku.

Instructions

This repository has branches for each of the videos in the course. You can use the branch pop up menu in github to switch to a specific branch and take a look at the course at that stage, or you can add /tree/BRANCH_NAME to the URL to go to the branch you want to access.

Branches

The branches are structured to correspond to the videos in the course. The naming convention is CHAPTER#_MOVIE#. As an example, the branch named 02_03 corresponds to the second chapter and the third video in that chapter. Some branches will have a beginning and an end state. These are marked with the letters b for "beginning" and e for "end". The b branch contains the code as it is at the beginning of the movie. The e branch contains the code as it is at the end of the movie. The main branch holds the final state of the code when in the course.

When switching from one exercise files branch to the next after making changes to the files, you may get a message like this:

error: Your local changes to the following files would be overwritten by checkout:        [files]
Please commit your changes or stash them before you switch branches.
Aborting

To resolve this issue:

Add changes to git using this command: git add .
Commit changes using this command: git commit -m "some message"

Instructor

Robin Andrews

Check out my other courses on LinkedIn Learning.