“Interactive Data Visualizations in Python” is a Carpentries Incubator lesson plan I developed for teaching learners how to create interactive data visualizations in Python.
I developed this workshop lesson in Summer 2021 as a follow-up to the Plotting and Programming in Python lesson. For my personal/work projects, I’ve been using Streamlit and Plotly to quickly build an online dashboard of interactive data visualizations - and I have 0 web development skills, which really shows the power of Streamlit. So I wanted to teach learners semi-new to Python how to make some data visualization web apps of their own!
This lesson is relatively new - so I would really love for other Carpentries Instructors to take it for a spin, submit any issues to the GitHub repo, and let me know how it went! If you want to know more about the lesson, you can check out the Incubator Lesson Spotlight post published on September 9, 2021. If you plan on teaching this lesson, please feel free to contact me with any questions you may have.
This workshop lesson is an introduction to making interactive data visualizations in Python. Learners will create a new environment using conda, wrangle data into the proper format using the pandas library, create visualizations using the Plotly Python library, and display these visualizations and create widgets using Streamlit. The lesson uses the Gapminder dataset, same as the “Plotting & Programming in Python” core SWC lesson. You can see an example of what learners will create during this workshop by clicking on the button below: