18.3. Studio: Data Visualization with Python¶
18.3.1. Getting Started¶
This dataset was cleaned before being uploaded and is included in the above GitHub repository, so you can focus on the visualizations.
Your mentors will split you up into small groups and each group will be given something in the dataset to visualize. The options are:
- Number of books published per year.
- Number of books published by each publisher.
- Some publishers’ names are in non-Latin scripts, such as Japanese and Russian. Matplotlib may not know how to display these names; that is okay!
- Text ratings count versus reviews count.
18.3.2. Create Your Visualizations¶
Once you have your group, everyone in the group needs to make two visualizations:
- One in Matplotlib.
- One in Seaborn.
- These visualizations can be of any chart type.
- Make sure that everyone is doing something different!
18.3.4. Present to the Class¶
Each presentation should be about 5min and cover:
- Why they picked this chart.
- What was effective about the chart for them?
- What changes do they think would make the chart even better.
18.3.5. Submitting Your Work¶
When finished make sure to push your changes up to GitHub. Copy the link to your GitHub repository and paste it into the submission box in Canvas for Studio: Data Visualization w/Python and click Submit.