Jupyter Notebook Lab — Module 10#

Data Visualization with Matplotlib

Practice creating business charts with Matplotlib — bar charts, line charts, and scatter plots — and customize them for professional communication.

Download#

📓 Student Notebook .ipynb 🔑 Answer Key coming soon

Open the .ipynb file in Google Colab by selecting File → Upload notebook.

What You’ll Practice#

  1. Creating bar charts to compare categorical data across regions
  2. Building line charts to visualize trends over time
  3. Plotting scatter charts to explore relationships between numeric variables
  4. Customizing charts with titles, axis labels, colors, and annotations
  5. Combining multiple charts in a single figure with subplots
  6. Saving charts to image files with plt.savefig()

Learning Objectives#

By completing this notebook you will be able to:

  • Use Matplotlib’s fig, ax = plt.subplots() pattern to create figures and axes
  • Plot bar, line, and scatter charts from Pandas DataFrames
  • Add titles, axis labels, and annotations to make charts business-ready
  • Create multi-panel figures with plt.subplots(rows, cols)
  • Save charts to image files with plt.savefig()

Next Module: Module 11 — Applied Integration →