Learn to turn small Python data sets into clear visualizations with Matplotlib. Across eight guided labs, you will set up the library, build and customize common chart types, save figures as image files, and arrange multiple plots in one figure.
Each lab develops one plotting pattern through short, concrete steps. You will work with line plots, bar charts, scatter plots, histograms, pie charts, and subplots while learning the labels, colors, markers, legends, axes, and layout controls that make a chart easier to interpret.
What You Will Learn
- Install Matplotlib, import
matplotlib.pyplot, and create figure and axes objects - Plot line data and add axis labels, titles, colors, markers, and line styles
- Create vertical and horizontal bar charts with colors and legends
- Build scatter plots and adjust marker size, color, and grid display
- Generate and customize histograms, including bin counts and density normalization
- Present proportions with pie-chart labels, percentages, exploded slices, and shadows
- Combine plots with subplots, shared axes, and adjusted layouts
- Display plots interactively and save figures to image files
Who This Course Is For
This course is for Python beginners who want a hands-on introduction to plotting rather than a theory-heavy treatment of data visualization. It is especially useful if you can write small scripts and lists but have not yet used Matplotlib. The course teaches chart construction; it does not cover data cleaning, statistical analysis, Pandas workflows, or advanced visualization design.
Prerequisites: Basic Python syntax—including variables, lists, function calls, and running a script—is recommended. No previous Matplotlib experience is required.
Learning environment: The guided labs run in a provided Ubuntu 22.04 WebIDE. You install and use Matplotlib in Python files, run the code, and inspect saved plot images within the lab environment.
Frequently Asked Questions
Does the course start with Matplotlib installation?
Yes. The first lab uses pip, imports matplotlib.pyplot, checks the installed version, and creates both an empty figure and a displayed plot.
Which chart types will I create?
You will create line plots, vertical and horizontal bar charts, scatter plots, histograms, pie charts, and multi-panel figures with subplots.
Do I need NumPy or Pandas experience?
No. One histogram exercise uses NumPy to generate sample data, but the course does not assume a broader NumPy or Pandas background. Basic Python is enough to follow the guided steps.
Are there independent challenges or a final project?
No. All eight activities are beginner guided labs. They provide focused practice with individual plotting techniques rather than an unassisted project.
