- Part 0: Introduction To NumPy
- Part 1: Overview of Matplotlib
- Part 2: Plotting Methods
- Part 3: How To Speak MPL
- Part 4: Limits, Legends, and Layouts
- Part 5: Artists
- Part 6: mpl_toolkits
Note: Parts 0 and 6 are optional.
You'll find the exercises within the Jupyter Notebooks.
The expected format to hand in your solutions to the exercises is a PDF file. For each exercise provide the title of the respective Notebook as a heading and the exercise's title as a subheading. After the heading, provide the Python code with your solution and a screenshot of the graphic generated. Your text is expected to be copy-pastable into the Jupyter Notebook containing the respective exercise.
Example: Your solution to the exercise at the bottom of notebook "Matplotlib_Tut-Part1-Figures_Subplots_and_layouts.ipynb"
will start with the heading Matplotlib_Tut-Part1-Figures_Subplots_and_layouts
followed by subheading Quick Exercise: Exercise 1.1
.
Next follows the entire Python code of this Cell, including your solution which comes right after the comment line:
# Can you figure out what to do next to plot x vs y1, y2, and y3 on one figure?
All you need is matplotlib jupyter installed. You can use your favorite Python package installer for this:
pip install matplotlib jupyter
git clone https://github.zhaw.ch/wagb/datavislab
cd datavislab
jupyter notebook
or:
conda install matplotlib jupyter
git clone https://github.zhaw.ch/wagb/datavislab
cd datavislab
jupyter notebook
A browser window should appear and you can verify that everything works as expected by clicking on the Test Install.ipynb
notebook. There, you will see a "code cell" that you can execute. Run it, and you should see a very simple line plot, indicating that all is well.