Matplotlib Markers
Markers show individual observations on a plotted series. They can make a sparse line chart easier to read and distinguish from another series.
Understand the idea
Choose a marker and size that remain clear at the final image size. Too many large markers on dense data can hide the underlying trend. Use shape as well as colour when a distinction matters, so the chart remains understandable in grayscale or to readers with colour-vision differences.
Where to try it
Run this complete script in a local virtual environment with Matplotlib installed (py -m pip install matplotlib). It uses a non-interactive backend and saves workshop.png in the current folder. The site shows a rendered example below; its text-only online runner does not display plot windows.
A worked example
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
fig, ax = plt.subplots(figsize=(7, 4), layout="constrained")
ax.plot([1, 2, 3, 4], [4, 7, 6, 9], marker="s", markersize=7)
ax.set(xlabel="Week", ylabel="Bookings", title="Show every observation")
fig.savefig("workshop.png", dpi=140)
plt.close(fig)
print("Saved workshop.png")
Read the result
Square markers reveal the four exact observations along the connecting line.
Try one change
Compare circles and squares at two sizes, checking readability in a small exported image.
For package options, see the Matplotlib documentation.