Your charts work, but would a stranger understand them? A bare chart is a puzzle: bars of what, measured in what? Today you make charts anyone can read — with a title, labeled axes, and a splash of color — and save one to share.

▶ Open this lesson in Colab

💡 Load the data and chart tool first:

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
penguins = sns.load_dataset("penguins").dropna()

A title and labels

After drawing a chart, you add words with plt.title, plt.xlabel, and plt.ylabel. The chart isn’t shown until plt.show(), so put these before it:

penguins.groupby("species")["body_mass_g"].mean().plot(kind="bar")
plt.title("Average penguin weight by species")
plt.xlabel("Species")
plt.ylabel("Body mass (grams)")
plt.show()

Now the chart explains itself: anyone can see it’s about penguin weight, by species, in grams. Labels turn a picture into a message.

Try it 🎯

Take your flipper-length-per-species chart and give it a title and both axis labels.

Add some color

.plot(...) accepts a color:

penguins["species"].value_counts().plot(kind="bar", color="teal")
plt.title("How many penguins of each species")
plt.xlabel("Species")
plt.ylabel("Count")
plt.show()

Try "coral", "slateblue", "gold" — pick something that fits your story.

Make it bigger

A roomier chart is easier to read. Set the size with figsize=(width, height) (in inches):

penguins.plot(kind="scatter", x="flipper_length_mm", y="body_mass_g", figsize=(8, 5))
plt.title("Heavier penguins have longer flippers")
plt.xlabel("Flipper length (mm)")
plt.ylabel("Body mass (grams)")
plt.show()

Notice the title itself states the finding — a great habit for a data report.

Save your chart

Save a chart to an image file with plt.savefig(...) — put it just before plt.show():

penguins["species"].value_counts().plot(kind="bar", color="teal")
plt.title("Penguins by species")
plt.savefig("penguins_by_species.png")
plt.show()

In Colab, the file appears in the Files panel on the left (the little folder icon) — right-click it to download, and you’ve got an image to put in a report or show a friend.

Predict it 🔮

If you run plt.title(...) after plt.show(), will the title appear on the chart? (No — plt.show() finishes and displays the chart, so anything after it is too late. Always label before show.)

Fix the bug 🐞

This chart is a mystery — bars with no explanation. Add a title and axis labels so a stranger could understand it:

penguins.groupby("island")["body_mass_g"].mean().plot(kind="bar")
plt.show()

(Before plt.show(), add plt.title("Average weight by island"), plt.xlabel("Island"), and plt.ylabel("Body mass (grams)").)

Your mission 🚀

Make one polished chart: pick a question, draw the chart, give it a clear title (state the finding!), label both axes, choose a color, and savefig it. Then download the image from the Files panel.

What you learned today

• plt.title, plt.xlabel, plt.ylabel explain a chart — add them before plt.show().
• color= and figsize= make charts prettier and clearer.
• plt.savefig("name.png") saves a chart to share.
• A good title states the finding, not just the topic.

Next time, you break free of penguins and load a dataset about something you care about. 🌍