Python — Matplotlib

Install & the two APIs

pip install matplotlib

import matplotlib.pyplot as plt

x = [1, 2, 3, 4]
y = [2, 4, 9, 16]

plt.plot(x, y)            # line chart
plt.show()                # opens a window (or renders in notebook)

plt (pyplot) is the state-machine interface every tutorial uses — start there.

Label your axes — always

plt.plot(x, y, marker="o")
plt.title("Distance over time")
plt.xlabel("Hours")
plt.ylabel("Kilometers")
plt.grid(True)
plt.show()

An unlabeled chart communicates nothing.

The essential chart types

# bar — categories vs values
plt.bar(["Mon", "Tue", "Wed"], [12, 18, 9])

# scatter — relationships between two variables
plt.scatter(heights, weights, alpha=0.5)

# histogram — distribution of ONE variable
plt.hist(exam_scores, bins=10)

# pie — parts of a whole (sparingly!)
plt.pie([60, 40], labels=["Cats", "Dogs"], autopct="%1.0f%%")

Data question	Chart
Trend over time	line
Compare categories	bar
Correlation of two vars	scatter
Shape/spread of one var	histogram

Multiple lines & legends

plt.plot(months, revenue, label="Revenue")
plt.plot(months, costs, label="Costs")
plt.legend()                 # shows the labels

Subplots — charts side by side

fig, axes = plt.subplots(1, 2, figsize=(10, 4))

axes[0].plot(x, y)
axes[0].set_title("Left chart")

axes[1].bar(cats, vals)
axes[1].set_title("Right chart")

plt.tight_layout()
plt.show()

Styling quickly

plt.plot(x, y,
         color="teal",
         linestyle="--",
         linewidth=2,
         marker="o",
         markersize=6)

plt.style.available          # list built-in themes
plt.style.use("seaborn-v0_8")   # one line → prettier everything

Saving instead of showing

plt.savefig("chart.png", dpi=150, bbox_inches="tight")

Put savefig BEFORE show() (show clears the canvas).

With pandas — one-liner charts

import pandas as pd

df["revenue"].plot(kind="line")
df.groupby("month")["sales"].sum().plot(kind="bar")
df.plot.scatter(x="height", y="weight")

pandas wraps matplotlib so DataFrame columns become plots directly.

Gotchas: forgetting plt.show() (nothing appears) · savefig after show (empty file) · comparing wildly different scales on one axis.

Mini Practice

1. Line chart of temperatures with markers + grid.
2. Bar chart of five categories; rotate tick labels via plt.xticks(rotation=45).
3. Scatter of two correlated columns from pandas.
4. Histogram of 100 random numbers.
5. 1×2 subplot figure with titles; save as PNG.

Next: SciPy →