Line and Bar Charts with Matplotlib

Line and bar charts answer most everyday questions. This lesson shows how to make them clear: several lines with a legend, sorted bars, and labels on the bars so readers don’t have to guess.

Several lines with a legend#

Give each line a label, then call legend():

import matplotlib.pyplot as plt

months = ["Jan", "Feb", "Mar", "Apr", "May", "Jun"]
pune = [120, 135, 150, 145, 170, 190]
delhi = [140, 130, 125, 160, 165, 175]

fig, ax = plt.subplots(figsize=(7, 4))
ax.plot(months, pune, marker="o", label="Pune")
ax.plot(months, delhi, marker="s", linestyle="--", label="Delhi")
ax.set_title("Monthly orders: Pune overtook Delhi in May")
ax.set_ylabel("Orders")
ax.legend()
ax.grid(alpha=0.3)
plt.show()

Useful styling options:

Option	Examples
marker	"o" circle, "s" square, "^" triangle
linestyle	"-", "--", ":"
color	"tab:green", "#0a7d4f"
linewidth	1, 2.5

Bar charts for categories#

import matplotlib.pyplot as plt

languages = ["Python", "JavaScript", "Java", "SQL", "C++"]
students = [420, 310, 280, 190, 120]

fig, ax = plt.subplots(figsize=(7, 4))
bars = ax.bar(languages, students, color="#0a7d4f")
ax.bar_label(bars)
ax.set_title("Most popular course among our students: Python")
ax.set_ylabel("Students enrolled")
plt.show()

ax.bar_label(bars) writes each value on top of its bar, so nobody has to read the y-axis.

Horizontal bars for long names#

When category names are long, turn the chart sideways with barh:

import matplotlib.pyplot as plt

topics = ["Data cleaning", "Exploratory analysis", "Feature engineering", "Model training", "Reporting"]
hours = [12, 8, 6, 4, 3]

fig, ax = plt.subplots(figsize=(7, 4))
ax.barh(topics[::-1], hours[::-1], color="tab:orange")
ax.set_title("Where a data project's time really goes")
ax.set_xlabel("Hours")
plt.show()

We reversed the lists with [::-1] so the biggest bar appears at the top.

Grouped bars#

To compare two series per category, shift each set of bars left and right by half a bar width:

import numpy as np
import matplotlib.pyplot as plt

subjects = ["Maths", "Science", "English"]
class_a = [72, 81, 77]
class_b = [78, 74, 83]
x = np.arange(len(subjects))
w = 0.38

fig, ax = plt.subplots(figsize=(7, 4))
ax.bar(x - w / 2, class_a, w, label="Class A")
ax.bar(x + w / 2, class_b, w, label="Class B")
ax.set_xticks(x, subjects)
ax.set_ylabel("Average marks")
ax.set_title("Class B leads in Maths and English")
ax.legend()
plt.show()

Quick check

Your y-axis starts at 70 instead of 0 and a small difference looks huge. For bar charts, always start the y-axis at zero, otherwise the bar heights lie.

Summary#

• ax.plot() for trends; give each line a label and call ax.legend().
• ax.bar() for categories, ax.barh() for long names; ax.bar_label() adds values.
• Sort bars, start bar axes at zero, and write the conclusion in the title.