Introduction to Matplotlib

Matplotlib is Python's most widely used library for creating static, animated, and interactive visualizations — plots, charts, and graphs.

Installing and Importing

pip install matplotlib

import matplotlib.pyplot as plt

Bar Graphs

Bar graphs compare categorical data using rectangular bars.

import matplotlib.pyplot as plt

subjects = ["Python", "DBMS", "OS", "DSA"]
marks = [88, 76, 82, 91]

plt.bar(subjects, marks, color="skyblue")
plt.xlabel("Subject")
plt.ylabel("Marks")
plt.title("Marks by Subject")
plt.show()

Horizontal bar graph

plt.barh(subjects, marks, color="orange")
plt.xlabel("Marks")
plt.title("Marks by Subject (Horizontal)")
plt.show()

Grouped bar chart (comparing two students)

import numpy as np

x = np.arange(len(subjects))
width = 0.35

plt.bar(x - width/2, [88, 76, 82, 91], width, label="Riya")
plt.bar(x + width/2, [75, 80, 70, 85], width, label="Amit")
plt.xticks(x, subjects)
plt.legend()
plt.title("Marks Comparison")
plt.show()

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Pie Charts

Pie charts show data as proportions of a whole (percentages of a circle).

import matplotlib.pyplot as plt

grades = ["A+", "A", "B", "C"]
counts = [15, 25, 40, 20]

plt.pie(counts, labels=grades, autopct="%1.1f%%", startangle=90)
plt.title("Grade Distribution")
plt.axis("equal")   # keeps the pie perfectly circular
plt.show()

Pie chart with an exploded slice (highlighting)

explode = (0.1, 0, 0, 0)   # "pull out" the first slice
plt.pie(counts, labels=grades, autopct="%1.1f%%", explode=explode, shadow=True)
plt.title("Grade Distribution (Highlighted)")
plt.show()

Common plt functions