Python Matplotlib Full Notes for Beginners

July 29, 2025 By @mritxperts

Introduction

Matplotlib is a data visualization library in Python. It helps you create various charts like line plots, bar graphs, scatter plots, pie charts, and more.

Installation

pip install matplotlib

Importing

import matplotlib.pyplot as plt

Basic Structure of a Plot

x = [1, 2, 3, 4]
y = [10, 20, 25, 30]
plt.plot(x, y)
plt.title("Sample Line Chart")
plt.xlabel("X-axis Label")
plt.ylabel("Y-axis Label")
plt.xticks([1, 2, 3, 4], ["One", "Two", "Three", "Four"])
plt.yticks([10, 20, 30])
plt.grid(True)
plt.legend(["Data"], loc='upper left')
plt.savefig("plot.png")  # Save plot as image
plt.show()

Line Plot

x = [1, 2, 3, 4, 5]
y = [5, 7, 4, 6, 8]
plt.plot(x, y, color='blue', linestyle='--', linewidth=2, marker='o')
plt.title("Line Plot Example")
plt.xlabel("X Axis")
plt.ylabel("Y Axis")
plt.xticks(x)
plt.grid(True)
plt.show()

Bar Chart

categories = ['A', 'B', 'C', 'D']
values = [10, 20, 15, 30]
plt.bar(categories, values, color='green', edgecolor='black')
plt.title("Bar Chart")
plt.xlabel("Categories")
plt.ylabel("Values")
plt.ylim(0, 35)
plt.grid(axis='y')
plt.show()

Horizontal Bar Chart

plt.barh(categories, values, color='orange')
plt.title("Horizontal Bar Chart")
plt.ylabel("Categories")
plt.xlabel("Values")
plt.xlim(0, 35)
plt.grid(axis='x')
plt.show()

Histogram

data = [22, 87, 5, 43, 56, 73, 55, 54, 11, 20, 51, 5, 79, 31, 27]
plt.hist(data, bins=5, color='purple', edgecolor='black')
plt.title("Histogram")
plt.xlabel("Ranges")
plt.ylabel("Frequency")
plt.grid(axis='y')
plt.show()

Pie Chart

labels = ['Python', 'Java', 'C++', 'Ruby']
sizes = [215, 130, 245, 210]
colors = ['gold', 'lightblue', 'lightgreen', 'pink']
plt.pie(sizes, labels=labels, colors=colors, startangle=90, shadow=True, autopct='%1.1f%%')
plt.title("Pie Chart")
plt.axis('equal')  # Equal aspect ratio makes the pie circular
plt.show()

Scatter Plot

x = [5, 7, 8, 7, 2, 17, 2, 9]
y = [99, 86, 87, 88, 100, 86, 103, 87]
plt.scatter(x, y, color='red', s=100)  # s is size of dots
plt.title("Scatter Plot")
plt.xlabel("X")
plt.ylabel("Y")
plt.grid(True)
plt.show()

Stacked Bar Chart

x = ['Q1', 'Q2', 'Q3', 'Q4']
A = [3, 4, 5, 6]
B = [1, 3, 4, 5]
plt.bar(x, A, label='Product A', color='blue')
plt.bar(x, B, bottom=A, label='Product B', color='orange')
plt.title("Stacked Bar Chart")
plt.xlabel("Quarter")
plt.ylabel("Sales")
plt.legend()
plt.show()

Box Plot

data = [7, 15, 13, 18, 9, 10, 22, 30]
plt.boxplot(data)
plt.title("Box Plot")
plt.ylabel("Values")
plt.grid(True)
plt.show()

Area Chart

x = [1, 2, 3, 4, 5]
y = [2, 3, 5, 6, 8]
plt.fill_between(x, y, color='skyblue', alpha=0.4)
plt.plot(x, y, color='blue')
plt.title("Area Chart")
plt.xlabel("X")
plt.ylabel("Y")
plt.grid(True)
plt.show()

Multiple Line Plot

x = [1, 2, 3, 4]
y1 = [1, 4, 9, 16]
y2 = [2, 5, 10, 17]
plt.plot(x, y1, label='Line 1', color='blue')
plt.plot(x, y2, label='Line 2', color='green')
plt.title("Multiple Line Plot")
plt.xlabel("X-axis")
plt.ylabel("Y-axis")
plt.legend()
plt.grid(True)
plt.show()

Real-Life Example: Student Marks

subjects = ['Math', 'Science', 'English', 'History']
marks = [88, 75, 90, 70]
plt.plot(subjects, marks, marker='o', color='blue')
plt.title("Student Marks")
plt.ylabel("Marks")
plt.ylim(0, 100)
plt.grid(True)
plt.show()

Customizations Summary

Feature	Description	Example Code
Title	Adds a title to the plot	plt.title(“Chart Title”)
Axis Labels	Labels the X and Y axes	plt.xlabel(“X”), plt.ylabel(“Y”)
Grid Lines	Adds grid to background	plt.grid(True)
Ticks	Custom values on axis	plt.xticks([…]), plt.yticks([…])
Legend	Labels for plotted lines or bars	plt.legend()
Style	Changes overall plot style	plt.style.use(‘ggplot’)
Save Plot	Save the plot as an image	plt.savefig(“file.png”)
Axis Limits	Fix min and max of axes	plt.xlim(), plt.ylim()

Recommended Styles in Matplotlib

plt.style.use('ggplot')
plt.style.use('seaborn')
plt.style.use('classic')

To see all available styles:

print(plt.style.available)