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Introduction to Matplotlib

Matplotlib is the standard plotting library for Python. It allows you to create high-quality, customizable visualizations such as line plots, scatter plots, bar charts, histograms, and more.

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Why use Matplotlib?

  • Full control over every element in a chart (titles, axes, colors, labels).
  • Exportable to many file formats (PNG, PDF, SVG).
  • Integrates seamlessly with NumPy and Pandas.

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Creating Your First Plot

The most common way to use Matplotlib is via the pyplot module: 
import matplotlib.pyplot as plt

# Data
x = [1, 2, 3, 4, 5]
y = [2, 4, 6, 8, 10]

# Create a line plot
plt.plot(x, y, label="Double Value", color="green", marker="o")

# Add labels and title
plt.xlabel("X Axis")
plt.ylabel("Y Axis")
plt.title("Simple Line Plot")
plt.legend()

# Display the plot
plt.show()

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Common Plot Types

  • plt.scatter(x, y): Creates a scatter plot (points).
  • plt.bar(x, height): Creates a vertical bar chart.
  • plt.hist(data): Creates a histogram to see data distribution.

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Next Steps

While Matplotlib is powerful, it can require a lot of code to make plots look modern. Let’s look at Seaborn, which builds on Matplotlib to provide beautiful, statistical charts with less code.