Creating Interactive Visualization with Python

Learn how to create interactive visualization with Matplotlib and Seaborn

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Data visualization is a powerful tool for understanding and communicating complex information. Python has several libraries for creating visualizations, including Matplotlib and Seaborn. Both libraries offer a rich set of tools for creating static and interactive visualizations.

Let’s take a deep dive into how to create interactive visualizations with these libraries.

Matplotlib

Matplotlib is a low-level library for creating visualizations in Python. It provides a wide range of options for creating different types of plots and charts, including line plots, scatter plots, bar plots, histograms, and more. Matplotlib also supports the customization of plot features, such as labels, titles, legends, and colors.

To create interactive visualizations with Matplotlib, you can use the pyplot sublibrary, which provides a high-level interface for plotting. The following code snippet shows how to create a simple line plot with pyplot:

import matplotlib.pyplot as plt

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

# Plot data
plt.plot(x, y)

# Add labels and title
plt.xlabel("X")
plt.ylabel("Y")
plt.title("Line…