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Practice

Introduction to Seaborn

Seaborn is a Python library built on top of Matplotlib. It helps you create attractive and easy-to-read statistical graphics.

With Seaborn, you can make complex plots with much less code compared to using Matplotlib alone.

You can think of Matplotlib as the engine that creates charts, and Seaborn as the designer that makes them look clean and modern.


Why Use Seaborn?​

Here are some reasons why Seaborn is popular among data analysts and scientists:

  • Better-looking charts by default: The charts look clean and professional without extra styling.
  • Less code for complex plots: Many types of plots can be made with just one function call.
  • Built for statistical data: It has built-in support for working with distributions, regression, and comparisons between categories.
  • Works well with Pandas: You can pass DataFrames directly, which makes data exploration faster.

Example: Creating a Simple Seaborn Plot​

Basic Seaborn Scatter Plot
import seaborn as sns
import matplotlib.pyplot as plt

# Example dataset
tips = sns.load_dataset("tips")

# Create a scatter plot of total bill vs tip
sns.scatterplot(data=tips, x="total_bill", y="tip")

plt.show()

With just one function call, you get axis labels, a styled grid, and a clean color scheme without writing extra code.

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