Data Visualization Tutorial for Beginners
Use the Tips dataset to practice creating different types of charts in both Matplotlib and Seaborn.
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In this project, you will use the Tips dataset (built into Seaborn) to practice creating different types of charts. The goal is not to do deep analysis — it is to get comfortable with the syntax and options of both Matplotlib and Seaborn.
You will build the same charts in both libraries so you can compare how they work.
Project Requirements
Load the Tips dataset with
sns.load_dataset("tips")Create the following charts using both Matplotlib and Seaborn:
Histogram
Bar chart
Box plot
Scatter plot
Heatmap of correlations
Customize labels, titles, font sizes, and color palettes
Save at least one chart as a PNG file
Technologies to Use
Python
Matplotlib
Seaborn
Pandas
Jupyter Notebook
What You Will Learn
You will understand the differences between the two libraries, when to use each one, and how to control the look of your charts. This is essential before moving to more complex visualizations.
Want to See a Solution?
A similar project using different datasets is available on Towards Data Science: 🔗 Introduction to Data Visualization in Python
