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Keep shoppingPython Data Visualization: Master Matplotlib, Seaborn & Plot
47 students
Python Data Visualization: Master Matplotlib, Seaborn & Plot
The complete guide to Data Viz. Create interactive dashboards, geospatial maps, and statistical plots in Python.
Created bySkillbox, LLC
Last updated 1/2026
English
English [Auto],
What you'll learn
- Create Publication-Quality Plots: Master Matplotlib and Seaborn to create static charts suitable for reports and academic papers.
- Build Interactive Dashboards: Use Plotly to create dynamic visualizations that allow users to zoom, pan, and filter data.
- Visualize Geospatial Data: Create interactive maps (Choropleth, Scatter Geo) to analyze geographical trends.
- Master Statistical Plotting: effortless visualize distributions, regressions, and correlations using Seaborn.
- Process Data for Plotting: Learn to clean and shape raw data using Pandas so it is ready for visualization.
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Course content
5 sections • 18 lectures • 1h 1m total length
Requirements
- A PC or Mac
- Basic math skills
- Desire to learn
Description
Data is the new oil. But it is useless if you can't see it.
In the world of Data Science, the ability to analyze data is only half the battle. You need to communicate your findings. You need to turn rows of numbers into compelling stories. You need Data Visualization.
Welcome to Mastering Data Visualization with Python. This course is not just about drawing lines on a graph; it is about mastering the most powerful libraries in the Python ecosystem to create publication-quality figures and interactive web-based dashboards.
Why this course? Most courses focus on just one library. We cover the entire stack. You will learn when to use the flexibility of Matplotlib, the statistical beauty of Seaborn, and the interactive power of Plotly.
What will you master?
1. The Foundation: Matplotlib
Understand the "Grammar of Graphics" and how to build plots from scratch.
Master subplots, axes, and figure customization to make your charts look professional, not default.
2. Statistical Elegance: Seaborn
Create complex statistical visualizations like Heatmaps, Violin Plots, and Pair Plots with a single line of code.
Learn to visualize regression models and data distributions effortlessly.
3. The Interactive Web: Plotly & Cufflinks
Take your charts to the next level. Build zoomable, clickable, and interactive charts that can be embedded in websites.
Create dynamic dashboards that allow users to filter and explore the data themselves.
4. Advanced Visualizations
Geospatial Data: Learn to plot data on real-world maps (Choropleth maps) to visualize geographical trends.
Network Graphs: Visualize relationships and hierarchies using specialized graph libraries.
Hierarchical Data: Master Treemaps and Sunburst charts to show nested data structures.
Real-World Projects You won't just learn syntax; you will apply it. We work with real-world datasets—from financial stock data to global geographical statistics—ensuring you are ready for the job market.
Who is this course for?
Data Analysts who want to move beyond Excel charts.
Python Developers wanting to add "Data Storytelling" to their skillset.
Researchers who need publication-quality figures for their papers.
Stop presenting boring spreadsheets. Enroll today and start creating visualizations that inform, persuade, and impress.
Who this course is for:
- Programmers
- Data Scientist
- Anyone interested in learning data science.
- Anyone interested in learning data visualizations.