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Matplotlib

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Matplotlib & Seaborn: Powerful Data Visualization in Python

Tell compelling stories with your data. This course teaches you to design and create beautiful, informative, and publication-quality charts and graphs using Python's premier visualization libraries, Matplotlib and Seaborn.

Who is this course for?

This course is designed for data analysts and scientists who know how to manipulate data with Pandas and want to effectively communicate their findings. If you want to build impactful visualizations and move beyond basic charts, this course is for you

What You Will Learn:

  • Understand the anatomy of a Matplotlib plot (Figures, Axes, Artists).

  • Create a wide range of plots from scratch: line plots, bar charts, scatter plots, and histograms.

  • Customize every element of your visuals: colors, labels, titles, legends, and styles.

  • Use Seaborn to create statistically sophisticated plots with less code.

  • Build multi-plot figures to compare different facets of your data.

  • Learn best practices for creating clear and honest data visualizations.

Detailed Course Curriculum

Module 1: Matplotlib Fundamentals

  • 1.1 Introduction to Data Visualization.

  • 1.2 The Matplotlib Object Hierarchy: Figure vs. Axes.

  • 1.3 Creating your first plot with plt.plot().

  • 1.4 Building Line and Scatter Plots to show relationships.

Module 2: Visualizing Distributions and Categories

  • 2.1 Bar Charts for categorical comparisons.

  • 2.2 Histograms and Box Plots to understand distributions.

  • 2.3 Customizing Plots: Adding titles, labels, colors, and line styles.

Module 3: Introduction to Seaborn

  • 3.1 Why Seaborn? Statistical plotting made easy.

  • 3.2 Creating beautiful plots with minimal code: relplot(), catplot(), displot().

  • 3.3 Advanced Statistical Plots: Heatmaps, Pairplots, and Violin plots.

Module 4: Advanced Customization and Storytelling

  • 4.1 Working with Subplots for multi-panel figures.

  • 4.2 Adding annotations and text to guide your audience.

  • 4.3 Exporting high-quality figures for reports and presentations.

  • 4.4 Principles of effective data storytelling.

Hands-on Project:

  • Hands-on Project on real data sets

Prerequisites:

  • Strong proficiency in Python and the Pandas library is essential.

Certification

Earn a Certificate of Completion powered by DigData — trusted by professionals, valued by employers, and aligned with real-world industry needs.

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