Course Description

Blue gradient rectangle with assorted sizes of white gears scattered around the word python in white and the python symbol of interlocked shapes of blue and gold in the center


You’ll begin with basics data visualization and its importance. Then, you will be given an overview of Statistics. You’ll also learn about key NumPy and Pandas
techniques, such as indexing, slicing, iterating, filtering, and grouping. Next, you’ll study different types of visualizations, compare them, and find out how to select
a particular type of visualization using this comparison. After you get a hang of the various visualization libraries, you’ll learn to work with Matplotlib and Seaborn to
simplify the process of creating visualizations. You’ll also be introduced to advanced visualization techniques, such as geoplots and interactive plots to build beautiful
and insightful visualizations. You’ll study basics of Bokeh, extending plots by adding widgets. At the end you will implement a few major activities using all the libraries that we’ve learned.

Course Outline

  • Lesson 1: The Importance of Data Visualization and
    • Data Exploration
    • Overview of statistics
    • NumPy
    • pandas
  • Lesson 2: All You Need to Know About Plots
    • Comparison Plots
    • Relation Plots
    • Composition Plots
    • Distribution Plots
    • Geo Plots
    • What Makes a Good Visualization?
  • Lesson 3: A deep dive into Matplotlib
    • Overview of Plots in Matplotlib
    • Pyplot Basics
    • Basic Text and Legend Functions
    • Basic Plots
    • Layouts
    • Images
    • Writing Mathematical Expressions
  • Lesson 4: Simplifying Visualizations Using Seaborn
    • Controlling Figure Aesthetics
    • Color Palettes
    • Interesting Plots in Seaborn
    • Multi-Plots in Seaborn
    • Regression Plots
    • Squarify
  • Lesson 5: Plotting Geospatial Data
    • Tile Providers
    • Custom Layers
  • Lesson 6: Making Things Interactive with Bokeh
    • Adding Widgets
  • Lesson 7: Combining What We've Learned
    • Implementing Matplotlib and Seaborn on New York
    • City Database
    • Visualizing Bokeh Stock Prices
    • Analyzing Airbnb Data with Geoplotlib

Learner Outcomes

At the end of this program, you will be able to:

  • Explain and use various plot types with Python
  • Explore and work with different plotting libraries
  • Explain and create effective visualizations
  • Improve your Python data wrangling skills
  • • Work with industry-standard tools like Matplotlib,
  • Seaborn, and Bokeh
  • • Understand different data formats and
  • representations


Data Visualization with Python is designed for developers and scientists, who want to get into data science or want to use data visualizations to enrich their personal
and professional projects. You do not need any prior experience in data analytics and visualization, however, it'll help you to have some knowledge of Python and familiarity with high school level mathematics. Even though this is a beginner level course on data visualization, experienced developers will be able to improve their Python skills by working with real-world data.
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