Live training with Teddy Petrou starts on December 1st and 8th at 12 PM (EST)

Training duration: 4 hours (Hands-on)

Price with 30% discount

Regular Price: $210.00

Subscribe now and start 7-day free trial

Sign-up for Premium Plan and Get 10-35% Additional Discount Live Training

Instructor Bio:

Python Data Science Expert Instructor - Author of Multiple Books and Python LIbraries | Founder | Dunder Data

Teddy Petrou

Teddy Petrou is the author of Pandas Cookbook, a highly rated text on performing real-world data analysis with Pandas. He is also the author of the books Exercise Python and Master Data Analysis with Python. He is the founder of Dunder Data, a company that teaches the fundamentals of data science and machine learning. He really enjoys discovering best practices on how to use and teach data analysis with Python.

30% discount ends in:

  • 00 Days
  • 00 Hours
  • 00 Minutes
  • 00 Seconds

Learning Objectives

  • Learn the fundamentals of using the Seaborn data visualization library and how it integrates with Pandas DataFrames

  • Understand the different categories of Seaborn plotting functions and the return type (Grid or Axes) of each

  • Learn how tidy data provides the best structure to take advantage of the Seaborn plotting functions

  • Learn how to choose grouping and aggregating variables, and how to customize plots with all the other available parameters

  • Learn how to create grids of plots


Course Outline

Day 1


Module 1: An overview of the 

Matplotlib Figure and Axes 

Training Overview 

Matplotlib Figure and Axes objects

An object-oriented approach to Matplotlib

Seaborn as a “wrapper” for Matplotlib

Module 2: Introduction to Seaborn 

Seaborn documentation and API

Integration with Pandas DataFrames

Main plotting parameters

Grid vs Axes plots

A different categorization for Seaborn plots


Module 3: Distribution Plots

Univariate distribution plots

Box plots

Changing the orientation of plots

Histograms and KDEs

Other distribution plots


Module 4: Automatic Grouping by Category 

Plotting a continuous by a categorical variable

Grouping with two continuous variables

Splitting groups by setting hue


Day 2


Module 5: Grouping and Aggregating Plots

Univariate grouping and aggregating

Choosing the aggregation function

Bar, Point, Count, and Line plots


Module 6: Tidy Data 

Definition of tidy data

Long data vs wide data

Seaborn automatically groups and aggregates

Manually grouping and aggregating with pandas


Module 7: Raw Data Plots 


Regression plots



Module 8: Grid Plots

Relationship with Matplotlib Figures

Discovering the Grid plotting functions

Setting the plot with the kind parameter

Creating multiple Axes with row/col parameters

Bivariate distribution plots

Hierarchical cluster maps


Module 9: Seaborn Styles and Palettes 

Run configuration parameters

Specific Seaborn styles

Color palettes and widgets

Course Abstract

The Seaborn data visualization library in Python provides a simple and intuitive interface for making beautiful plots directly from a Pandas DataFrame. When users arrange their data in tidy form, the Seaborn plotting functions perform the heavy lifting by grouping, splitting, aggregating, and plotting data, often with a single line of code. This course provides comprehensive coverage of how to use all of the Seaborn plotting functions with real-life data.

What background knowledge you should have?

  • Elementary knowledge of the Python programming language is necessary

  • Some experience with Matplotlib and Pandas libraries are helpful, but not strictly necessary

  • Prior work with Jupyter Notebooks would be helpful as all material is delivered with them

What is included in your ticket?

  • Access to live training and QA session with the Instructor

  • Access to the on-demand recording

  • Certificate of completion

Upcoming Live Training & Recordings

Access all live training