Intro to Seaborn Course (How To)

Introduction to Seaborn

Seaborn is a data visualization library built on top of the plotting library, Matplotlib. It offers a rich set of high-level tools for creating statistical charts and plots. It's more convenient than Matplotlib for quickly visualizing data because it integrates well with Pandas Dataframe objects.

• Introduction

  3:34

• instruction

  Relational Plots

• instruction

  Distribution Plots

• instruction

  Categorical Plots

• Introduction to Seaborn Review

  5 questions

Plotting Functions

Now that we've gone through an overview of the different plot types available in Seaborn, let's start using the library! You'll use Seaborn's plotting functions with a Pokemon dataset to perform exploratory data analysis.

• Setting Up a New JupyterLab Environment

  1:32

• Setting Up Seaborn

  1:59

• Exploring the Data

  3:10

• Relationship Plots

  5:36

• Distribution Plots

  4:35

• Categorical Scatter Plot

  3:04

• Categorical Distribution Plots

  4:21

• Categorical Estimation Plots

  4:31

• Plotting Functions Review

  6 questions

Seaborn Data Visualization Challenges

Now that you've worked through examples and practiced creating plots with Seaborn, it's time to work on some plots on your own. This stage offers a series of Seaborn challenges you'll complete using the Yu-Gi-Oh! dataset.

• Challenge: Setting Up

  2:14

• Challenge: Scatter Plot

  3:26

• Challenge: Histogram and Kernel Density Estimation

  2:43

• Challenge: Strip Plot

  3:29

• Challenge: Box and Violin Plots

  1:26

• Challenge: Bar and Count Plots

  1:46

• Seaborn Data Visualization Review

  5 questions