• Online, Self-Paced
Course Description

Seaborn is a data visualization library used for data science that provides a high-level interface for drawing graphs. These graphs are able to convey a lot of information, while also being visually appealing. In this course you will explore Seaborn basic plots and aesthetics.

Learning Objectives

Python for Data Science: Basic Data Visualization Using Seaborn

Course Overview

  • describe what Seaborn is and how it relates to other data science libraries in Python
  • install Seaborn and load a dataset for analysis
  • define and plot the distribution of a single variable using a histogram and kernel density estimate curve
  • configure an univariate distribution's appearance, including color, size, and the components of the plot
  • analyze the relationship between two variables by plotting a bivariate distribution
  • distinguish between scatter plots, hexbin plots, and KDE plots
  • use the Seaborn pair plot to generate a grid to plot the relationship between multiple pairs of variables in your dataset
  • perform a regression analysis on a pair of variables in your dataset by using the Seaborn lmplot
  • describe the basic aesthetic themes and styles available in Seaborn
  • recall some of the use cases and features of Seaborn


Framework Connections

The materials within this course focus on the Knowledge Skills and Abilities (KSAs) identified within the Specialty Areas listed below. Click to view Specialty Area details within the interactive National Cybersecurity Workforce Framework.