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