Seaborn Distribution Plots | Python Machine Learning Tutorial
In this video, you’ll learn about creating distribution plots using Seaborn. Seaborn is essential to Machine Learning! It allows you to create advanced plots to visualize your data. In this video, you’ll learn how to create several different types of plots including distribution plots, joint plots, and pair plots. After watching this video and learning several Seaborn commands/plots, there’s an activity right below this description for you to try out on your own using the skills you learned here. Enjoy!
SEABORN DISTRIBUTION PLOTS ACTIVITY:
Import libraries and load one Seaborn in-built dataset of your choice. Create a distribution plot, remove the line of best fit, then create a joint plot as well as a pair plot for the same dataset.
TIMESTAMP:
00:00 Introduction & Recap of Last Video
00:18 Lesson Structure for Seaborn Categorical Plots
00:29 Import libraries/dataset + set up for first plot
01:01 Explore distplot()
02:05 Create jointplot()
02:50 Create pairplot()
03:46 Recap of Current Video
04:00 Call-to-action: Seaborn Distribution Plots
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