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ggside: Plot Linear Regression using Marginal Distributions (ggplot2 extension)
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Marginal Distribution (Density) plots are a way to extend your numeric data with side plots that highlight the density (histogram or boxplots work too).
Marginal Distribution Plots were made popular with the seaborn jointplot() in Python. They can now be made in R using #ggside, an new #ggplot2 extension! You can make linear regression with marginal distributions using histograms, densities, box plots, and more.
Bonus - The side panels are super customizable for uncovering complex relationships.
GET THE CODE SHOWN IN THE VIDEO:
Are you ready to get a job, make a data science transition, and accelerate your career? Then read on!
MY COURSES WILL SKYROCKET 🚀 YOUR CAREER IN WEEKS:
TABLE OF CONTENTS
00:00 Introduction to ggside
00:25 GitHub Project Setup
01:13 Libraries: ggside, tidyverse, tidyquant
01:42 Data - mpg dataset
02:13 Plot 1 - Side-Density Plot with Scatterplot Main
06:26 Plot 2 - Faceted Main Plot with Side-Boxplot
Marginal Distribution Plots were made popular with the seaborn jointplot() in Python. They can now be made in R using #ggside, an new #ggplot2 extension! You can make linear regression with marginal distributions using histograms, densities, box plots, and more.
Bonus - The side panels are super customizable for uncovering complex relationships.
GET THE CODE SHOWN IN THE VIDEO:
Are you ready to get a job, make a data science transition, and accelerate your career? Then read on!
MY COURSES WILL SKYROCKET 🚀 YOUR CAREER IN WEEKS:
TABLE OF CONTENTS
00:00 Introduction to ggside
00:25 GitHub Project Setup
01:13 Libraries: ggside, tidyverse, tidyquant
01:42 Data - mpg dataset
02:13 Plot 1 - Side-Density Plot with Scatterplot Main
06:26 Plot 2 - Faceted Main Plot with Side-Boxplot
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ggside: Plot Linear Regression using Marginal Distributions (ggplot2 extension)
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