Data Science In R - The Ultimate R Cheat Sheet - The Ultimateness Just Doubled!

Written by Matt Dancho

The Ultimate R Cheat Sheet simply put makes it easy to learn R. The Ultimate R Cheat Sheet saves you time by providing hyperlinks to the documentation and package-level cheat sheets for the most important packages in R. The latest update doubles its ultimateness by providing a second page that includes Special Topics:

Time Series, Forecasting, and Financial Analysis
Network Analysis and Natural Language Processing
Geospatial Analysis
Machine Learning and Deep Learning
Speed and Scale, Interoperability, and Miscellaneous Topics

Data Science In R - Ultimate R Cheat Sheet

About The Ultimate R Cheat Sheet

The Ultimate R Cheat Sheet links to every document you need by including visuals for where each package fits in the process.

Ultimate R Cheat Sheet - Page 1

About The Upgrade - Special Topics (Page 2)

We’ve now added a second sheet that includes special topics shown here.

Ultimate R Cheat Sheet - page 1

Learn R for Business With The Ultimate R Cheat Sheet

Learn tools that will advance your career while generating business value for your organization.

Learn by following the Ultimate R Cheat Sheet
Follow a clear-cut path from data import to business reporting
Learn dplyr and tidyr for cleaning and wrangling data
Learn ggplot2 for visualization
Learn rmarkdown for business reporting
Learn 2 modeling techniques: regression and clustering
All while solving 2 business projects!
Life-time access and no prerequisites!

Get Started Today

Download The Ultimate R Cheat Sheet

Data Science In R - Ultimate R Cheat Sheet

Download Ultimate R Cheat Sheet

Like our cheat sheets? Get them all!

Learn R for Business With The Ultimate R Cheat Sheet

We offer a Business-First Course that teaches 10 of the tools on Page 1 of the Ultimate R Cheat Sheet.

Data Science With R Toolchain

10+ core tidyverse packages and more!

You will learn:

dplyr and tidyr for data cleaning, wrangling, and manipulation
lubridate, stringr, and forcats for working with time series, text, and categorical data
ggplot2 for building advanced visualizations
purrr for iterating and scaling up analyses
broom for modeling with base R
rmarkdown for business reporting

How You Learn: Project-Based Learning

The student also solves 2 projects during the course:

New Product Pricing Algorithm - Help your R&D department develop new products that fill gaps in the current product portfolio
Customer Segmentation - Help your Marketing department target customers with emails aligned with customer interests

You finish the course with two reports (one for each project). Here’s an example of the Customer Segmentation project report.

Customer Segmentation Report