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Shiny Cheat Sheet

May 31, 2019

If you’re ready to build interactive web apps with R, say hello to Shiny. This cheat sheet provides a tour of the Shiny package and explains how to build and customize an interactive app. Be sure to follow the links on the sheet for even more information. Updated 01/16.

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Data Visualization Cheat Sheet

The ggplot2 package lets you make beautiful and customizable plots of your data.

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RStudio IDE Cheat Sheet

No matter what you do with R, the RStudio IDE can help you do it faster. This cheat sheet will guide you th...

Shiny Cheat Sheet

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The Latest Resources

The devtools package makes it easy to build your own R packages, and packages make it easy to share your R code.

The ggplot2 package lets you make beautiful and customizable plots of your data.

No matter what you do with R, the RStudio IDE can help you do it faster. This cheat sheet will guide you through the most useful features of the IDE, as well as the long list of keyboard shortcuts.

R Markdown is an authoring format that makes it easy to write reusable reports with R.

Sparklyr provides an R interface to Apache Spark, a fast and general engine for processing Big Data.

This cheat sheet will guide you through the grammar, reminding you how to select, filter, arrange, mutate, summarise, group, and join data frames and tibbles.

The Data Import cheat sheet reminds you how to read in flat files with the readr package and work with the results as tibbles, and reshape messy data with tidyr.

This cheatsheet will remind you how to manipulate lists with purrr as well as how to apply functions iteratively to each element of a list or vector.

The stringr package provides an easy to use toolkit for working with strings, i.e. character data, in R.

This lubridate cheatsheet covers how to round dates, work with time zones, extract elements of a date or time, parse dates into R and more.

Keras is a high-level neural networks API developed with a focus on enabling fast experimentation.

Tidy Evaluation (Tidy Eval) is a framework for doing non-standard evaluation in R that makes it easier to program with tidyverse functions.

This cheatsheet reminds you how to make factors, reorder their levels, recode their values, and more.

The reticulate package provides a comprehensive set of tools for interoperability between Python and R.