Factors are R’s data structure for categorical data. The forcats package makes it easy to work with factors. This cheatsheet reminds you how to make factors, reorder their levels, recode their values, and more. Updated 2/19.
Other content in this Stream
52:21Training your TensorFlow models in the cloud
TensorFlow is an open-source software library for numerical computation using data flow graphs.
Deep Learning with Keras Cheat Sheet
Keras is a high-level neural networks API developed with a focus on enabling fast experimentation.
46:23A new set of IDE features to help you and your team work better and faster together
RStudio Server Pro has a whole new set of features designed to help you and your team work better and faster together.
43:40Thinking inside the box: you can do that inside a data frame?!
The data frame is a crucial data structure in R and, especially, in the tidyverse. Working on a column or a variable is a very natural operation, which is great. But what about row-oriented work?
55:42Creating and Preprocessing a Design Matrix with Recipes
In this talk, a new package called recipes is shown where the specification of model terms and preprocessing steps can be enumerated sequentially.
48:56Collaboration and time travel- version control with git, github and RStudio
Hadley Wickham presents and demonstrates how understanding git & github will give you two data science superpowers.
56:26Use JavaScript visualization libraries at the R console
HTMLwidgets are always hosted within an R package and include all of the source code for their dependencies. This is to ensure that code which depends on widgets doesn’t require an internet connection
47:16Effective frameworks for thinking about data analysis/data science problems in R
Hadley Wickham Chief Scientist at RStudio and Adjunct Professor of Statistics at Rice University will discuss broadly an effective framework for thinking about data analysis/data science problems in R
Tidy Evaluation with rlang Cheat Sheet
Tidy Evaluation (Tidy Eval) is a framework for doing non-standard evaluation in R that makes it easier to program with tidyverse functions.
Python with R and Reticulate Cheat Sheet
The reticulate package provides a comprehensive set of tools for interoperability between Python and R.
Work with Strings Cheat Sheet
The stringr package provides an easy to use toolkit for working with strings, i.e. character data, in R.
Apply Functions Cheat Sheet
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.
Package Development Cheat Sheet
The devtools package makes it easy to build your own R packages, and packages make it easy to share your R code.
Sparklyr Cheat Sheet