What is Tidyverse
tidyverse in the R ecosystem
Where does Tidyverse come from?
Packages are developed and maintained by RStudio Inc.
- Also make RStudio, Rstudio Server, Shiny, and a variety of other tools.
- Open source with commercial products available.
Many publications including:
- Wickham, Hadley. “Tidy data.” Journal of Statistical Software 59.10 (2014): 1-23.
- Wickham, Hadley. “An introduction to ggplot: an implementation of the grammar of graphics in R.” Statistics (2006).
- Wickham, Hadley. “ggplot2.” Wiley Interdisciplinary Reviews: Computational Statistics 3.2 (2011): 180-185.
- Wickham, Hadley. “Reshaping data with the reshape package.” Journal of statistical software 21.12 (2007): 1-20.
Why was tidyverse invented?
- Out of a sense of frustration with some of the R’s warts including inconsistent syntax and naming schemes.
- Read more here http://r4stats.com/articles/why-r-is-hard-to-learn/
- In order to make some steps of analysis easier, especially data manipulation and munging.
“There are definitely some academic statisticians who just don’t understand why what I do is statistics, but basically I think they are all wrong . What I do is fundamentally statistics. The fact that data science exists as a field is a colossal failure of statistics. To me, that is what statistics is all about. It is gaining insight from data using modelling and visualization. Data munging and manipulation is hard and statistics has just said that’s not our domain.” –Hadley Wickham
- To provide a unified approach for doing Data Science
- Because people don’t format their Excel spreadsheets very nicely!
Tidyverse controversy
The growing popularity of the tidyverse has led to some controversy, and some great memes!
https://twitter.com/_ColinFay/status/901167200496750592/photo/1
Some of these concerns have been outlined in the TidyverseSkeptic document, these include:
- Tidyverse makes learning harder, due to adding much complexity leading to cognitive overload
- tidyverse tends to be verbose, dplyr has hundreds of functions.
- Adoption of Tidyverse may give RStudio too much control of the open-source R project.
- RStudio provides frequent training sessions and webinars, many first time R users learn only tidyverse.
- There is evidence that people who only learn tidyverse see base R as outdated or obsolete.
- Widspread adoption of Tidyverse packages may limit adoption of technologically superior packages.
Read more of the back and forth at the following links:
https://www.r-bloggers.com/why-i-dont-use-the-tidyverse/
https://www.r-bloggers.com/the-tidyverse-curse/
http://varianceexplained.org/r/teach-tidyverse/
https://ds4ps.org/2019/04/20/datatable-vs-dplyr.html
https://twitter.com/hadleywickham/status/903102871163604994?lang=en
Alternatives:
- Base R
data.table is a fast alternative with its own special syntax.
- a tidyverse package, dtplyr is in development to prodvide access to it while maintaining tidyverse syntax.
- A comparison of common operations in data.table and dplyr can be found here.
Python pandas
Should you learn tidyverse?
Probably Yes
1) Data science and tidyverse are intertwined and growing rapidly.
2) “Future proof” yourself - if the next generation of R users are mostly tidyverse users, knowing tidyverse should be a safe bet for the next ~5+ years (probably?).
3) Future jobs / resume building.
4) Code examples, availability of help.
5) Because it makes the memes MUCH more enjoyable!
Getting setup
In the R console run the following commands to ensure that you have packages installed:
if (!any(rownames(installed.packages()) == "knitr")){
install.packages("knitr")
}
library(knitr)
if (!any(rownames(installed.packages()) == "tidyverse")){
install.packages("tidyverse")
}
library(tidyverse)
Download the template Markdown workshop document and open it
In the R console run the following command
download.file("https://raw.githubusercontent.com/ucdavis-bioinformatics-training/2019-Winter-Bioinformatics_Command_Line_and_R_Prerequisites_Workshop/master/Intro_to_R/Intro2R/Intro_to_tidyverse_and_ggplot2.Rmd", "Intro_to_tidyverse_and_ggplot2.Rmd")