Programming Resources

Regular Expressions
https://regexr.com/

Setting Up R for Performing Basic Statistical Analyses

Installing Main Programs

Make sure these are installed.

• R
• https://www.r-project.org/
• R Studio
• https://www.rstudio.com/

Working in an R notebook allows you to keep a copy of the code you've run and generate output you can save and share.

• R Studio - File - New File - New Notebook

R Studio Add Ins

R Studio allows for installation of add-ins. The GREA add-in which allows for the import of many types of data files into R seems like it will be useful.

(The code snippets which follow are R code insertions in an R notebook in R Studio.)


R Package Management for Specific Projects

I can never remember what packages I used after I tried something but I haven't worked on it for a while. I found keeping a list of the packages I need and letting R do the tedious work of making sure they're ready to use reduces my frustration level.



R Packages Mentioned in This Post

• devtools
• collection of package development tools
• https://cran.r-project.org/web/packages/devtools/index.html
• GREA
• R Studio add-in for importing data files (not a package)
• https://github.com/Stan125/GREA
• rio
• package to simplify importing and exporting data sets
• https://cran.r-project.org/web/packages/rio/index.html
• https://cran.r-project.org/web/packages/rio/rio.pdf
• https://cran.r-project.org/web/packages/rio/vignettes/rio.html

R Learning Resources

R for basic statistical analysis
http://www.gardenersown.co.uk/education/lectures/r/basics.htm#basic_stats

Applied Statistics with R (online text)
https://daviddalpiaz.github.io/appliedstats/

Quick R
http://www.statmethods.net/stats/ttest.html

R for Data Science online book
http://r4ds.had.co.nz/

A Layered Grammar of Graphics (intro to concepts behind ggplot2)
http://vita.had.co.nz/papers/layered-grammar.pdf

R data exploration

histograms for all numeric variables in data frame
https://www.r-bloggers.com/quick-plot-of-all-variables/

> dataset %>%
+ keep(is.numeric) %>%
+ gather() %>%
+ ggplot(aes(value)) +
+ facet_wrap(~key, scales = "free") +
+ geom_histogram()

Plotting in R
http://www.stat.wisc.edu/~larget/stat302/chap2.pdf


data frame column types
numeric
double
interger
logical
factor

messy data frames
http://www.win-vector.com/blog/2015/04/what-can-be-in-an-r-data-frame-column/
POSIXlt
Arbitrary lists
Matrices
Data frames