This content has appeared before in a dirty data post, but I still find myself googling these functions. So they deserve a post of their own. The tidyr package has several functions that allow you to reshape your data. They are surprisely useful; I have found myself gathering a lot, mostly to get data from “SPSS format” into something that ggplot will handle. I have also discovered the flexibility with which you can spread the data on a particular variable, do a set of computations, and then gather it back for plotting…. handy.
Use gather(data, key, value, …)
data = the dataframe you want to morph from wide to long
key = the name of the new column that is levels of what is represented in the wide format as many columns
value = the name of the column that will contain the values
… = columns to gather, or leave (use -column to gather all except that one)
Kudos to Garrick Aden-Buie for creating these gganimation gif to illustrate tidyr processes
Use spread(data, key, value)
data = the dataframe you want to morph from long to wide
key = the name of the column that contains the key
value = the name of the column contains the values
Use separate(data, col, into)
data = dataframe
col = name of column to separate
into = character vector of new column [note- these need quotes]
separate(treatments, year_no, c(“year”, “month”))
separate() assumes you want to split on a space, period, forward slash or dash. You can give it an extra argument sep = “-” to specify what to separate on.
Use unite(data, col, …)
data = dataframe
col = name of column to separate
… = bare names of columns to unite
