tidyr

Principles of tidy data:

• Every column is a variable
• Every row is an observation
• Every cell is a single value

An example:

The code for this example using package tidyr is

tidydata <- messydata %>%
    pivot_longer(cols = !id, names_to = "roadtype", values_to = "mpg")

pivot_longer() “lengthens” data, increasing the number of rows and decreasing the number of columns. The inverse transformation is pivot_wider()

As we can see, the id column is essential. Sometimes data have row names, but don’t have a column name for them. Then we can create one manually

library(tidyverse)
mtcars %>%
    rownames_to_column("carname") %>%
    head()

• “Tidy” or “messy” depends on the use case. Sometimes, “tidy” data can be “messy” in other scenarios.