5.2 Tidy Data

In the previous example, our data were organized where day and quantity caught shared common columns. That is, not every variable had a dedicated column and consequently, not every variable had a value in every given cell - day did not have any cell values.

Tidy data breaks this down and reserves one column per variable and one row per observation. Remember, we have three variables: site, day, and quantity caught. So let’s transform this…

First, working with a collection tool where we have one table per day:

Site	Day	Trout_Caught
Mabel-lake	1	1
Postill-lake	1	3
Ellison-lake	1	0

Site	Day	Trout_Caught
Mabel-lake	2	3
Postill-lake	2	4
Ellison-lake	2	5

Site	Day	Trout_Caught
Mabel-lake	3	3
Postill-lake	3	5
Ellison-lake	3	1

And second, gathering this data into a single dataset, sorted by site:

Site	Day	Trout_Caught
Mabel-lake	1	1
Mabel-lake	2	3
Mabel-lake	3	3
Postill-lake	1	3
Postill-lake	2	4
Postill-lake	3	5
Ellison-lake	1	0
Ellison-lake	2	5
Ellison-lake	3	1

Now that’s tidy data!