Read R4DS chapter 12.
Solve Introduction and exploring raw data and Tidying data of the Cleaning Data in R course at DataCamp.
Class_files/Statistikdatabasen_2019-11-14 23_25_40.csv contains records of adults visiting dental care by sex, municipality and year (downloaded from The National Board of Health and Welfare dental health records). Read it withdental_data <- read_csv2("Class_files/Statistikdatabasen_2019-11-14 23_25_40.csv", skip = 1, n_max = 580)
(why skip = 1 and n_max = 580?) and use pivot_longer (or the deprecated version of it gather) to convert it to long (“tidy”) format.
Class_files/Statistikdatabasen_2018-01-23 15_04_12.csv contains records of suicides and death totals by sex, county and year (from The National Board of Health and Welfare). Read it withdata <- read_csv2("Class_files/Statistikdatabasen_2018-01-23 15_04_12.csv", skip = 1, n_max = 80)
and plot the proportion of suicides among death totals, by year, for the whole country.
The file Class_files/Statistikdatabasen_2018-01-23 15_39_06.csv contains monthly records of social assistance (ekonomiskt bistånd). Explore it in a spread sheet and transform to “tidy format” containing the variable average payment per houshold (Utbetalt ekonomiskt bistånd tkr divided by Antal hushåll) for each month and county. It may be helpful to join the first two columns using paste.
Examination of the course Matematik I (MM2001) consists a large number of smaller labs/exams with individual codes (Provkoder), see the course plan for a full list. The file Class_files/MM2001.csv contains results for 100 randomly chosen students exported using and older version of Ladok. Each row corresponds to one student (name and id removed). Transform data (or a subset of data) to a tidy format.