Read R4DS chapter 12.
Solve the chapters Tidy Data and From Wide to Long and Back of the Reshaping Data with tidyr 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 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.