Using prose, describe how the variables and observations are organised in each of the sample tables.
##Solutions
library(tidyverse)── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ──
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✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag() masks stats::lag()1.Using prose, describe how the variables and observations are organised in each of the sample tables
Sketch out the process you’d use to calculate the rate for table2 and table4a + table4b. You will need to perform four operations:
Extract the number of TB cases per country per year.
Extract the matching population per country per year.
Divide cases by population, and multiply by 10000.
Store back in the appropriate place.
table2 |>
pivot_wider(
names_from = type,
values_from = count
) |> mutate(rate = cases/population * 10000)# A tibble: 6 × 5
country year cases population rate
<chr> <dbl> <dbl> <dbl> <dbl>
1 Afghanistan 1999 745 19987071 0.373
2 Afghanistan 2000 2666 20595360 1.29
3 Brazil 1999 37737 172006362 2.19
4 Brazil 2000 80488 174504898 4.61
5 China 1999 212258 1272915272 1.67
6 China 2000 213766 1280428583 1.67 table4a |>
pivot_longer(
cols = -country,
names_to = "year",
values_to = "n"
)# A tibble: 6 × 3
country year n
<chr> <chr> <dbl>
1 Afghanistan 1999 745
2 Afghanistan 2000 2666
3 Brazil 1999 37737
4 Brazil 2000 80488
5 China 1999 212258
6 China 2000 213766