For a time series analysis, I have a data frame that is based on periods. I have a column with starters and a column with patients who discontinue therapy. Now I want to calculate the current users of therapy per period. I calculated the difference between 'starters' and 'discontinue' as an intermediate step.
> df <- data.frame(
period = c(1,2,3,4,5,6),
starters = c(595, 113, 36, 489, 28, 101),
discontinue = c(0, 11, 6, 8, 14, 8))
> df$difference <- df$starters - df$discontinue
> df
period starters discontinue difference
1 1 595 0 595
2 2 113 11 102
3 3 36 6 30
4 4 489 8 481
5 5 28 14 14
6 6 101 8 93
To calculate current users, I would like to add a column 'current.users' with initial value = df$difference[1] and adds the difference each row. Output should look like:
> df
period starters discontinue difference current.users
1 1 595 0 595 595
2 2 113 11 102 697
3 3 36 6 30 727
4 4 489 8 481 1208
5 5 28 14 14 1222
6 6 101 8 93 1315
I tried to use for loops and data.table, but I can not calculate the next value in the column based on the previous value in the same column. Does anyone know the correct code for this issue? Thanks in advance!
With dplyr
library(tidyverse)
df %>%
mutate(difference = starters - discontinue,
current.users = cumsum(difference))
period starters discontinue difference current.users
1 1 595 0 595 595
2 2 113 11 102 697
3 3 36 6 30 727
4 4 489 8 481 1208
5 5 28 14 14 1222
6 6 101 8 93 1315
Without the difference column
df %>%
mutate(current.users = cumsum(starters - discontinue))
period starters discontinue current.users
1 1 595 0 595
2 2 113 11 697
3 3 36 6 727
4 4 489 8 1208
5 5 28 14 1222
6 6 101 8 1315