I am creating two employment growth graphs that span over a 60-year period.
The dataset shows the year and month, the metro area, and the size of the total labor force, and it is structured like this:
Year Period Area No. of jobs
2016 Jan Metro1 10000
2016 Feb Metro1 10200
...
2021 May Metro2 14800
2021 Jun Metro1 15000
2016 Jan Metro2 30000
2016 Feb Metro2 30200
...
2021 May Metro2 48800
2021 Jun Metro2 50000
I need to calculate the monthly change and the cumulative growth for each metro which I have already done using dplyr:
data_update <- data %>%
group_by(Area) %>%
mutate(Monthly_Change = (`No. of jobs` - lag(`No. of jobs`))) %>%
replace_na(list(Monthly_Change = 0)) %>%
mutate(Cummulative_Growth = cumsum(Monthly_Change))
However, my problem is that this calculates the cumulative growth for a period greater than 60 months because I can only download the data for every month of every year. In other words, the selection dialogue requires me to select the years in one box and then the months in a separate box so if I were to not include January 2016 because it exceeds the 60 month period then January 2017-2021 would not be included either.
Is there a way to group the data by area and then subset the last 60 rows of each group?
