Add and mutate columns in data frame reflecting cumulative data of existing variables

I'm still very new to R so apologies for tedious questions.
I have the dataframe:

Code   Country     Date.x     Continent NewCases NewDeaths
1  ARG Argentina 2020-03-14 South America        3         1
2  ARG Argentina 2020-03-14 South America        3         1
3  ARG Argentina 2020-03-14 South America        3         1
4  ARG Argentina 2020-03-14 South America        3         1
5  ARG Argentina 2020-03-14 South America        3         1
6  ARG Argentina 2020-03-14 South America        3         1
  Recovered     Date.y NewTests Population    GDP GDPCapita
1         1 2020-03-04        0   44494502 637486     14400
2         1 2020-03-06        0   44494502 637486     14400
3         1 2020-03-07        0   44494502 637486     14400
4         1 2020-03-08        0   44494502 637486     14400
5         1 2020-03-09        0   44494502 637486     14400
6         1 2020-03-16        0   44494502 637486     14400

and I'm looking to add 4 new cumulative variables, "Cumulative_Cases", "Cumulative_Deaths", "Cumulative_Recovered" & "Cumulative_Tests", for each country up to the date of the observation.

My understanding is I need to firstly, arrange the dataframe by date and country? Then for each new variable groupby country then mutate using the cumsum function?

Yes, :slight_smile: you're on the right track.

p.s. You had a good instinct to share something about the data of concern, you even styled it which is appreciated ! however, the way you did it does not facilitate easy copy and pasting of your data, so a user can easily add it to their R session.

You can read this guide to see how such things are possible via datapasta package, or base::dput()
FAQ: How to do a minimal reproducible example ( reprex ) for beginners

This topic was automatically closed 21 days after the last reply. New replies are no longer allowed.

If you have a query related to it or one of the replies, start a new topic and refer back with a link.

Thanks @nirgrahamuk really appreciate the tips on how to provide a better example I'll definitely keep it in mind for next time!
I've tried using this code to arrange my dataframe

group_by(MASTER_COVID, Country) %>%
               arrange(date, .by_group = TRUE)

But I am receiving the error

Error: arrange() failed at implicit mutate() step. 
x Could not create a temporary column for `..2`.
i `..2` is `date`.

Could you enlighten me as to why?

I thought you had date.x and date.y but now you reference date?

in principle theres no problem with the approach

mtcars %>%
group_by(gear, cyl) %>%
  arrange(mpg, .by_group = TRUE)

Therefore if you have problems with your script, it must be data related.

Yes sorry, I decided to streamline my data with all dates into one column