cumsum in grouped data with dplyr

Question

I have a data frame df (which can be downloaded here) referred to a register of companies that looks something like this:

    Provider.ID        Lo         


        

Answer 1

I got the solution to my problem. I restarted my session and I got my result grouping just by Local Authority and then arranging:

> df.1 = df %>% group_by(Local.Authority) %>%
+ mutate(cum.total = cumsum(total)) %>%
+ arrange(year, month, Local.Authority)
> df.1
Source: local data frame [41 x 8]
Groups: Local.Authority [36]

   Provider.ID  Local.Authority month  year entry  exit total cum.total
                             
1  1-102642676           Bexley    10  2010     1     0     1         1
2  1-102642676            Brent    10  2010     1     0     1         1
3  1-102642676 Bristol, City of    10  2010     1     0     1         1
4  1-102642676             Bury    10  2010     1     0     1         1
5  1-102642676   Cambridgeshire    10  2010     1     0     1         1
6  1-102642676    Cheshire East    10  2010     2     0     2         2
7  1-102642676      East Sussex    10  2010     5     0     5         5
8  1-102642676          Enfield    10  2010     1     0     1         1
9  1-102642676            Essex    10  2010     1     0     1         1
10 1-102642676        Hampshire    10  2010     1     0     1         1

Checking "Kent" now it yields the expected result:

> check = df.1 %>% filter(Local.Authority == "Kent")
> check
Source: local data frame [3 x 8]
Groups: Local.Authority [1]

  Provider.ID Local.Authority month  year entry  exit total cum.total
                           
1 1-102642676            Kent    10  2010     1     0     1         1
2 1-102642676            Kent     9  2011     0     1    -1         0
3 1-102642676            Kent    10  2014     1     0     1         1