dplyr - R: adding together previous rows in a dataframe -

df

   patient.id index.admission.  adm_date dish_date bi 1         124            false  2/7/2009  2/8/2009  0 2         124             true  3/5/2009 3/15/2009  1 3         124            false  4/5/2011  4/7/2011  0 4         124            false 3/25/2012 3/27/2012  0 5         124             true  5/5/2012 5/20/2012  1 6         124             true  9/8/2013 9/15/2013  1 7         124            false  1/5/2014 1/15/2014  0 8         233            false  1/1/2010  1/8/2010  0 9         233            false  1/1/2011  1/5/2011  0 10        233             true  2/2/2011 2/25/2011  1 11        233            false 1/25/2012 1/28/2012  0 12        542             true  3/5/2015 3/15/2015  1 13       1243             true  2/5/2009  2/8/2009  1 14       1243             true  2/5/2011 2/19/2011  1 

i need create new column adds bi grouped patients.

my data should this:

   patient.id index.admission.  adm_date dish_date bi  num_index_ad 1         124            false  2/7/2009  2/8/2009  0  0 2         124             true  3/5/2009 3/15/2009  1  1 3         124            false  4/5/2011  4/7/2011  0  1 4         124            false 3/25/2012 3/27/2012  0  1 5         124             true  5/5/2012 5/20/2012  1  2 6         124             true  9/8/2013 9/15/2013  1  3 7         124            false  1/5/2014 1/15/2014  0  3 8         233            false  1/1/2010  1/8/2010  0  0 9         233            false  1/1/2011  1/5/2011  0  0 10        233             true  2/2/2011 2/25/2011  1  1 11        233            false 1/25/2012 1/28/2012  0  1 12        542             true  3/5/2015 3/15/2015  1  1 13       1243             true  2/5/2009  2/8/2009  1  1 14       1243             true  2/5/2011 2/19/2011  1  2 

using dplyri have:

df1 <- df %>%   group_by(patient.id) %>%    (i in df) {     mutate(num_index_ad = bi[lag(i),] +bi[i,])     } 

this gives error: "error in .subset2(x, i, exact = exact) : subscript out of bounds"

thanks in advance:

> dput(df) structure(list(patient.id = c(124l, 124l, 124l, 124l, 124l, 124l,  124l, 233l, 233l, 233l, 233l, 542l, 1243l, 1243l), index.admission. = c(false,  true, false, false, true, true, false, false, false, true, false,  true, true, true), adm_date = structure(c(8l, 10l, 12l, 9l, 13l,  14l, 4l, 1l, 2l, 5l, 3l, 11l, 6l, 7l), .label = c("1/1/2010",  "1/1/2011", "1/25/2012", "1/5/2014", "2/2/2011", "2/5/2009",  "2/5/2011", "2/7/2009", "3/25/2012", "3/5/2009", "3/5/2015",  "4/5/2011", "5/5/2012", "9/8/2013"), class = "factor"), dish_date = structure(c(7l,  8l, 11l, 10l, 12l, 13l, 1l, 4l, 3l, 6l, 2l, 9l, 7l, 5l), .label = c("1/15/2014",  "1/28/2012", "1/5/2011", "1/8/2010", "2/19/2011", "2/25/2011",  "2/8/2009", "3/15/2009", "3/15/2015", "3/27/2012", "4/7/2011",  "5/20/2012", "9/15/2013"), class = "factor"), bi = c(0, 1, 0,  0, 1, 1, 0, 0, 0, 1, 0, 1, 1, 1)), .names = c("patient.id", "index.admission.",  "adm_date", "dish_date", "bi"), row.names = c(na, -14l), class = "data.frame") 

i didn't find general dupe here additional solutions

df$num_index_ad <- with(df, ave(bi, patient.id, fun = cumsum))  

or

library(dplyr) df %>%    group_by(patient.id) %>%   mutate(num_index_ad = cumsum(bi)) 

or

library(data.table) setdt(df)[, num_index_ad := cumsum(bi), = patient.id]