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For a sample dataframe:

df <- structure(list(output.code = structure(1:15, .Label = c("E00000001",
       "E00000003", "E00000005", "E00000007", "E00000010", "E00000012", 
       "E00000013", "E00000014", "E00000016", "E00000017", "E00000018", 
       "E00000019", "E00000020", "E00000021", "E00000022"), class = "factor"), 
       all.usual = c(194L, 250L, 367L, 123L, 102L, 213L, 216L, 154L, 
       281L, 290L, 218L, 139L, 226L, 282L, 223L), same.address = c(176L, 
       218L, 288L, 83L, 80L, 196L, 134L, 125L, 228L, 218L, 189L, 
       112L, 185L, 235L, 192L), lsoa.code = structure(c(1L, 1L, 
       1L, 1L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 3L), .Label = c("E01000001", 
      "E01000002", "E01000003"), class = "factor")), .Names = c("output.code", 
       "all.usual", "same.address", "lsoa.code"), class = "data.frame", row.names = c(NA, 
       -15L))

I am trying to aggregate two columns into a new dataframe using dplyr.

For one column, I found this to work:

library(dplyr)
df %>% 
  group_by(lsoa.code) %>% 
  summarise(all.usual = sum(all.usual))

But I wish to sum the values of all the 'lsoa.codes' for the two variables (same.address and all.usual).

This doesn't work:

df %>% 
  group_by(lsoa.code) %>% 
  summarise(all.usual = sum(all.usual)
  summarise(same.address = sum(same.address))

Can someone please advise how this code may be adapted to aggregate the two columns?

Also, I wish to create a dataframe from the results.

Many thanks in advance.

KT_1
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    use `summarise_each(funs(sum), all.usual, same.address)` or `summarise(all.usual = sum(all.usual), same.address = sum(same.address))` – Jaap Mar 30 '16 at 15:24
  • Take @ProcrastinatusMaximus 's first solution. It's good to learn the right way – Pierre L Mar 30 '16 at 15:37

1 Answers1

2

Like this?

    df %>%
    group_by(lsoa.code) %>% 
    summarise(all.usual = sum(all.usual), same.address = sum(same.address))
Pierre L
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denise
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