R rolling up rows to a single row (continuous & factor variables)

Question

I am trying to roll up a bunch of rows for one day into a single row. I would like it in dplyr if possible. I know that my code is far from correct, but this was how far I got:

data %>%
  group_by(DAY) %>%
  summarise_each(funs(Sum = n()), SEX, GROUP, TOTAL)

Original:

DAY SEX GROUP   TOTAL       
7/1/14  FEMALE  A   1       
7/1/14  FEMALE  B   1       
7/1/14  FEMALE  B   1       
7/1/14  FEMALE  A   1       
7/1/14  MALE    A   1       
7/1/14  MALE    B   2       

New:

DAY     FEMALE  MALE    GROUP_A GROUP_B TOTAL
7/1/14  4       2       3       3       7  

Answer 1

Another way with data.table, tested on a data.frame with more than one day.

require(data.table)
setDT(data)[, as.list(c(table(SEX), table(GROUP), TOTAL=sum(TOTAL))), by=DAY]

#      DAY FEMALE MALE A B TOTAL
#1: 7/1/14      3    0 1 2     3
#2: 8/1/14      1    2 2 1     4

EDIT: another, less manual, option (you don't need to know which variables are factors and which are numeric), thanks to some help from @jangorecki and @DavidArenburg

wh_num <- sapply(data, is.numeric)[-1]
wh_fact <-sapply(data, is.factor)[-1]
setDT(data)[, as.list(c(lapply(.SD[, wh_fact, with = FALSE], table), 
                        lapply(.SD[, wh_num, with = FALSE], sum), 
                        recursive = TRUE)), by = DAY]

#      DAY SEX.FEMALE SEX.MALE GROUP.A GROUP.B TOTAL
#1: 7/1/14          3        0       1       2     3
#2: 8/1/14          1        2       2       1     4

data

data <- structure(list(DAY = c("7/1/14", "7/1/14", "7/1/14", "8/1/14", 
"8/1/14", "8/1/14"), SEX = structure(c(1L, 1L, 1L, 1L, 2L, 2L
), .Label = c("FEMALE", "MALE"), class = "factor"), GROUP = structure(c(1L, 
2L, 2L, 1L, 1L, 2L), .Label = c("A", "B"), class = "factor"), 
    TOTAL = c(1L, 1L, 1L, 1L, 1L, 2L)), .Names = c("DAY", "SEX", 
"GROUP", "TOTAL"), row.names = c(NA, -6L), class = "data.frame")

Answer 2

It may seem a little arcane, but here is a short incantation

dat %>% group_by(DAY) %>%
  summarise_each(funs(ifelse(is.numeric(.), sum(.), list(table(.))))) -> res

data.frame(DAY=res$DAY, t(unlist(res[, 2:ncol(res)])))
#      DAY SEX.FEMALE SEX.MALE GROUP.A GROUP.B TOTAL
# 1 7/1/14          4        2       3       3     7

Here, you simply summarise each column as a table if it's not numeric, or sum it if it is (for the total column). This needs to be returned as a list since summarise_each expects a single value. Then, the result is expanded to a regular data.frame.