I think you are looking for reshaping your data using pivot_wider
from tidyr
:
library(tidyr)
df %>% pivot_wider(., names_from = age, values_from = freq)
# A tibble: 4 x 4
sex survive child adult
<fct> <fct> <int> <int>
1 male yes 4 0
2 female yes 6 3
3 male no 1 0
4 female no 2 1
or
library(tidyr)
df %>% pivot_wider(., names_from = c(age, survive), values_from = freq)
# A tibble: 2 x 5
sex child_yes adult_yes child_no adult_no
<fct> <int> <int> <int> <int>
1 male 4 0 1 0
2 female 6 3 2 1
Is it what you are looking for ? If not, can you provide the expected outcome ?
Data
df = structure(list(sex = structure(c(2L, 2L, 1L, 1L, 2L, 2L, 1L,
1L), .Label = c("female", "male"), class = "factor"), age = structure(c(2L,
1L, 2L, 1L, 2L, 1L, 2L, 1L), .Label = c("adult", "child"), class = "factor"),
survive = structure(c(2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L), .Label = c("no",
"yes"), class = "factor"), freq = c(4L, 0L, 6L, 3L, 1L, 0L,
2L, 1L)), class = "data.frame", row.names = c(NA, -8L))