问题
I want to make cross table of a variable with all other variables in the data.frame.
library(tidyverse)
library(janitor)
humans <- starwars %>%
filter(species == "Human")
humans %>%
janitor::tabyl(gender, eye_color)
gender blue blue-gray brown dark hazel yellow
female 3 0 5 0 1 0
male 9 1 12 1 1 2
humans %>%
dplyr::select_if(is.character) %>%
dplyr::select(-name, -gender) %>%
purrr::map(.f = ~janitor::tabyl(dat = humans, gender, .x))
Error: Unknown columns `blond`, `none`, `brown`, `brown, grey`, `brown` and ...
Call `rlang::last_error()` to see a backtrace
回答1:
tably
takes names as arguments and you passed a vector to it.
If you use imap
you'll have access to the name of the column, that you can convert to a symbol, and as janitor
supports quasi-quotation you can write:
humans %>%
select_if(is.character) %>%
select(-name, -gender) %>%
imap(.f = ~janitor::tabyl(dat = humans, !!sym(.y), gender))
#$`hair_color`
# hair_color female male
# auburn 1 0
# auburn, grey 0 1
# auburn, white 0 1
# black 1 7
# blond 0 3
# brown 6 8
# brown, grey 0 1
# grey 0 1
# none 0 3
# white 1 1
#
# $skin_color
# skin_color female male
# dark 0 4
# fair 3 13
Interestingly tabyl.data.frame
calls an unexported function that works on symbols so by calling it directly we can skip the unquoting and use base R.
cols <- setdiff(names(Filter(is.character,humans)), c("name","gender"))
lapply(cols, function(x) janitor:::tabyl_2way(humans, as.name(x), quote(gender)))
# [[1]]
# hair_color female male
# auburn 1 0
# auburn, grey 0 1
# auburn, white 0 1
# black 1 7
# blond 0 3
# brown 6 8
# brown, grey 0 1
# grey 0 1
# none 0 3
# white 1 1
#
# [[2]]
# skin_color female male
# dark 0 4
To make it work with xtable
@akrun's suggestion works here as well :
humans %>%
select_if(is.character) %>%
select(-name, -gender) %>%
imap(.f = ~tabyl(dat = humans, !!sym(.y), gender) %>% rename_at(1,~"x")) %>%
xtableList
or
cols <- setdiff(names(Filter(is.character,humans)), c("name","gender"))
l <- lapply(cols, function(x) {
res <- janitor:::tabyl_2way(humans, as.name(x), quote(gender))
names(res)[1] <- "x"
res
})
xtableList(l)
回答2:
Assuming that we need pairwise table with 'gender'
humans %>%
dplyr::select_if(is.character) %>%
dplyr::select(-name, -gender) %>%
imap(~ tibble(!! .y := .x) %>%
mutate(gender = humans[['gender']]) %>%
janitor::tabyl(!!rlang::sym(names(.)[1]), gender))
#$hair_color
# hair_color female male
# auburn 1 0
# auburn, grey 0 1
# auburn, white 0 1
# black 1 7
# blond 0 3
# brown 6 8
# brown, grey 0 1
# grey 0 1
# none 0 3
# white 1 1
#$skin_color
# skin_color female male
# dark 0 4
# fair 3 13
# light 6 5
#...
Update
The xtable::xtableList
requires names to be same across the list
elements. To make that happen, change the first column name same across the list
elements and then create an identifier column
library(xtable)
humans %>%
dplyr::select_if(is.character) %>%
dplyr::select(-name, -gender) %>%
imap(~ tibble(!! .y := .x) %>%
mutate(gender = humans[['gender']]) %>%
janitor::tabyl(!!rlang::sym(names(.)[1]), gender) %>%
mutate(colNname = .y) %>%
rename_at(1, ~ 'Variable')) %>%
xtableList
回答3:
Using only data.table
(and one %>%
):
library(data.table)
swDT <- data.table(starwars)
setkey(swDT, gender, hair_color)
swDT[species == "Human"
][CJ(gender, hair_color, unique =TRUE), .N, .EACHI] %>%
dcast(hair_color ~ gender, value.var = "N")
hair_color female male
1: auburn 1 0
2: auburn, grey 0 1
3: auburn, white 0 1
4: black 1 7
5: blond 0 3
6: brown 6 8
7: brown, grey 0 1
8: grey 0 1
9: none 0 3
10: white 1 1
回答4:
The list-columns in starwars
add complexity, but here's an example with mtcars
: crosstab cyl
against all other variables.
mtcars %>%
tidyr::gather(var, value, -cyl) %>%
janitor::tabyl(cyl, value, var, show_missing_levels = FALSE) %>%
purrr::map2(.x = ., .y = names(.), ~ janitor::adorn_title(.x, col_name = .y))
Returns a list of crosstabs. cyl x am, cyl x carb, etc. :
$`am`
am
cyl 0 1
4 3 8
6 4 3
8 12 2
$carb
carb
cyl 1 2 3 4 6 8
4 5 6 0 0 0 0
6 2 0 0 4 1 0
8 0 4 3 6 0 1
...
If you will do further manipulation of these data.frames you may find this title option friendlier:
purrr::map2(.x = ., .y = names(.), ~ janitor::adorn_title(.x, col_name = .y, placement = "combined"))
Which gives you:
$vs
cyl/vs 0 1
4 1 10
6 3 4
8 14 0
来源:https://stackoverflow.com/questions/54377189/tidyverse-cross-tables-of-one-variable-with-all-other-variables-in-data-frame