I have these two tables;
<A> <B>
a1 a2 b1
ABC CAFE AB
ABD DRINK BF
ABF CAFE ..
ABFF DRINK
.. ..
I would like to know the summarize table containing B to a1 in table A like this;
library(dplyr)
library(stringr)
A1 <- A %>%
filter(str_detect(a1, "AB")) %>%
group_by(a2) %>%
summarize(n())
A2 <- A %>%
filter(str_detect(a1, "BF")) %>%
group_by(a2) %>%
summarize(n())
However, I should make the code several times so that I would like to a function to input the B table in the str_detect function... How do I make the function?
Here I designed a function called count_fun
, which has four arguments. dat
is a data frame like A
, Scol
is a column with strings, Gcol
is the grouping column, and String
is the test string. See https://cran.r-project.org/web/packages/dplyr/vignettes/programming.html to learn how to design a function using dplyr
.
library(dplyr)
library(stringr)
count_fun <- function(dat, Scol, Gcol, String){
Scol <- enquo(Scol)
Gcol <- enquo(Gcol)
dat2 <- dat %>%
filter(str_detect(!!Scol, String)) %>%
group_by(!!Gcol) %>%
summarize(n())
return(dat2)
}
count_fun(A, a1, a2, "AB")
# # A tibble: 2 x 2
# a2 `n()`
# <chr> <int>
# 1 CAFE 2
# 2 DRINK 2
count_fun(A, a1, a2, "BF")
# # A tibble: 2 x 2
# a2 `n()`
# <chr> <int>
# 1 CAFE 1
# 2 DRINK 1
We can then apply count_fun
using lapply
to loop through every elements in B
.
lapply(B$b1, function(x){
count_fun(A, a1, a2, x)
})
# [[1]]
# # A tibble: 2 x 2
# a2 `n()`
# <chr> <int>
# 1 CAFE 2
# 2 DRINK 2
#
# [[2]]
# # A tibble: 2 x 2
# a2 `n()`
# <chr> <int>
# 1 CAFE 1
# 2 DRINK 1
DATA
A <- read.table(text = "a1 a2
ABC CAFE
ABD DRINK
ABF CAFE
ABFF DRINK
",
header = TRUE, stringsAsFactors = FALSE)
B <- data.frame(b1 = c("AB", "BF"), stringsAsFactors = FALSE)