There is a tibble that contains number 1 to 4.
library(tidyverse)
# reproducible data
sample_tbl <- structure(list(X1 = c(4L, 4L, 1L, 4L, 1L, 4L, 2L, 3L, 2L, 4L),
X2 = c(1L, 4L, 4L, 4L, 4L, 2L, 4L, 4L, 3L, 2L), X3 = c(4L,
3L, 3L, 3L, 2L, 2L, 1L, 1L, 4L, 2L), X4 = c(1L, 4L, 3L, 2L,
3L, 4L, 2L, 1L, 1L, 1L), X5 = c(1L, 3L, 3L, 1L, 2L, 2L, 3L,
3L, 4L, 1L), X6 = c(2L, 3L, 4L, 4L, 3L, 2L, 4L, 1L, 1L, 3L
), X7 = c(3L, 4L, 1L, 2L, 3L, 3L, 2L, 2L, 2L, 1L), X8 = c(2L,
4L, 4L, 2L, 3L, 2L, 3L, 4L, 3L, 4L), X9 = c(2L, 1L, 4L, 4L,
2L, 4L, 4L, 1L, 3L, 3L), X10 = c(3L, 4L, 1L, 3L, 1L, 2L,
1L, 2L, 2L, 3L)), class = c("tbl_df", "tbl", "data.frame"
), row.names = c(NA, -10L))
# A tibble: 10 x 10
X1 X2 X3 X4 X5 X6 X7 X8 X9 X10
<int> <int> <int> <int> <int> <int> <int> <int> <int> <int>
1 4 1 4 1 1 2 3 2 2 3
2 4 4 3 4 3 3 4 4 1 4
3 1 4 3 3 3 4 1 4 4 1
4 4 4 3 2 1 4 2 2 4 3
5 1 4 2 3 2 3 3 3 2 1
6 4 2 2 4 2 2 3 2 4 2
7 2 4 1 2 3 4 2 3 4 1
8 3 4 1 1 3 1 2 4 1 2
9 2 3 4 1 4 1 2 3 3 2
10 4 2 2 1 1 3 1 4 3 3
I want to change 1 and 2 to 0, and 3 to 4 to 1.
Expected Output:
# A tibble: 10 x 10
X1 X2 X3
<int> <int> ...
1 1 0 ...
2 1 1 ...
3 0 1 ...
4 1 1 ...
5 0 1 ...
6 1 0 ...
7 0 1 ...
8 1 1 ...
9 0 1 ...
10 1 0 ...
I thought I could use dplyr::mutate(), dplyr::across(), dplyr::case_when() but I cannot figure out how.
How can I do this?
CodePudding user response：
Using integer division by 3:
sample_tbl %/% 3
# X1 X2 X3 X4 X5 X6 X7 X8 X9 X10
# 1 1 0 1 0 0 0 1 0 0 1
# 2 1 1 1 1 1 1 1 1 0 1
# 3 0 1 1 1 1 1 0 1 1 0
# 4 1 1 1 0 0 1 0 0 1 1
# 5 0 1 0 1 0 1 1 1 0 0
# 6 1 0 0 1 0 0 1 0 1 0
# 7 0 1 0 0 1 1 0 1 1 0
# 8 1 1 0 0 1 0 0 1 0 0
# 9 0 1 1 0 1 0 0 1 1 0
# 10 1 0 0 0 0 1 0 1 1 1
CodePudding user response：
We can loop across the column, create a logical vector with %in% on the vector of values 3, 4 and coerce it to binary
library(dplyr)
sample_tbl <- sample_tbl %>%
mutate(across(everything(), ~ (. %in% c(3, 4))))
-output
sample_tbl
# A tibble: 10 x 10
X1 X2 X3 X4 X5 X6 X7 X8 X9 X10
<int> <int> <int> <int> <int> <int> <int> <int> <int> <int>
1 1 0 1 0 0 0 1 0 0 1
2 1 1 1 1 1 1 1 1 0 1
3 0 1 1 1 1 1 0 1 1 0
4 1 1 1 0 0 1 0 0 1 1
5 0 1 0 1 0 1 1 1 0 0
6 1 0 0 1 0 0 1 0 1 0
7 0 1 0 0 1 1 0 1 1 0
8 1 1 0 0 1 0 0 1 0 0
9 0 1 1 0 1 0 0 1 1 0
10 1 0 0 0 0 1 0 1 1 1
If we need to use case_when
sample_tbl <- sample_tbl %>%
mutate(across(everything(), ~ case_when(. %in% c(3, 4) ~ 1,
. %in% c(1, 2) ~ 0)))
Or using base R
sample_tbl[] <- lapply(sample_tbl, \(x) (x %in% c(3, 4)))
data
sample_tbl <- structure(list(X1 = c(4L, 4L, 1L, 4L, 1L, 4L, 2L, 3L, 2L, 4L),
X2 = c(1L, 4L, 4L, 4L, 4L, 2L, 4L, 4L, 3L, 2L), X3 = c(4L,
3L, 3L, 3L, 2L, 2L, 1L, 1L, 4L, 2L), X4 = c(1L, 4L, 3L, 2L,
3L, 4L, 2L, 1L, 1L, 1L), X5 = c(1L, 3L, 3L, 1L, 2L, 2L, 3L,
3L, 4L, 1L), X6 = c(2L, 3L, 4L, 4L, 3L, 2L, 4L, 1L, 1L, 3L
), X7 = c(3L, 4L, 1L, 2L, 3L, 3L, 2L, 2L, 2L, 1L), X8 = c(2L,
4L, 4L, 2L, 3L, 2L, 3L, 4L, 3L, 4L), X9 = c(2L, 1L, 4L, 4L,
2L, 4L, 4L, 1L, 3L, 3L), X10 = c(3L, 4L, 1L, 3L, 1L, 2L,
1L, 2L, 2L, 3L)), row.names = c(NA, -10L), class = c("tbl_df",
"tbl", "data.frame"))
CodePudding user response：
Here is a base R option.
Change 1 and 2 to 0 and remaining values to 1.
sample_tbl[sample_tbl == 1 | sample_tbl == 2] <- 0
sample_tbl[sample_tbl != 0] <- 1
sample_tbl
# X1 X2 X3 X4 X5 X6 X7 X8 X9 X10
# <int> <int> <int> <int> <int> <int> <int> <int> <int> <int>
# 1 1 1 1 1 1 0 0 1 1 1
# 2 0 1 0 0 1 1 0 1 1 1
# 3 1 1 0 1 0 1 1 0 1 0
# 4 1 1 1 1 1 1 1 0 0 1
# 5 1 0 1 1 0 1 1 1 0 0
# 6 1 1 0 1 1 1 1 1 0 1
# 7 0 1 1 0 1 1 0 0 0 1
# 8 1 1 0 1 0 0 1 1 0 1
# 9 1 0 1 1 1 1 1 1 1 1
#10 0 1 1 1 0 1 1 0 1 0