I have a dataset that has a column which consists of 0 and 1s. Is there a way that I can separate that column into two columns so that one column consists of the 0s and the other 1s?
I tried to used the separate function from tidyverse however, it hasn't worked yet.
We may use split in base R
lst1 <- split(df1$col1, df1$col1)
mx <- max(lengths(lst1))
data.frame(lapply(lst1, `length<-`, mx))
Or if we want to create two columns
library(dplyr)
library(tidyr)
library(data.table)
df1 %>%
mutate(rn = rowid(col1),
colnm = case_when(col1 == 0 ~ "col1", TRUE ~ "col2")) %>%
pivot_wider(names_from = colnm, values_from = col1) %>%
select(-rn)
-output
# A tibble: 8 × 2
col1 col2
<dbl> <dbl>
1 0 1
2 0 1
3 0 1
4 0 1
5 0 1
6 0 1
7 0 1
8 0 NA
df1 <- structure(list(col1 = c(0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1,
1, 1)), class = "data.frame", row.names = c(NA, -15L))
A simple ifelse statement could also be used to do this. -
df <- as.data.frame(c(0,0,1,0,1,1,0,0,0,0,0,1,0,0,0,0,1,1,0))
names(df)<-"col1"
df$col_0 <- ifelse(df$col1 == 0, 0, NA)
df$col_1 <- ifelse(df$col1 == 1, 1, NA)
Returns the following result:
> df
col1 col_0 col_1
1 0 0 NA
2 0 0 NA
3 1 NA 1
4 0 0 NA
5 1 NA 1
6 1 NA 1
7 0 0 NA
8 0 0 NA
9 0 0 NA
10 0 0 NA
11 0 0 NA
12 1 NA 1
13 0 0 NA
14 0 0 NA
15 0 0 NA
16 0 0 NA
17 1 NA 1
18 1 NA 1
19 0 0 NA
