CODEWITHSUNDEEP
r
Amy
Amy

Reputation: 113

How to merge two true/false variables in R?

I have four variables as below in a data.frame which continues on thousands of rows:

One      Two      Three    Four 

TRUE     TRUE     FALSE    FALSE
FALSE    TRUE     TRUE     TRUE
TRUE     FALSE    FALSE    TRUE
TRUE     TRUE     TRUE     FALSE
FALSE    TRUE     FALSE    TRUE
FALSE    FALSE    TRUE     FALSE
TRUE     FALSE    FALSE    TRUE

I want to create two new variables, one which merges columns one and two, the second which merges columns three and four. So each new column would display TRUE if either or both of the two columns displayed TRUE, and would display FALSE if both were false. The resulting data would look like this:

One      Two      OneTwo     Three    Four    ThreeFour

TRUE     TRUE     TRUE       FALSE    FALSE   FALSE
FALSE    TRUE     TRUE       TRUE     TRUE    TRUE
TRUE     FALSE    TRUE       FALSE    TRUE    TRUE
TRUE     TRUE     TRUE       FALSE    FALSE   FALSE
FALSE    FALSE    FALSE      FALSE    TRUE    TRUE
FALSE    FALSE    FALSE      TRUE     FALSE   TRUE
TRUE     FALSE    TRUE       FALSE    TRUE    TRUE

Any help would be much appreciated. I've looked through some other questions but can't find how to do this specifically.

Upvotes: 8

Views: 1310

Answers (6)

lroha
lroha

Reputation: 34406

You can achieve this in a vectorized way:

tf <- c(TRUE, FALSE)
nm <- names(df)

# Merge
res <- cbind(df, df[tf] | df[rev(tf)])

# Set the names
names(res) <- c(nm, paste0(nm[tf], nm[rev(tf)]))

Gives:

     V1    V2    V3    V4    V5    V6 V1V2  V3V4  V5V6
1 FALSE  TRUE  TRUE  TRUE  TRUE FALSE TRUE  TRUE  TRUE
2  TRUE  TRUE  TRUE  TRUE FALSE  TRUE TRUE  TRUE  TRUE
3  TRUE  TRUE  TRUE FALSE  TRUE FALSE TRUE  TRUE  TRUE
4  TRUE FALSE FALSE FALSE  TRUE  TRUE TRUE FALSE  TRUE
5  TRUE  TRUE FALSE FALSE FALSE FALSE TRUE FALSE FALSE

Data:

set.seed(5)
df <- as.data.frame(matrix(sample(c(TRUE, FALSE), 30, replace = TRUE), 5))

Upvotes: 4

elehna
elehna

Reputation: 126

Using the package dplyr you can do this:

library(dplyr)
data <- data %>% mutate(
   OneTwo = as.logical(One + Two),
   ThreeFour = as.logical(Three + Four))

This works since TRUE and FALSE are actually saved as 1 and 0 by the computer. R then codes values larger 0 as TRUE. To be a bit more "correct", you could also use this code, to get back 0s and 1s before converting them to logicals:

library(dplyr)
data <- data %>%
   mutate(
    OneTwo = as.logical(pmax(One, Two)),
    ThreeFour = as.logical(pmax(One, Two)))

Upvotes: 6

UseR10085
UseR10085

Reputation: 8146

Using case_when from dplyr package

library(dplyr)
df %>% 
  mutate(OneTwo = case_when(One == TRUE & Two == TRUE ~ TRUE,
                            One == FALSE & Two == TRUE ~ TRUE,
                            One == TRUE & Two == FALSE ~ TRUE,
                            One == FALSE & Two == FALSE ~ FALSE),
         ThreeFour = case_when(Three == TRUE & Four == TRUE ~ TRUE,
                               Three == FALSE & Four == TRUE ~ TRUE,
                               Three == TRUE & Four == FALSE ~ TRUE,
                               Three == FALSE & Four == FALSE ~ FALSE))

Upvotes: 1

Ronak Shah
Ronak Shah

Reputation: 388907

Here's a way which can be extended to any number of columns.

#Create group of every two columns
cols <- ceiling(seq_len(ncol(df))/2)
#Create column names
new_col <- tapply(names(df), cols, paste0, collapse = "")
#Split every two columns and use `|`.
df[new_col] <- sapply(split.default(df, cols), function(x) Reduce(`|`, x))
df

#    One   Two Three  Four OneTwo ThreeFour
#1  TRUE  TRUE FALSE FALSE   TRUE     FALSE
#2 FALSE  TRUE  TRUE  TRUE   TRUE      TRUE
#3  TRUE FALSE FALSE  TRUE   TRUE      TRUE
#4  TRUE  TRUE  TRUE FALSE   TRUE      TRUE
#5 FALSE  TRUE FALSE  TRUE   TRUE      TRUE
#6 FALSE FALSE  TRUE FALSE  FALSE      TRUE
#7  TRUE FALSE FALSE  TRUE   TRUE      TRUE

Upvotes: 3

Allan Cameron
Allan Cameron

Reputation: 173793

A generalizable solution for many columns. Here, the final two column are the results from comparing each pair of columns.

cbind(df, do.call(cbind, lapply(seq(length(df)/2) * 2, function(i) df[[i-1]] | df[[i]])))
    One   Two Three  Four     1     2
1  TRUE  TRUE FALSE FALSE  TRUE FALSE
2 FALSE  TRUE  TRUE  TRUE  TRUE  TRUE
3  TRUE FALSE FALSE  TRUE  TRUE  TRUE
4  TRUE  TRUE  TRUE FALSE  TRUE  TRUE
5 FALSE  TRUE FALSE  TRUE  TRUE  TRUE
6 FALSE FALSE  TRUE FALSE FALSE  TRUE
7  TRUE FALSE FALSE  TRUE  TRUE  TRUE

Upvotes: 3

bttomio
bttomio

Reputation: 2306

You could try this:

OneTwo <- ifelse(One == TRUE & Two == TRUE, TRUE,
                 ifelse(One == TRUE & Two == FALSE, TRUE,
                        ifelse(One == FALSE & Two == TRUE, TRUE,
                               ifelse(One == FALSE & Two == FALSE, FALSE)))

Upvotes: 1

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