You can use the following methods to check if multiple columns are equal in a data frame in R:

Method 1: Check if All Columns Are Equal

library(dplyr)

#create new column that checks if all columns are equal
df <- df %>%
        rowwise %>%
        mutate(match = n_distinct(unlist(cur_data())) == 1) %>%
        ungroup()

Method 2: Check if Specific Columns Are Equal

library(dplyr)

#create new column that checks if columns 'A', 'C', and 'D' are equal
df_temp <- df %>%
             select('A', 'C', 'D') %>%
             rowwise %>%
             mutate(match = n_distinct(unlist(cur_data())) == 1) %>%
             ungroup()

#add new column to existing data frame
df$match <- df_temp$match

The following examples show how to use each method in practice with the following data frame:

#create data frame
df = data.frame(A=c(4, 0, 3, 3, 6, 8, 7),
                B=c(4, 2, 3, 5, 6, 4, 7),
                C=c(4, 0, 3, 3, 5, 10, 7),
                D=c(4, 0, 3, 3, 3, 8, 7))

#view data frame
df

  A B  C D
1 4 4  4 4
2 0 2  0 0
3 3 3  3 3
4 3 5  3 3
5 6 6  5 3
6 8 4 10 8
7 7 7  7 7

Example 1: Check if All Columns Are Equal

We can use the following syntax to check if the value in every column in the data frame is equal for each row:

library(dplyr)

#create new column that checks if all columns are equal
df <- df %>%
        rowwise %>%
        mutate(match = n_distinct(unlist(cur_data())) == 1) %>%
        ungroup()

#view updated data frame
df

# A tibble: 7 x 5
      A     B     C     D match
      
1     4     4     4     4 TRUE 
2     0     2     0     0 FALSE
3     3     3     3     3 TRUE 
4     3     5     3     3 FALSE
5     6     6     5     3 FALSE
6     8     4    10     8 FALSE
7     7     7     7     7 TRUE 

If the value in each column is equal, then the match column returns True.

Otherwise, it returns False.

Note that you can convert True and False values to 1 and 0 by using as.numeric() as follows:

library(dplyr)

#create new column that checks if all columns are equal
df <- df %>%
        rowwise %>%
        mutate(match = as.numeric(n_distinct(unlist(cur_data())) == 1)) %>%
        ungroup()

#view updated data frame
df

# A tibble: 7 x 5
      A     B     C     D match
      
1     4     4     4     4     1
2     0     2     0     0     0
3     3     3     3     3     1
4     3     5     3     3     0
5     6     6     5     3     0
6     8     4    10     8     0
7     7     7     7     7     1

Example 2: Check if Specific Columns Are Equal

We can use the following syntax to check if the value in columns A, C, and D in the data frame are equal for each row:

library(dplyr)

#create new column that checks if columns 'A', 'C', and 'D' are equal
df_temp <- df %>%
             select('A', 'C', 'D') %>%
             rowwise %>%
             mutate(match = n_distinct(unlist(cur_data())) == 1) %>%
             ungroup()

#add new column to existing data frame
df$match <- df_temp$match

#view updated data frame
df

  A B  C D match
1 4 4  4 4  TRUE
2 0 2  0 0  TRUE
3 3 3  3 3  TRUE
4 3 5  3 3  TRUE
5 6 6  5 3 FALSE
6 8 4 10 8 FALSE
7 7 7  7 7  TRUE

Otherwise, it returns False.