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In R, a logical vector can be created using the == operator to check whether the values in multiple columns are equal. This vector can then be used to subset the dataframe to view the rows where all the columns are equal. The function all() can also be used to create a single logical vector for the columns to check if all the values across multiple columns are equal. Different ways of combining the logical vectors can be used to achieve the desired result.
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.
The following tutorials explain how to perform other common tasks in R: