You can use the following basic syntax to combine rows with the same column values in a data frame in R:
library(dplyr) df %>% group_by(group_var1, group_var2) %>% summarise(across(c(values_var1, values_var2), sum))
The following example shows how to use this syntax in practice.
Example: Combine Rows with Same Column Values in R
Suppose we have the following data frame that contains information about sales and returns made by various employees at a company:
#create data frame df <- data.frame(id=c(101, 101, 102, 103, 103, 103), employee=c('Dan', 'Dan', 'Rick', 'Ken', 'Ken', 'Ken'), sales=c(4, 1, 3, 2, 5, 3), returns=c(1, 2, 2, 1, 3, 2)) #view data frame df id employee sales returns 1 101 Dan 4 1 2 101 Dan 1 2 3 102 Rick 3 2 4 103 Ken 2 1 5 103 Ken 5 3 6 103 Ken 3 2
We can use the following syntax to combine rows that have the same value in the id and employee columns and then aggregate the remaining columns:
library(dplyr) #combine rows with same value for id and employee and aggregate remaining columns df %>% group_by(id, employee) %>% summarise(across(c(sales, returns), sum)) # A tibble: 3 x 4 # Groups: id  id employee sales returns 1 101 Dan 5 3 2 102 Rick 3 2 3 103 Ken 10 6
The result is a data frame that combines all of the rows in the original data frame that had the same value in the id and employee columns and then calculates the sum of values in the sales and returns columns.
Note: We chose to aggregate the sales and returns columns using the sum function, but you can aggregate by another metric such as the mean if you’d like.
The following tutorials explain how to perform other common tasks in R: