You can use the bind_rows() function from the dplyr package in R to bind together two data frames by their rows:
bind_rows(df1, df2, df3, ...)
Similarly, you can use the bind_cols() function from dplyr to bind together two data frames by their columns:
bind_cols(df1, df2, df3, ...)
The following examples show how to use each of these functions in practice.
Example 1: Use bind_rows()
The following code shows how to use the bind_rows() function to bind three data frames together based on their rows:
library(dplyr)
#create data frames
df1 <- data.frame(team=c('A', 'A', 'B', 'B'),
points=c(12, 14, 19, 24))
df2 <- data.frame(team=c('A', 'B', 'C', 'C'),
points=c(8, 17, 22, 25))
df3 <- data.frame(team=c('A', 'B', 'C', 'C'),
assists=c(4, 9, 12, 6))
#row bind together data frames
bind_rows(df1, df2, df3)
team points assists
1 A 12 NA
2 A 14 NA
3 B 19 NA
4 B 24 NA
5 A 8 NA
6 B 17 NA
7 C 22 NA
8 C 25 NA
9 A NA 4
10 B NA 9
11 C NA 12
12 C NA 6
Notice that this function automatically fills in missing values with NA if the data frames do not all have the same column names.
Example 2: Use bind_cols()
The following code shows how to use the bind_cols() function to bind three data frames together based on their columns:
library(dplyr)
#create data frames
df1 <- data.frame(team=c('A', 'A', 'B', 'B'),
points=c(12, 14, 19, 24))
df2 <- data.frame(team=c('A', 'B', 'C', 'C'),
points=c(8, 17, 22, 25))
df3 <- data.frame(team=c('A', 'B', 'C', 'C'),
assists=c(4, 9, 12, 6))
#column bind together data frames
bind_cols(df1, df2, df3)
team points assists steals blocks rebounds
1 A 12 A 8 A 4
2 A 14 B 17 B 9
3 B 19 C 22 C 12
4 B 24 C 25 C 6
Notice that the original columns from each data frame appear in the final data frame in the order that we specified them in the bind_cols() function.
Additional Resources
The following tutorials explain how to bind together data frames using the rbind() and cbind() functions from base R:
The following tutorials explain how to perform other common functions in dplyr:
