Often you may be interested in joining multiple data frames in R. Fortunately this is easy to do using the left_join() function from the dplyr package.
library(dplyr)
For example, suppose we have the following three data frames:
#create data frame
df1 <- data.frame(a = c('a', 'b', 'c', 'd', 'e', 'f'),
b = c(12, 14, 14, 18, 22, 23))
df2 <- data.frame(a = c('a', 'a', 'a', 'b', 'b', 'b'),
c = c(23, 24, 33, 34, 37, 41))
df3 <- data.frame(a = c('d', 'e', 'f', 'g', 'h', 'i'),
d = c(23, 24, 33, 34, 37, 41))
To join all three data frames together, we can simply perform two left joins, one after the other:
#join the three data frames df1 %>% left_join(df2, by='a') %>% left_join(df3, by='a') a b c d 1 a 12 23 NA 2 a 12 24 NA 3 a 12 33 NA 4 b 14 34 NA 5 b 14 37 NA 6 b 14 41 NA 7 c 14 NA NA 8 d 18 NA 23 9 e 22 NA 24 10 f 23 NA 33
Note that you can also save the result of this join as a data frame:
#join the three data frames and save result as new data frame named all_data all_data <- df1 %>% left_join(df2, by='a') %>% left_join(df3, by='a') #view summary of resulting data frame glimpse(all_data) Observations: 10 Variables: 4 $ a <chr> "a", "a", "a", "b", "b", "b", "c", "d", "e", "f" $ b <dbl> 12, 12, 12, 14, 14, 14, 14, 18, 22, 23 $ c <dbl> 23, 24, 33, 34, 37, 41, NA, NA, NA, NA $ d <dbl> NA, NA, NA, NA, NA, NA, NA, 23, 24, 33
Additional Resources
How to Filter Rows in R
How to Remove Duplicate Rows in R
How to Group & Summarize Data in R