merging several dataframes using plyr::join_all in R

Merging multiple dataframes is simple with the join_all function in the plyr R package. Here’s a quick guide:

Install and load plyr

install.packages("plyr")
library(plyr)

Using join_all

# Sample dataframes
df1 <- data.frame(ID = c(1, 2, 3), Value1 = c("A", "B", "C"))
df2 <- data.frame(ID = c(2, 3, 4), Value2 = c("D", "E", "F"))
df3 <- data.frame(ID = c(1, 3, 4), Value3 = c("G", "H", "I"))

# List of dataframes
dfs <- list(df1, df2, df3)

# Merge all dataframes using join_all
merged_df <- join_all(dfs, by = "ID", type = "full")

print(merged_df)

Results

  ID Value1  Value2  Value3
1  1      A   <NA>      G
2  2      B      D   <NA>
3  3      C      E      H
4  4   <NA>      F      I

• by = "ID": specifies the common column to merge by.
• type = "full": specifies a full join, meaning all rows from all dataframes are included.

Choosing the type of join

You can also specify other types of joins such as “left”, “right”, or “inner” depending on your needs:

• Left join: includes all rows from the first dataframe and matches from others.
• Right join: includes all rows from the last dataframe and matches from others.
• Inner join: includes only rows that have matches in all dataframes.

merged_df_inner <- join_all(dfs, by = "ID", type = "inner")

plyr::join_all makes merging multiple dataframes easy and efficient, with flexible join options to suit your specific needs.