how to merge data in r

Merging data in R involves combining data from two different data frames based on one or more common columns. This can be done using base R functions, such as merge(), or using more efficient and user-friendly functions from the tidyverse package.

Here is an example of merging two data frames in R using tidyverse:

main.r
library(tidyverse)

# Create two data frames to merge
df1 <- data.frame(id = 1:5, value1 = runif(5))
df2 <- data.frame(id = 3:7, value2 = runif(5))

# Merge the data frames based on the 'id' column
merged_df <- left_join(df1, df2, by = "id")

# View the merged data frame
merged_df
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In the example above, we create two data frames df1 and df2 with a common column id. We then use the left_join() function to merge df1 and df2 based on the id column. The resulting merged data frame contains all the rows from df1 and matching rows from df2, with NA values in the value2 column for non-matching rows.

Other useful functions for merging data in R include inner_join(), right_join(), and full_join(), which correspond to different types of SQL joins. Additionally, dplyr functions such as mutate(), filter(), and group_by() can be used to manipulate merged data frames further.