match and replace two columns of a three column dataframe with matching variables of another dataframe in r

You can achieve this by using the match function in R to replace the columns of one dataframe with the corresponding columns of another dataframe. Here is an example:


main.r
# Create the dataframes
df1 <- data.frame(
  var1 = c("a", "b", "c", "d"),
  var2 = c(1, 2, 3, 4),
  var3 = c(10, 20, 30, 40)
)

df2 <- data.frame(
  var1 = c("a", "b", "c", "d"),
  var2 = c(5, 6, 7, 8),
  var4 = c(50, 60, 70, 80)
)

# Match and replace columns
match_indices <- match(df1$var1, df2$var1)
df1$var2 <- df2$var2[match_indices]
df1$var3 <- df2$var4[match_indices]

# Print the updated dataframe
print(df1)
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21 lines

In this example, we match the var1 column of df1 with the var1 column of df2 using the match function, and then replace the var2 and var3 columns of df1 with the corresponding columns of df2.

Alternatively, you can use the merge function to achieve the same result:


main.r
# Merge df1 and df2 on var1
df1 <- merge(df1, df2, by = "var1", all.x = TRUE)
df1$var2 <- df1$var2.y
df1$var3 <- df1$var4
# Remove unnecessary columns
df1 <- df1[, c("var1", "var2", "var3")]
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7 lines

Note that the all.x = TRUE argument in the merge function ensures that all rows from df1 are included in the merged dataframe, even if there are no matches in df2.

Also, the dplyr package provides a convenient way to perform this operation:


main.r
library(dplyr)
df1 <- left_join(df1, df2, by = "var1") %>%
  mutate(var2 = var2.y, var3 = var4) %>%
  select(var1, var2, var3)
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