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Often I go about joining two dataframes together that have the same name. Is there a way to do this within the join-step so that I don't end up with a .x and a .y column? So the names might be 'original_mpg', and 'new_mpg'?
library(dplyr) left_join(mtcars, mtcars[,c("mpg",'cyl')], by=c("cyl")) names(mtcars) #ugh 
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The join() functions from dplyr preserve the original order of rows in the data frames while the merge() function automatically sorts the rows alphabetically based on the column you used to perform the join.
Method 1: using colnames() method colnames() method in R is used to rename and replace the column names of the data frame in R. The columns of the data frame can be renamed by specifying the new column names as a vector. The new name replaces the corresponding old name of the column in the data frame.
How do I concatenate two columns in R? To concatenate two columns you can use the <code>paste()</code> function. For example, if you want to combine the two columns A and B in the dataframe df you can use the following code: <code>df['AB'] <- paste(df$A, df$B)</code>.
The merge() function in base R can be used to merge input dataframes by common columns or row names. The merge() function retains all the row names of the dataframes, behaving similarly to the inner join. The dataframes are combined in order of the appearance in the input function call.
Currently, this is an open issue with dplyr. You'll either have to rename before or after the join or use merge from base R, which takes a suffixes argument.
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The default suffixes, c(".x", ".y"), can be overridden by passing them as a character vector of length 2:
library(dplyr) left_join(mtcars, mtcars[,c("mpg","cyl")], by = c("cyl"), suffix = c("_original", "_new")) %>% head() Output
mpg_original cyl disp hp drat wt qsec vs am gear carb mpg_new 1 21 6 160 110 3.9 2.62 16.46 0 1 4 4 21.0 2 21 6 160 110 3.9 2.62 16.46 0 1 4 4 21.0 3 21 6 160 110 3.9 2.62 16.46 0 1 4 4 21.4 4 21 6 160 110 3.9 2.62 16.46 0 1 4 4 18.1 5 21 6 160 110 3.9 2.62 16.46 0 1 4 4 19.2 6 21 6 160 110 3.9 2.62 16.46 0 1 4 4 17.8 If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
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