Left join only selected columns in R with the merge() function

Question

I am trying to LEFT Join 2 data frames but I do not want join all the variables from the second data set:

As an example, I have dataset 1 (DF1):

  Cl    Q   Sales  Date    A    2   30     01/01/2014    A    3   24     02/01/2014    A    1   10     03/01/2014    B    4   10     01/01/2014    B    1   20     02/01/2014    B    3   30     03/01/2014 

And I would like to left join dataset 2 (DF2):

Client  LO  CON    A    12  CA    B    11  US    C    12  UK    D    10  CA    E    15  AUS    F    91  DD 

I am able to left join with the following code:

merge(x = DF1, y = DF2, by = "Client", all.x=TRUE) :

   Client Q    Sales   Date             LO      CON    A      2    30      01/01/2014       12      CA    A      3    24      02/01/2014       12      CA    A      1    10      03/01/2014       12      CA    B      4    10      01/01/2014       11      US    B      1    20      02/01/2014       11      US    B      3    30      03/01/2014       11      US 

However, it merges both column LO and CON. I would only like to merge the column LO.

   Client Q    Sales   Date             LO          A      2    30      01/01/2014       12          A      3    24      02/01/2014       12          A      1    10      03/01/2014       12          B      4    10      01/01/2014       11          B      1    20      02/01/2014       11         B      3    30      03/01/2014       11       

Answer 1

You can do this by subsetting the data you pass into your merge:

merge(x = DF1, y = DF2[ , c("Client", "LO")], by = "Client", all.x=TRUE) 

Or you can simply delete the column after your current merge :)

Answer 2

I think it's a little simpler to use the dplyr functions select and left_join ; at least it's easier for me to understand. The join function from dplyr are made to mimic sql arguments.

 library(tidyverse)   DF2 <- DF2 %>%    select(client, LO)   joined_data <- left_join(DF1, DF2, by = "Client") 

You don't actually need to use the "by" argument in this case because the columns have the same name.