Let’s see the dimension of each output when we specify all.x= TRUE and when we don’t. In our case, the producer Lucas will not be join to the merge because it is missing from one dataset. If we set all.x= FALSE, R will join only the matching values in both data set.
#Data merge data movie
We can do that by setting all.x= TRUE.įor instance, we can add a new producer, Lucas, in the producer data frame without the movie references in movies data frame. These rows will have NA in those columns that are usually filled with values from y. With partial merging, it is possible to keep the rows with no matching rows in the other data frame.
In the full matching, the dataframe returns only rows found in both x and y data frame. It is not surprising that two dataframes do not have the same common key variables. This shows that merge operation is performed even if the column names are different. # 6 Spielberg US Catch Me If You Can # Check if data are identical M2 <- merge(producers, movies, by.x = "surname", by.y = "name") # Change name of ` movies ` dataframeĬolnames(movies) <- 'name' We use the function identical(x1, x2) to check if both dataframes are identical.
We change surname to name in the movies data frame. Let’s merge data frames when the common key variables have different names. M1 <- merge(producers, movies, by.x = "surname") Surname = c("Spielberg","Scorsese","Hitchcock","Tarantino","Polanski"), We add stringsAsFactors=FALSE in the data frame because we don’t want R to convert string as factor, we want the variable to be treated as character. We can merge both data and check if the dimensionality is 7×3.
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