Left Join in R (dplyr) - Too many observations?

Question

I'm using dplyrs left join function in order to match two dataframes.

I have a panel data set A which consists of 4708 rows and 2 columns ID and Name:

ID Name
1  Option1
1  Option2
1  Option3
2  Option2
2  Option3
3  Option1
3  Option4

My dataset B consists of single definitions and categories for each name column (86 rows):

Name        Definition  Category
Option1     Def1         1
Option2     Def2         1
Option3     Def2         2
Option4     Def3         2

So in the end I need following data set C which links the columns of B to A:

ID Name      Definition   Category
1  Option1   Def1         1
1  Option2   Def2         1
1  Option3   Def2         2
2  Option2   Def2         1
2  Option3   Def2         2
3  Option1   Def1         1
3  Option4   Def3         2

I used a left_join command in dplyr to do this:

Data C <- left_join(A,B, by="name")

However, for some reason I got 5355 rows instead of the original 4708, so rows were some added. My understanding was that left_join simply assigns the definitions & categories of B to data set A.

Why do I get more rows ? Or are there any other ways to get the desired data frame C?

Answer 1

With left_join(A, B) new rows will be added wherever there are multiple rows in B for which the key columns (same-name columns by default) match the same, single row in A. For example:

library(dplyr)
df1 <- data.frame(col1 = LETTERS[1:4],
                  col2 = 1:4)
df2 <- data.frame(col1 = rep(LETTERS[1:2], 2),
                  col3 = 4:1)

left_join(df1, df2)  # has 6 rows rather than 4