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

It's hard to know without seeing your original data, but if data frame B does not contain unique values on the join columns, you will get repeated rows from data frame A whenever this happens. You could try:

data_frame_b %>% count(join_col_1, join_col_2)

Which will let you know if there are non-unique combinations of the two variables.

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

More rows may also appear if you have NA values in both A's and B's names on which you join. So make sure you exclude those.