This is going to be a really short blog post. I recently found that if I join two tables with one of the tables having duplicated rows, the final joined table also contains the duplicated rows. It could be the expected behavior for others but I want to make a note here for myself.

library(tidyverse) df1<- tibble(key = c("A", "B", "C", "D", "E"), value = 1:5) df1
## # A tibble: 5 x 2

key value

<chr> <int>

1 A 1

2 B 2

3 C 3

4 D 4

5 E 5

dataframe 2 has two …