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 …