Cross Join in dplyr in R

Question

library(dplyr)
cust_time<-data.frame(cid=c("c1","c2","c3","c4","c5"),ts=c(2,7,11,13,17))
#I want to do a cross join on self, preferable in dplyr else base package is Ok
#But w/o renaming header names
#Currently I have to create a duplicate cust_time to do this.
cust_time.1<-rename(cust_time,cid1=cid,ts1=ts)
merge(cust_time,cust_time.1,by=NULL)

#Later I will want to do cross join within the grouped region
cust_time <-mutate(cust_time,ts.bucket=ts%/%10)
#If using duplicate tables, not sure, how to do the below
#group_by(cust_time,ts.bucket) %>%
#do cross join within this bucket

Basically, I want to do a cross self-join on a table but since I cant a dplyr solution, I used the base package. But it requires me to rename all the columns. However, I later want to be able do a cross-join at a grouped level and this is where I am stumbling.
Any help appreciated.

Answer 1

As of dplyr version 1.0, you can do a cross join by specifying by = character():

cust_time %>% full_join(cust_time, by = character())

Answer 2

You just need a dummy column to join on:

cust_time$k <- 1
cust_time %>% 
  inner_join(cust_time, by='k') %>%
  select(-k)

Or if you don't want to modify your original dataframe:

cust_time %>%
  mutate(k = 1) %>%
  replicate(2, ., simplify=FALSE) %>%
  Reduce(function(a, b) inner_join(a, b, by='k'), .) %>%
  select(-k)