Duplicating values in a data frame conditionally - r

Question

I have a dataframe that in an entirely simplistic representation looks like this:
structure(list(Plant = c("rose", "rose", "rose", "rose", "rose",
"rose", "rose", "rose", "cactus", "cactus", "cactus", "cactus"
), Area = c("North", "North", "North", "North", "South", "South",
"South", "South", "South", "South", "South", "South"), dups = c(4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 2L, 2L, 2L, 2L)), class = "data.frame", row.names = c(NA,
-12L))
For any row of plant, I want to replace it with specific possible combinations of plant and area that are within another data frame. They are not ALL possible combinations, but just the ones that truly exist.
The possible combinations of the variables look like this:
structure(list(nam = c("rose", "rose", "rose", "rose", "cactus",
"cactus"), area = c("North", "South", "East", "West", "South",
"Northwest")), class = "data.frame", row.names = c(NA, -6L))
The final dataset should look like:
structure(list(Plant2 = c("rose", "rose", "rose", "rose", "rose",
"rose", "rose", "rose", "cactus", "cactus", "cactus", "cactus"
), Area2 = c("North", "South", "East", "West", "North", "South",
"East", "West", "South", "Northwest", "South", "Northwest")), class = "data.frame", row.names = c(NA,
-12L))
This is how I started. I created a variable for how many combinations were potentially possible and added them to the datframe with a join. And then I got super stuck because try as I might, I can't change the Area variables properly. I thought I could basically paste all the combinations of the variables with the same dups value, but I can't call to the other dataframe from dplyr. This is a very simplistic version of the data, there are many other combinations and so it's not really want to do by subsetting the data, etc...
dups<-combos %>% group_by(nam) %>% mutate(dups=n())
colnames(dups)<-c("Plant","Area","dups")
df<-left_join(df,dups)
df<-df %>% uncount(dups, .remove=FALSE)

Answer 1

The information you have provided is not enough to produce a final dataframe like that since each combination of Plant and dups in df can be mapped to multiple values in combos. For instance, each "rose" and "4" could be matched against the first four rows in combos. However, it seems that you simply want Area2 to repeat itself until the values fill up all possible entries for each group of Plant and dups. If so, you can try
library(dplyr)
combos <- combos %>% group_by(nam) %>% mutate(dups = n())
df %>%
group_by(Plant, dups) %>%
mutate(Area2 = rep(
combos$area[combos$nam == Plant[[1L]] & combos$dups == dups[[1L]]],
length.out = n()
))
Output
# A tibble: 12 x 4
# Groups: Plant, dups [2]
Plant Area dups Area2
<chr> <chr> <int> <chr>
1 rose North 4 North
2 rose North 4 South
3 rose North 4 East
4 rose North 4 West
5 rose South 4 North
6 rose South 4 South
7 rose South 4 East
8 rose South 4 West
9 cactus South 2 South
10 cactus South 2 Northwest
11 cactus South 2 South
12 cactus South 2 Northwest

Answer 2

You can use expand.grid to create a dataframe with all possible conditions
expand.grid(name = unique(df$name), area = unique(df$area))
Plant Area
1 rose North
2 cactus North
3 rose South
4 cactus South
5 rose East
6 cactus East
7 rose West
8 cactus West
9 rose Northwest
10 cactus Northwest

Answer 3

This snippet should do what you want, if I've understood correctly. Here, d1 and d2 are your first and second data frames. I don't think that computing dups as you have is necessary for this task, but maybe I've misunderstood your intention.
library("dplyr")
l <- split(d2$area, d2$nam)
d1 %>%
group_by(Plant) %>%
mutate(Area = rep_len(l[[Plant[1L]]], n())) %>%
ungroup() %>%
select(-dups)
# A tibble: 12 × 2
Plant Area
<chr> <chr>
1 rose North
2 rose South
3 rose East
4 rose West
5 rose North
6 rose South
7 rose East
8 rose West
9 cactus South
10 cactus Northwest
11 cactus South
12 cactus Northwest