Loop Output Stored as List - r

Question

I have wide supervisory data where a single observation consists of a level 1 employee and their department all the way down to level 8. I use a loop with other commands to produce a list all employees and the departments beneath them in long format so that I can see what departments employees are responsible for at all levels. There may be a more elegant way to do this than a loop, but it works fine. Sample data (through level 3 for succinctness):
data <- tibble(LV1_Employee_Name = "Chuck", LV1_Employee_Nbr = "1", LV1_Department = "Tha Boss", LV1_Department_Nbr = "90",
LV2_Employee_Name = c("Alex", "Alex", "Paul", "Paul", "Jennifer", "Jennifer"), LV2_Employee_Nbr = c("2", "2", "3", "3", "4", "4"), LV2_Department = c("Leadership", "Leadership", "Finance", "Finance", "Philanthropy", "Philanthropy"), LV2_Department_Nbr = c("91", "91", "92", "92", "93", "93"),
LV3_Employee_Name = c("Dan", "Wendy", "Sarah", "Monique", "Miguel", "Brandon"), LV3_Employee_Nbr = c("2", "2", "3", "3", "4", "4"), LV3_Department = c("Analytics", "Pop Health", "Acounting", "Investments", "Yacht Aquisitions", "Golf Junkets"), LV3_Department_Nbr = c("94", "95", "96", "97", "98", "99"))
The loop below first produces six tibbles named level1_1, level1_2, level1_3, level2_2, level2_3, level3_3. Each tibble contains an employee name, number, and the department at the same department level or below. The code then lists and binds the rows of these tibbles with ls() and bind_rows(), then applies the distinct() command, and I've got what I need.
first_department <- 1
data_colnames <- c("Employee", "Employee_Id", "Department", "Department_Number")
for(i in 1:3){
for(k in first_department:3){
assign(paste0("level", i, "_", k), setNames(distinct(as_tibble(c(data[ ,paste0("LV", i, "_", "Employee_Name")], data[ ,paste0("LV", i, "_", "Employee_Nbr")],
data[ ,paste0("LV", k, "_", "Department")], data[ ,paste0("LV", k, "_", "Department_Nbr")]))),
data_colnames))
}
first_department = first_department + 1
}
employees_departments <- distinct(bind_rows(mget(ls(pattern = "^level")))) %>%
filter(is.na(Department) == FALSE)
rm(list = ls(pattern = "^level"))
What I'd like to do is, rather than produce an initial output of six tibbles, have the loop itself output the list. This will save me from having a huge list of tibbles in the output which, I'm told, is not very "R-like".

Answer 1

Here is a revised version that stores the results in a list within your loop. This will include an index idx incremented each time through the loop. Afterwards, you can use bind_rows on this list to get a complete result.
library(tidyverse)
idx <- 1
first_department <- 1
data_colnames <- c("Employee", "Employee_Id", "Department", "Department_Number")
data_lst <- list()
for(i in 1:3){
for(k in first_department:3){
data_lst[[idx]] <- setNames(
distinct(as_tibble(
c(data[ ,paste0("LV", i, "_", "Employee_Name")],
data[ ,paste0("LV", i, "_", "Employee_Nbr")],
data[ ,paste0("LV", k, "_", "Department")],
data[ ,paste0("LV", k, "_", "Department_Nbr")]))),
data_colnames)
idx <- idx + 1
}
first_department = first_department + 1
}
distinct(bind_rows(data_lst)) %>%
filter(!is.na(Department))
Output
Employee Employee_Id Department Department_Number
<chr> <chr> <chr> <chr>
1 Chuck 1 Tha Boss 90
2 Chuck 1 Leadership 91
3 Chuck 1 Finance 92
4 Chuck 1 Philanthropy 93
5 Chuck 1 Analytics 94
6 Chuck 1 Pop Health 95
7 Chuck 1 Acounting 96
8 Chuck 1 Investments 97
9 Chuck 1 Yacht Aquisitions 98
10 Chuck 1 Golf Junkets 99
11 Alex 2 Leadership 91
12 Paul 3 Finance 92
13 Jennifer 4 Philanthropy 93
14 Alex 2 Analytics 94
15 Alex 2 Pop Health 95
16 Paul 3 Acounting 96
17 Paul 3 Investments 97
18 Jennifer 4 Yacht Aquisitions 98
19 Jennifer 4 Golf Junkets 99
20 Dan 2 Analytics 94
21 Wendy 2 Pop Health 95
22 Sarah 3 Acounting 96
23 Monique 3 Investments 97
24 Miguel 4 Yacht Aquisitions 98
25 Brandon 4 Golf Junkets 99