How can I do this standard excel operation in R? - r

Question

I want to identify who are default and voluntary members in an Insurance database. Default members are ones with a certain number of units depending on their age. Voluntary members are any members with more units than default members at that age.
I want to create a column in R that says either "Default" or "Voluntary"
I have a table of the number of units a default member has. For example:
Age Units
18 2
19 2
20 2
21 2
22 2
23 2
24 2
25 3
26 3
27 3
28 3
29 3
30 3
31 4
32 4
33 4
34 4
35 4
36 4
37 4
38 4
39 4
40 4
41 4
42 4
43 4
44 4
45 4
46 4
47 4
48 4
49 4
50 3
51 3
52 3
53 3
54 3
55 3
56 3
57 3
58 3
59 3
60 2
61 2
62 2
63 2
64 2
65 1
66 1
67 1
68 1
69 1
I would usually do this in excel by vlookup-ing the member's number of units and if it equals the default number of units from above table I would say they are default and if not non default.
This is how I would achieve in excel
if( MembersUnits = vlookup(memberage,defaultunitstable,2,0),"Default", "Voluntary")
I expect out put to be "Default" or "Voluntary"

Answer 1

Using the data you supplied as a lookup table, I created data of person age and the number of units they have, joined the threshold values from lookup and compared the values with ifelse:
library(dplyr)
lookup <- structure(list(Age = 18:69,
Units = c(2L, 2L, 2L, 2L, 2L, 2L,
2L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L)),
row.names = c(NA,
-52L), class = c("tbl_df", "tbl", "data.frame"))
dat <- tibble(Age = c(50, 50, 49, 32, 18), Units = c(3, 5, 5, 4, 3))
left_join(dat, rename(lookup, "Threshold" = "Units"), by = "Age") %>%
mutate(member = ifelse(Units == Threshold, "Default", "Voluntary"))
# A tibble: 5 x 4
Age Units Threshold member
<dbl> <dbl> <int> <chr>
1 50 3 3 Default
2 50 5 3 Voluntary
3 49 5 4 Voluntary
4 32 4 4 Default
5 18 3 2 Voluntary

Answer 2

if (!require("prodlim")) {
install.packages("prodlim")
require("prodlim")
} # ensure installation and loading of package "prodlim"
ifelse(is.na(row.match(as.data.frame(dat), as.data.frame(lookup))),
"Voluntary",
"Default")
## [1] "Default" "Voluntary" "Voluntary" "Default" "Default" "Default"
## the function
## prodlim::row.match(as.data.frame(dat), as.data.frame(lookup))
## returns for each row in dat,
## the matching row number in lookup or
## NA if there is no match
##
## This resulting vector one can use to translate any non-NA to "Default" and
## any NA to "Voluntary" using the vectorized `ifelse`
Ah I used as example data following #Paul:
require(dplyr)
dat <- tibble(Age = c(50, 50, 49, 26, 32, 18), Units = c(3, 5, 5, 3, 4, 2))
lookup <- structure(list(Age = 18:69,
Units = c(2L, 2L, 2L, 2L, 2L, 2L,
2L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L)),
row.names = c(NA,
-52L), class = c("tbl_df", "tbl", "data.frame"))