Saving the output of a str_which loop in R - r

Question

I work with a sheet of data that lists a variety of scientific publications. Rows are publications,
columns are a variety of metrics describing each publication (author name and position, Pubmed IDs, Date etc...)
I want to filter for publications for each author and extract parts of them. The caveat is the format:
all author names (5-80 per cell) are lumped together in one cell for each row.
I managed to solve this with the use of str_which, saving the coordinates for each author and later extract. This works only for manual use. When I try to automate this process using a loop to draw on a list of authors I fail to save the output.
I am at a bit of a loss on how to store the results without overwriting previous ones.
sampleDat <-
data.frame(var1 = c("Doe J, Maxwell M, Kim HE", "Cronauer R, Carst W, Theobald U", "Theobald U, Hey B, Joff S"),
var2 = c(1:3),
var3 = c("2016-01", "2016-03", "2017-05"))
list of names that I want the coordinates for
namesOfInterest <-
list(c("Doe J", "Theobald U"))
the manual extraction, requiring me to type the exact name and output object
Doe <- str_which(sampleDat$var1, "Doe J")
Theobald <- str_which(sampleDat$var1, "Theobald U")
one of many attempts that does not replicate the manual version.
results <- c()
for (i in namesOfInterest) {
results[i] <- str_which(sampleDat$var1, i)
}

Answer 1

The for loop is set up incorrectly (it needs to be something like for(i in 1:n){do something}). Also, even if you fix that, you'll get an error related to the fact that str_which returns a vector of varying length, indicating the position of each of the matches it makes (and it can make multiple matches). Thus, indexing a vector in a loop won't work here because whenever a author has multiple matches, more than one entry will be saved to a single element, throwing an error.
Solve this by working with lists, because lists can hold vectors of arbitrary length. Index the list with double bracket notation: [[.
library(stringr)
sampleDat <-
data.frame(var1 = c("Doe J, Maxwell M, Kim HE", "Cronauer R, Carst W, Theobald U", "Theobald U, Hey B, Joff S"),
var2 = c(1:3),
var3 = c("2016-01", "2016-03", "2017-05"))
# no need for list here. a simple vector will do
namesOfInterest <- c("Doe J", "Theobald U")
# initalize list
results <- vector("list", length = length(namesOfInterest))
# loop over list, saving output of `str_which` in each list element.
# seq_along(x) is similar to 1:length(x)
for (i in seq_along(namesOfInterest)) {
results[[i]] <- str_which(sampleDat$var1, namesOfInterest[i])
}
which returns:
> results
[[1]]
[1] 1
[[2]]
[1] 2 3
The way to understand the output above is that the ith element of the list, results[[i]] contains the output of str_which(sampleDat$var1, namesOfInterest[i]), where namesOfInterest[i] is always exactly one author. However, the length of results[[i]] can be longer than one:
> sapply(results, length)
[1] 1 2
indicating that a single author can be mentioned multiple times. In the example above, sapply counts the length of each vector along the list results, showing that namesOfInterest[1] has one paper, and namesOfInterest[2] has 2. `

Answer 2

Here is another approach for you. If you want to know which scholar is in which publication, you can do the following as well. First, assign unique IDs to publications. Then, split authors and create a long-format data frame. Define groups by authors and aggregate publication ID (pub_id) as string (character). If you need to extract some authors, you can use this data frame (foo) and subset rows.
library(tidyverse)
mutate(sampleDat, pub_id = 1:n()) %>%
separate_rows(var1, sep = ",\\s") %>%
group_by(var1) %>%
summarize(pub_id = toString(pub_id)) -> foo
var1 pub_id
<chr> <chr>
1 Carst W 2
2 Cronauer R 2
3 Doe J 1
4 Hey B 3
5 Joff S 3
6 Kim HE 1
7 Maxwell M 1
8 Theobald U 2, 3
filter(foo, var1 %in% c("Doe J", "Theobald U"))
var1 pub_id
<chr> <chr>
1 Doe J 1
2 Theobald U 2, 3
If you want to have index as numeric, you can twist the idea above and do the following. You can subset rows with targeted names with filter().
mutate(sampleDat, pub_id = 1:n()) %>%
separate_rows(var1, sep = ",\\s") %>%
group_by(var1) %>%
summarize(pub_id = list(pub_id)) %>%
unnest(pub_id)
var1 pub_id
<chr> <int>
1 Carst W 2
2 Cronauer R 2
3 Doe J 1
4 Hey B 3
5 Joff S 3
6 Kim HE 1
7 Maxwell M 1
8 Theobald U 2
9 Theobald U 3