create data frame from nested entries - r

Question

I have a data frame test like this:
dput(test)
structure(list(X = 1L, entityId = structure(1L, .Label = "HOST-123", class = "factor"),
displayName = structure(1L, .Label = "server1", class = "factor"),
discoveredName = structure(1L, .Label = "server1", class = "factor"),
firstSeenTimestamp = 1593860000000, lastSeenTimestamp = 1603210000000,
tags = structure(1L, .Label = "c(\"CONTEXTLESS\", \"CONTEXTLESS\", \"CONTEXTLESS\", \"CONTEXTLESS\", \"CONTEXTLESS\", \"CONTEXTLESS\", \"CONTEXTLESS\", \"CONTEXTLESS\"), c(\"app1\", \"client\", \"org\", \"app1\", \"DATA_CENTER\", \"PURPOSE\", \"REGION\", \"Test\"), c(NA, \"NONE\", \"Host:Environment:test123\", \"111\", \"222\", \"GENERAL\", \"444\", \"555\")", class = "factor")), .Names = c("X",
"entityId", "displayName", "discoveredName", "firstSeenTimestamp",
"lastSeenTimestamp", "tags"), class = "data.frame", row.names = c(NA,
-1L))
There is a column called tags which should become a dataframe. I need to get rid of the first row in tags (which keep saying CONTEXTLESS, expand the second column in tags(make them columns. Lastly I need to insert the 3rd column values in tags under each expanded columns.
For example in needs to look like this:
structure(list(entityId = structure(1L, .Label = "HOST-123", class = "factor"),
displayName = structure(1L, .Label = "server1", class = "factor"),
discoveredName = structure(1L, .Label = "server1", class = "factor"),
firstSeenTimestamp = 1593860000000, lastSeenTimestamp = 1603210000000,
app1 = NA, client = structure(1L, .Label = "None", class = "factor"),
org = structure(1L, .Label = "Host:Environment:test123", class = "factor"),
app1.1 = 111L, data_center = 222L, purppose = structure(1L, .Label = "general", class = "factor"),
region = 444L, test = 555L), .Names = c("entityId", "displayName",
"discoveredName", "firstSeenTimestamp", "lastSeenTimestamp",
"app1", "client", "org", "app1.1", "data_center", "purppose",
"region", "test"), class = "data.frame", row.names = c(NA, -1L
))
I need to remove the 1st vector that keeps saying "contextless", add the second vector the columns. Each 2nd vector value should be a column name. Last vector should be values of the newly added columns.

Answer 1

If you are willing to drop the first "row" of garbage and then do a ittle cleanup of the parse-side-effects, then this might be a good place to start:
read.table(text=gsub("\\),", ")\n", test$tags[1]), sep=",", skip=1, #drops line
header=TRUE)
c.app1 client org app1 DATA_CENTER PURPOSE REGION Test.
1 c(NA NONE Host:Environment:test123 111 222 GENERAL 444 555)
The read.table function uses the scan function which doesn't know that "c(" and ")" are meaningful. The other alternative might be to try eval(parse(text= .)) (which would know that they are enclosing vectors) on the the second and third lines, but I couldn't see a clean way to do that. I initially tried to separate the lines using strsplit, but that caused me to loose the parens.
Here's a stab at some cleanup via that addition of some more gsub operations:
read.table(text=gsub("c\\(|\\)","", # gets rid of enclosing "c(" and ")"
gsub("\\),", "\n", # inserts line breaks
test$tags[1])),
sep=",", #lets commas be parsed
skip=1, #drops line
header=TRUE) # converts to colnames
app1 client org app1.1 DATA_CENTER PURPOSE REGION Test
1 NA NONE Host:Environment:test123 111 222 GENERAL 444 555
The reason for the added ".1" in the second instance of app1 is that R colnames in dataframes need to be unique unless you override that with check.names=FALSE

Answer 2

Here is a tidyverse approach
library(dplyr)
library(tidyr)
str2dataframe <- function(txt, keep = "all") {
# If you can confirm that all vectors are of the same length, then we can make them into columns of a data.frame
out <- eval(parse(text = paste0("data.frame(", as.character(txt),")")))
# rename columns as X1, X2, ...
nms <- make.names(seq_along(out), unique = TRUE)
if (keep == "all")
keep <- nms
`names<-`(out, nms)[, keep]
}
df %>%
mutate(
tags = lapply(tags, str2dataframe, -1L),
tags = lapply(tags, function(d) within(d, X2 <- make.unique(X2)))
) %>%
unnest(tags) %>%
pivot_wider(names_from = "X2", values_from = "X3")
df looks like this
> df
X entityId displayName discoveredName firstSeenTimestamp lastSeenTimestamp
1 1 HOST-123 server1 server1 1.59386e+12 1.60321e+12
tags
1 c("CONTEXTLESS", "CONTEXTLESS", "CONTEXTLESS", "CONTEXTLESS", "CONTEXTLESS", "CONTEXTLESS", "CONTEXTLESS", "CONTEXTLESS"), c("app1", "client", "org", "app1", "DATA_CENTER", "PURPOSE", "REGION", "Test"), c(NA, "NONE", "Host:Environment:test123", "111", "222", "GENERAL", "444", "555")
Output looks like this
# A tibble: 1 x 14
X entityId displayName discoveredName firstSeenTimestamp lastSeenTimestamp app1 client org app1.1 DATA_CENTER PURPOSE REGION Test
<int> <fct> <fct> <fct> <dbl> <dbl> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
1 1 HOST-123 server1 server1 1593860000000 1603210000000 NA NONE Host:Environment:test123 111 222 GENERAL 444 555