Replace Value & Shift Data Frame If Certain Condition Met - regex

Question

I've scraped data from a source online to create a data frame (df1) with n rows of information pertaining to individuals. It comes in as a single string, and I split the words apart into appropriate columns.
90% of the information is correctly formatted to the proper number of columns in a data frame (6) - however, once in a while there is a row of data with an extra word that is located in the spot of the 4th word from the start of the string. Those lines now have 7 columns and are off-set from everything else in the data frame.
Here is an example:
Num Last-Name First-Name Cat. DOB Location
11 Jackson, Adam L 1982-06-15 USA
2 Pearl, Sam R 1986-11-04 UK
5 Livingston, Steph LL 1983-12-12 USA
7 Thornton, Mark LR 1982-03-26 USA
10 Silver, John RED LL 1983-09-14 USA
df1 = c(" 11 Jackson, Adam L 1982-06-15 USA",
"2 Pearl, Sam R 1986-11-04 UK",
"5 Livingston, Steph LL 1983-12-12 USA",
"7 Thornton, Mark LR 1982-03-26 USA",
"10 Silver, John RED LL 1983-09-14 USA")
You can see item #10 has an extra input added, the color "RED" is inserted into the middle of the string.
I started to run code that used stringr to evaluate how many characters were present in the 4th word, and if it was 3 or greater (every value that will be in the Cat. column is is 1-2 characters), I created a new column at the end of the data frame, assigned the value to it, and if there was no value (i.e. it evaluates to FALSE), input NA. I'm sure I could likely create a massive nested ifelse statement in a dplyr mutate (my personal comfort zone), but I figure there must be a more efficient way to achieve my desired result:
Num Last-Name First-Name Cat. DOB Location Color
11 Jackson, Adam L 1982-06-15 USA NA
2 Pearl, Sam R 1986-11-04 UK NA
5 Livingston, Steph LL 1983-12-12 USA NA
7 Thornton, Mark LR 1982-03-26 USA NA
10 Silver, John LL 1983-09-14 USA RED
I want to find the instances where the 4th word from the start of the string is 3 characters or longer, assign that word or value to a new column at the end of the data frame, and shift the corresponding values in the row to the left to properly align with the others rows of data.

Answer 1

here's a simpler way:
input <- gsub("(.*, \\w+) ((?:\\w){3,})(.*)", "\\1 \\3 \\2", input, TRUE)
input <- gsub("([0-9]\\s\\w+)\\n", "\\1 NA\n", input, TRUE)
the first gsub transposes colors to the end of the string. the second gsub makes use of the fact that unchanged lines will now end with a date and country-code (not a country-code and a color), and simply adds an "NA" to them.
IDEone demo

Answer 2

We could use gsub to remove the extra substrings
v1 <- gsub("([^,]+),(\\s+[[:alpha:]]+)\\s*\\S*(\\s+[[:alpha:]]+\\s+\\d{4}-\\d{2}-\\d{2}.*)",
"\\1\\2\\3", trimws(df1))
d1 <- read.table(text=v1, sep="", header=FALSE, stringsAsFactors=FALSE,
col.names = c("Num", "LastName", "FirstName", "Cat", "DOB", "Location"))
d1$Color <- trimws(gsub("^[^,]+,\\s+[[:alpha:]]+|[[:alpha:]]+\\s+\\d{4}-\\d{2}-\\d{2}\\s+\\S+$",
"", trimws(df1)))
d1
# Num LastName FirstName Cat DOB Location Color
#1 11 Jackson Adam L 1982-06-15 USA
#2 2 Pearl Sam R 1986-11-04 UK
#3 5 Livingston Steph LL 1983-12-12 USA
#4 7 Thornton Mark LR 1982-03-26 USA
#5 10 Silver John LL 1983-09-14 USA RED

Answer 3

Using strsplit instead of regex:
# split strings in df1 on commas and spaces not preceded by the start of the line
s <- strsplit(df1, '(?<!^)[, ]+', perl = T)
# iterate over s, transpose the result and make it a data.frame
df2 <- data.frame(t(sapply(s, function(x){
# if number of items in row is 6, insert NA, else rearrange
if (length(x) == 6) {c(x, NA)} else {x[c(1:3, 5:7, 4)]}
})))
# add names
names(df2) <- c("Num", "Last-Name", "First-Name", "Cat.", "DOB", "Location", "Color")
df2
# Num Last-Name First-Name Cat. DOB Location Color
# 1 11 Jackson Adam L 1982-06-15 USA <NA>
# 2 2 Pearl Sam R 1986-11-04 UK <NA>
# 3 5 Livingston Steph LL 1983-12-12 USA <NA>
# 4 7 Thornton Mark LR 1982-03-26 USA <NA>
# 5 10 Silver John LL 1983-09-14 USA RED