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I am a beginner using R, and I am wanting to create a dataframe that stores a range of dates to their respective classified time period.

paleo.periods <- c("Paleoindian","Early Paleoindian", "Middle Paleoindian", "Late Paleoindian", "Archaic","Early Archaic", "Middle Archaic","Late Archaic","Woodland","Early Woodland","Middle Woodland","Late Woodland","Late Prehistoric")

paleo.dates <- c(c(13500,8000), c(13500,10050) ,c(10050,9015), c(9015,8000), c(8000,2500), c(8000,5500), c(5500,3500), c(3500,2500), c(2500,1150), c(2500,2000), c(2000,1500), c(1500,1150), c(1150,500))

I would like for the arrangement to come out where I can refer to a given time period, ex: "Late Woodland", and get the associated vector of it's beginning and end timeframes, ex: (1500,1150)

I tried simply doing this by

paleo.seg <- data.frame(paleo.periods,paleo.dates)

however, this creates 3 variables: a list of the periods, a list of the vectors, and paleo.dates. I am not sure why it is creating 3 variables, as I'd like it to be only 2: paleo.periods and paleo.dates. I would also like to refer to them as paleo.seg$paleo.periods which will return the list of periods (and later use this to somehow refer to the periods individually), same with the dates.

Essentially I would like my dataframe to look a bit like this:

paleoperiods paleodates 
"Late Woodland" 1500,1100

Therefore I could look specifically for the string "Late Woodland" and find the vector dates. I tried doing this on my current data.frame, and
"Woodland" %in% paleo.seg returns false. So I feel like I am misunderstanding how to build a proper dataframe, as well as being able to match one categorical variable to two dates.

There are a few ways that you could go about this depending on your reasoning about what you want to do with your dataframe. My recommendation would actually be to split the dates column into two separate date columns(start and end I believe, from your description). This way you could calculate or use rules based on the dates. I've found this useful when looking at data, as it gives you the ability to filter based on two different aspects of the date. If you would like them to be in the same column, you could make the dates a character in order to have them in the same column. However, this approach does have drawbacks in terms of using it for exploratory data analysis. An example of this would be:

paleo.dates <- c("13500,8000","13500,10050","10050,9015","9015,8000", ...)

This would allow you to look up Late Woodland and get "1500,1100", but you wouldn't be able to search for periods occurring after 1500 if that type of analysis is something you would be doing at a later point.