Hi, James,
if I understand you correctly, maybe,
with(firstdf,
ifelse(Province %in% seconddf$Country,
Province,
Country)
)
does what you want?
Hth -- Gerrit
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gerrit.eich...@math.uni-giessen.de Justus-Liebig-University Giessen
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Am 10.08.2021 um 12:58 schrieb James Milks via R-help:
I have two columns in a larger data set that list countries in one column and,
in some cases, individual provinces within a country or oversea territories in
another. I have country population in a second data set that I’m planning to
use to calculate per capita rates in the first data set. My issue: I need to
match my two data sets. Here are some examples:
First data set:
Province <- c("Australian Capital Territory", "New South Wales", "Northern Territory", "Queensland", "South Australia", "Tasmania",
"Victoria", "Western Australia", "", "", "", "Faroe Islands", "Greenland")
Country <- c("Australia", "Australia", "Australia", "Australia", "Australia", "Australia", "Australia", "Australia",
"Austria", "Azerbaijan", "Denmark", "Denmark", "Denmark")
firstdf <- data.frame(Province, Country)
Second data set:
Country <- c("Australia", "Austria", "Azerbaijan", "Denmark", "Faroe Islands",
"Greenland")
seconddf <- data.frame(Country)
In this example, I need to aggregate sum Australia while keeping Faroe Islands
and Greenland separate from Denmark. What I’d like to do is create a column
that looks like this:
firstdf$nation <- c("Australia", "Australia", "Australia", "Australia", "Australia", "Australia", "Australia",
"Australia", "Austria", "Azerbaijan", "Denmark", “Faroe Islands", “Greenland”)
Is there a way to do this or am I stuck doing this by hand?
Thanks for any help on this vexing issue.
Jim Milks
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