vlookup not working? Weird counts?

General
1

Sorry if my question is silly but I get ridiculous results adding info from the "info" df to my "source" df.
All I need is equivalent of vlookup so finding and adding OrgCode and OrgName based on OrgID.

source <- data.frame(
  stringsAsFactors = FALSE,
  URN = c("aaa","bbb","ccc",
          "ddd","eee","fff","ggg"),
  OrgID = c(32047,32047,32047,
            32430,32430,336954,12454),
  QF16 = c("Yes","No","No","Yes",
           "Yes","No","No"),
  QF4 = c(100, 100, 100, 100, 100, 0, 50)
)

info <- data.frame(
  stringsAsFactors = FALSE,
  OrgID = c(32047,
            32322,31818,32430),
  OrgCode = c("001702E",
              "001192Q",
              "000985Q","001673B"),
  OrgName = c("Name1",
              "Name2","Name3",
              "Name4")
)

result <- left_join(source, info, by="OrgID")

Everything looks fine on the example above but when I apply that to my real two databases I have following counts
source = 98309 obs. of 67 variables
info = 49104 obs. of 16 variables
result = 5878665 obs. of 82 variables

What am I doing wrong? When do you think this may happen?

2

Hi @Slavek , it seems that the likely issue is that there are duplicate OrgID in your info table. To confirm you could run: dplry::count(info, OrgID, sort = TRUE). If the first rows are all 1's, then I'm wrong, but if you have any higher than that, then it confirms duplicates, which hence produces the additional rows in your merge.

3

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