Hi Bill. Sorry to be so obtuse with the example data, I was trying
(too hard) not to share any actual values so I just created randomized
values for my example; of course I should have specified that the
random values would not provide the expected problem pattern. I should
have just used simple dummy codes as Bill Dunlap did.
So per Bill's example data for Data1, the expected (hoped for) output
should be:
Vendor Account Num_Vendors_Sharing_Bank_Acct
1 V1 A1 0
2 V2 A2 3
3 V3 A2 3
4 V4 A2 3
Where the new calculated variable is Num_Vendors_Sharing_Bank_Acct.
The value is 3 for V2, V3 and V4 because they each share bank account
A2.
Likewise, in the Data2 frame, the same logic applies:
Vendor Account Num_Vendors_Sharing_Bank_Acct
1 V1 A1 0
2 V2 A2 3
3 V3 A2 3
4 V1 A2 3
5 V4 A3 0
6 V2 A4 0
Thanks!
Quoting Bill Dunlap <williamwdun...@gmail.com>:
What should the result be for
Data1 <- data.frame(Vendor=c("V1","V2","V3","V4"),
Account=c("A1","A2","A2","A2"))
?
Must each vendor have only one account? If not, what should the result be
for
Data2 <- data.frame(Vendor=c("V1","V2","V3","V1","V4","V2"),
Account=c("A1","A2","A2","A2","A3","A4"))
?
-Bill
On Tue, Nov 17, 2020 at 1:20 PM Tom Woolman <twool...@ontargettek.com>
wrote:
Hi everyone. I have a dataframe that is a collection of Vendor IDs
plus a bank account number for each vendor. I'm trying to find a way
to count the number of duplicate bank accounts that occur in more than
one unique Vendor_ID, and then assign the count value for each row in
the dataframe in a new variable.
I can do a count of bank accounts that occur within the same vendor
using dplyr and group_by and count, but I can't figure out a way to
count duplicates among multiple Vendor_IDs.
Dataframe example code:
#Create a sample data frame:
set.seed(1)
Data <- data.frame(Vendor_ID = sample(1:10000), Bank_Account_ID =
sample(1:10000))
Thanks in advance for any help.
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