I have a dataframe titled
FilteredData with many columns. Specifically, there are two columns I am interested in:
I want to group all
Sale number entries by dates.
Date is a date-type field, and
Sale number is a character-type field. If I'm not mistaken, I think these types are the reason why other Q&As on S.O. haven't been much help to me.
How can I do this?
I've tried the following:
aggregate(FilteredData$`Sale number`, by FilteredData$Date, FUN = count) group_by(FilteredData$`Sale number`, FilteredData$Date)
Neither worked, and neither did the solution found here when I tried it.
I tried the following:
library(sqldf) Freq = sqldf('SELECT Date, COUNT('Sale Number') FROM FilteredData GROUP BY Date')
and it surprisingly worked. However, is there a way to obtain this result without having to use SQL syntax, i.e. something "purely" in R?
Your question is a little unclear... So you want to group by date and then count the number of non-duplicate entries within a date?
dplyr can do this:
FilteredData %>% # take filtered data group_by(FundedDate) %>% # group by the date subset(!duplicated('Sale number')) %>% # remove rows that are duplicated sales numbers count('Sale number') # count sales numbers