How can I add a condition in a function using ddply

Question

I am creating a new variable mydata_weighted.equity for my dataset using the following code:

mydata_weighted.equity <- ddply(mydata, .(TrackerID), function(x)
    data.frame(weighted.equity = weighted.mean(x$Equity_dummy,
                                      x$Financiers_Unit_Share_Dollar)))

This works.

Now, I want to do the same again, but include only those observations for which a special condition is met. Namely, that the value for the variable signatory is >0.

I bet that there is a way like

mydata_weighted.equity <- ddply(mydata, .(TrackerID), function(x)
  data.frame(weighted.equity = weighted.mean(x$Equity_dummy,
                                             x$Financiers_Unit_Share_Dollar), if signatory > 0))

but I just don't figure out how to code it.

Desperatly looking for help as the deadline for my project is getting closer...

Answer 1

Try this:

library(tidyverse)
mydata_weighted.equity <- ddply(mydata, .(TrackerID), function(x){ 
x %>% filter(signatory>0) %>% summarise(weighted.equity = weighted.mean(Equity_dummy, Financiers_Unit_Share_Dollar)) %>% data.frame()

It will filter the data then calculate what you want!