add dplyr operations

[ocramz]

• mutate() adds new variables that are functions of existing variables
• select() picks variables based on their names.
  • see the text, int etc. lenses
• filter() picks cases based on their values.
• summarise() reduces multiple values down to a single summary.
  - [ ] arrange() changes the ordering of the rows. not needed

[ocramz]

filter() -> filter
summarise() -> dataframes are Foldable

[ocramz]

mutate() is interesting; in the current implementation, we are lacking a typesafe way to re-insert values into a row.

[ocramz]

@adamConnerSax shows this workaround for a row function :

let add_nwnh_dem r = K.knitMaybe "Missing column when computing nwnh_dem" $ do
        vocT <- r ^? Heidi.double (BR.heidiColKey "VOC Total")
        wnhT <- r ^? Heidi.double (BR.heidiColKey "WNH Total")
        voc <- r ^? Heidi.int (BR.heidiColKey "NWNH VEP")
        wnh <- r ^? Heidi.int (BR.heidiColKey "WNH VEP")
        vocSST <- r ^? Heidi.double (BR.heidiColKey "State-Specific")
        let turnout = ((vocT * realToFrac voc) + (wnhT * realToFrac wnh))/realToFrac (voc + wnh)
            voc_dem = vocT - turnout - vocSST
        return
          $ Heidi.insert (BR.heidiColKey "Demographic") (Heidi.VPDouble voc_dem)
          $ Heidi.insert (BR.heidiColKey "VOC - State Average") (Heidi.VPDouble $ voc_dem + vocSST) r