# 01b_2 RED Splits for Spotify.r

colsToPull.red_split <- c("accounting_month", "label_sc_group", "transac_type")

## NOTE: We are missing data for March 2013 to Oct 2013 ... but for accounting??
DT.RED_Split_Spotify.an <- 
  runQry(.m(
      tbl = "analytics"
    , schema = "bi"
    , colsToPull = colsToPull.red_split
    , colsToAgg = "units"
    , dateCol = "accounting_month"
    , minDate = "2013-11-01"
    , where = list(store_name = "Spotify")
    , limit = NULL
    ))

DT.RED_Split_Spotify.an[label_sc_group %ni% c("Orchard", "RED"), label_sc_group := "OSC"]
setkeyIfNot(DT.RED_Split_Spotify.an, colsToPull.red_split)
jesusForData(DT.RED_Split_Spotify.an)

DT.RED_Split_Spotify.an <- aggregateDT(DT.RED_Split_Spotify.an)

DT.RED_Split_Spotify   [, units_perc := units / sumn(units), by=accounting_month]
DT.RED_Split_Spotify.an[, units_perc := units / sumn(units), by=accounting_month]

DT.RED_Split_Merged <- merge(DT.RED_Split_Spotify, DT.RED_Split_Spotify.an, suffix=c(".acc", ".anal"))[, c("gross", "GPU") := NULL]

DT.RED_Split_Merged[, anal_to_acc := percOf(units_perc.anal, units_perc.acc)]

ggplot(DT.RED_Split_Merged[transac_type != "Download Tracks"], aes(x = accounting_month, y=anal_to_acc, color=label_sc_group)) + geom_line(aes(linetype = transac_type)) + percent.y()