R/quad_new.R

In sudhakar-valgen/analyticsprospervue: Analytics applications for use in Salesforce

#'
#'This function takes two variables and converts them into a quad
#'@import RForcecom
#'@import dplyr
#'@export quad_new

quad_new <- function(access_token, instance_url, object, field1, data_type1,field2, data_type2,newname){

  instance_u <- paste0(instance_url,'/')
  api <- '36.0'
  myobject <- object
  myquery <- paste0('Select Id, ', field1,', ',field2,' FROM ', myobject)
  session <- c(sessionID = access_token,instanceURL = instance_u, apiVersion = api)
  data1 <- rforcecom.bulkQuery(session, myquery, myobject)

  data1 <- na.omit(data1)
  # data_type1 = "B"
  # data_type2 = "A"
  if(data_type1 == "B"){
    var1 <- date_recency(data1[,2],5)
  }else{
    #data3 <- past_date_recency(data1[,2],5)
    var1 <- data1[,2]
  }

  if(data_type2 == "B"){
    var2 <- date_recency(data1[,3],5)

  }else{
    #data3 <- past_date_recency(data1[,3],5)
    var2 <- data1[,3]

  }


  #var1 <- data1[,2]
  #var2 <- data1[,3]
  var1 <- data_clean(var1, data_type1) # New variable is created
  var2 <- data_clean(var2, data_type2)

  newdata <- data.frame(Id = data1$Id, var1, var2)
  summary <- newdata %>% group_by(var1, var2) %>%
    summarise(counts = n())
  summary$Rank <- rank(-summary$counts, ties.method = "random")
  newdata <- merge(newdata, summary, all = T)
  newdata <- subset(newdata, select = c('Id', 'Rank'))
  colnames(newdata) <- c("Id", newname)
  updater(access_token, instance_url, myobject, newdata)
}