R/prepare_app_data.R

In luceydav/irsSOI: Tools to load and explore IRS SOI Zip Data

#' Function to select cols and add city/county
#'
#' @description
#' Helper to
#'
#' @param irs Cleaned IRS data.table from [clean_soi()]
#'
#' @examples
#' \dontrun{library(data.table)
#' irs_app_data <- prepare_app_data(irs)}
#'
#' @importFrom glue glue_data
#'
#' @export
prepare_app_data <- function(irs) {

  data <- data.table::copy(irs)

  cols <-
    c(
      "year",
      "zipcode",
      "state",
      "agi_level",
      "agi_level_2",
      "a00100", # agi
      "a00200", # salary
      "n00200",
      "total_tax", # derived
      "n1",
      "n2", # exemptions
      "numdep",
      "a01000", # gains
      "n01000",
      "a02300", # unemploy
      "n02300",
      "a09750", # healthcare indiv
      "n09750",
      "a04470", # total item deds
      "a18425", # sl tax
      "n18425",
      "a18450", # sales tax
      "n18450",
      "a18500", # RE tax
      "n18500",
      "a19300", # mortgage
      "n19300",
      "a19700", # contributions
      "n19700",
      "a09600", # amt
      "n09600",
      "a11000", # eitc (early)
      "n11000",
      "a59660", # eitc (late)
      "n59660",
      "a00600", # dividends
      "n00600",
      "a00300", # interest
      "n00300",
      "a00900", # business inc
      "n00900",
      "a26270", # pship/scorp net inc
      "n26270",
      "a85300", # net inv income tax (late)
      "n85300",
      "a01700", # pension/annuity
      "n01700",
      "a02500", # soc sec
      "n02500"
    )

  # Select specified columns, then filter any zip codes where
  data <- data[, cols, with = FALSE]

  # number of returns < 100 in any year in specified year range
  drops <- unique(data[, .SD[sum(n1) < 100], list(zipcode, year)]$zipcode)
  data <- data[!zipcode %chin% drops]

  # Set key
  setkeyv(data, c("year", "zipcode", "agi_level"))

  return(data)
}