R/make_summary_DT.R

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

#' Function to take incoming reactive data.frame, convert to data.table and build Summary DT
#'
#' @description
#' Makes a Summary datatable of AGI, Federal Tax, Total returns and Unique Zips by year
#' using output of [clean_soi()]
#'
#' @param data IRS data.table
#' @param type chr specifying how to display data
#'
#' @import htmltools
#' @importFrom stats setNames
#'
#' @export
make_summary_DT <- function(data, type = "agi") {

  # data <-
  #  fst::read_fst("/Users/davidlucey/Desktop/David/Projects/irs_soi_app/data/irs_app_data.fst")

  # Convert data to data.table if not one
  if (!data.table::is.data.table(data) ){
    data.table::setDT(data)
  } else {
    data <- data.table::copy(data)
  }

  # Set scale as filtered down to zipcode
  if (length(data$zipcode) < 500 & type == "agi") {
    digits <- 3
  } else {
    digits <- 1
  }

  if( type == "agi") {

    data <- data[,
                 list(
                   tot_agi = sum(as.numeric(a00100), na.rm = TRUE) / 1000000,
                   tot_tax = sum(as.numeric(total_tax), na.rm = TRUE) /
                     1000000,
                   tot_returns = sum(as.numeric(n1), na.rm = TRUE) / 1000000,
                   tot_indiv = sum(as.numeric(n2), na.rm = TRUE) / 1000000,
                   unique_zips = length(unique(zipcode))
                 ),
                 by = year]

  } else {

    data <-
      data[,
           {
             tot_agi = sum(as.numeric(a00100), na.rm = TRUE) / 1000000
           tot_tax = sum(as.numeric(total_tax), na.rm = TRUE) /
             1000000
           tot_returns = sum(as.numeric(n1), na.rm = TRUE)
           tot_indiv = sum(as.numeric(n2), na.rm = TRUE)
           area = sum(as.numeric(land_area_in_sqmi), na.rm = TRUE)
           unique_zips = length(unique(zipcode))
           n1 = sum(as.numeric(n1), na.rm = TRUE) / 1000000
           list(
             agi_cap = tot_agi / n1,
             tax_cap = tot_tax / n1,
             indiv_cap = tot_indiv / tot_returns,
             pop_density = (tot_indiv * length(unique(agi_level))) / area,
             unique_zips
           )},
           by = year]

  }

  # Fix labels
  scale <- data.table::fifelse(type == "per_cap", "$k", "$B")
  scope <- data.table::fifelse(type == "per_cap", "Per Cap", "Aggregated Total")
  type_text <- data.table::fifelse(type == "per_cap", "Per Capita ", "")
  caption <- data.table::fifelse(
    type == "per_cap",
    glue::glue("AGI {scope}, Fed'l Tax {scope}, Family Size and Pop. Density by Selection"),
    glue::glue('{scope} AGI, Federal Tax, Total Returns, Individuals and Unique Zips by Selection')
  )
  pg_length <- length(unique(data$year))

  # Table
  # https://taxfoundation.org/federal-tax-revenue-source-1934-2018/
  DT::datatable(
    data,
    colnames = c(
      "Year",
      glue::glue("AGI {type_text}{scale}"),
      glue::glue("Fed'l Tax {type_text}{scale}"),
      data.table::fifelse(type == "per_cap", "Family Size", "Returns (m)"),
      data.table::fifelse(type == "per_cap", "Pop Density (SQM.)", "Popu. (m)"),
      "Zips"
    ),
    options =
      list(
        pageLength = pg_length,
        scrollY = TRUE,
        dom = 't'
      ),
    caption = htmltools::tags$caption(
      style = 'caption-side: top; text-align: center;',
      '', htmltools::em(caption)
    ),
    rownames = FALSE
  ) %>%
    DT::formatRound(
      columns = c(2:5),
      mark = ",",
      digits = digits
    ) %>%
    DT::formatRound(
      columns = 6,
      mark = ",",
      digits = 0
    )
}