tests/testthat/test-make_industry_table.R

In djpr-data/djprlabourdash: DJSIR Jobs Dashboard

test_that("make_industry_table() makes the industry table", {
  # Clear any leftover environmental variables from earlier tests
  Sys.unsetenv("R_DJPRLABOURDASH_TABLEDEST")

  i_t <- make_industry_table(
    data = filter_dash_data(
      c(
        "A84601662A",
        "A84601680F",
        "A84601683L",
        "A84601686V",
        "A84601665J",
        "A84601704L",
        "A84601707V",
        "A84601710J",
        "A84601638A",
        "A84601653X",
        "A84601689A",
        "A84601656F",
        "A84601713R",
        "A84601668R",
        "A84601695W",
        "A84601698C",
        "A84601650T",
        "A84601671C",
        "A84601641R",
        "A84601716W")
    ),
    row_order = c(
      "A84601662A",
      "A84601680F",
      "A84601683L",
      "A84601686V",
      "A84601665J",
      "A84601704L",
      "A84601707V",
      "A84601710J",
      "A84601638A",
      "A84601653X",
      "A84601689A",
      "A84601656F",
      "A84601713R",
      "A84601668R",
      "A84601695W",
      "A84601698C",
      "A84601650T",
      "A84601671C",
      "A84601641R",
      "A84601716W")
    )

  expect_s3_class(i_t, "flextable")

  i_t_header_row <- as.character(i_t$header$dataset[1, ])

  expect_equal(
    i_t_header_row,
    c(
      "",
      "Current figures",
      "Current figures",
      "Change in latest period",
      "Change in past year",
      "Change since COVID-19",
      "Change during govt"
    )
  )

  i_t_final_col <- i_t$body$dataset$`SINCE NOV 2014`
  expect_type(i_t_final_col, "character")
  expect_true(all(nchar(i_t_final_col) >= 1))
})

test_that("make_industry_table()'s output has not changed", {

  data <- djprlabourdash:::filter_dash_data(
    c(
      "A84601662A",
      "A84601680F",
      "A84601683L",
      "A84601686V",
      "A84601665J",
      "A84601704L",
      "A84601707V",
      "A84601710J",
      "A84601638A",
      "A84601653X",
      "A84601689A",
      "A84601656F",
      "A84601713R",
      "A84601668R",
      "A84601695W",
      "A84601698C",
      "A84601650T",
      "A84601671C",
      "A84601641R",
      "A84601716W")
  ) %>%
    dplyr::filter(.data$date <= as.Date("2022-05-02"))

  to_may_2022 <- data %>%
    dplyr::mutate(
      indicator = dplyr::if_else(.data$industry != "",
                                 .data$industry,
                                 "Victoria - all industries")
    )

  table <- make_industry_table(to_may_2022,
    row_order = c(
      "A84601662A",
      "A84601680F",
      "A84601683L",
      "A84601686V",
      "A84601665J",
      "A84601704L",
      "A84601707V",
      "A84601710J",
      "A84601638A",
      "A84601653X",
      "A84601689A",
      "A84601656F",
      "A84601713R",
      "A84601668R",
      "A84601695W",
      "A84601698C",
      "A84601650T",
      "A84601671C",
      "A84601641R",
      "A84601716W"),
    highlight_rows = "A84601662A"

  )

  expect_s3_class(table, "flextable")

  table_df <- table$body$dataset
  expect_s3_class(table_df, "data.frame")
  expect_equal(
    names(table_df),
    c(
      " ",
      "SERIES_ID",
      "MAY 2022",
      "% OF TOTAL",
      "LAST 3 YEARS",
      "SINCE FEB 2022",
      "SINCE MAY 2021",
      "SINCE FEB 2020",
      "SINCE NOV 2014"
    )
  )

  table_without_sparklines <- dplyr::select(
    table_df,
    -`LAST 3 YEARS`
  )
  expect_snapshot_output(table_without_sparklines)
})