Rename to profile_ranking

NAMESPACE

@@ -8,7 +8,7 @@ export(aka)
 export(as_label)
 export(as_name)
 export(emissions_profile)
-export(emissions_profile_any_add_values_to_categorize)
+export(emissions_profile_any_add_profile_ranking)
 export(emissions_profile_upstream)
 export(enquo)
 export(enquos)

NEWS.md

@@ -2,16 +2,16 @@
 
 # tiltIndicator 0.0.0.9098
 
-* `emissions_profile_any_add_values_to_categorize()` now relocates the new
+* `emissions_profile_any_add_profile_ranking()` now relocates the new
 columns to the left.
 
 # tiltIndicator 0.0.0.9097
 
-* `emissions_profile*()` uses `co2$values_to_categorize` if present (#605).
+* `emissions_profile*()` uses `co2$profile_ranking` if present (#605).
 
 # tiltIndicator 0.0.0.9096
 
-* New pre-processing helper `emissions_profile_any_add_values_to_categorize()`
+* New pre-processing helper `emissions_profile_any_add_profile_ranking()`
 (#602).
 
 # tiltIndicator 0.0.0.9095

R/emissions_profile_any_add_values_to_categorize.R

@@ -6,7 +6,7 @@
 #' @family pre-processing helpers
 #'
 #' @return The input data frame with the additional columns `grouped_by` and
-#'   `values_to_categorize` and one row per benchmark per company.
+#'   `profile_ranking` and one row per benchmark per company.
 #'
 #' @export
 #'
@@ -18,25 +18,25 @@
 #' companies <- read_csv(toy_emissions_profile_any_companies())
 #'
 #' products <- read_csv(toy_emissions_profile_products())
-#' products |> emissions_profile_any_add_values_to_categorize()
+#' products |> emissions_profile_any_add_profile_ranking()
 #'
 #' inputs <- read_csv(toy_emissions_profile_upstream_products())
-#' inputs |> emissions_profile_any_add_values_to_categorize()
-emissions_profile_any_add_values_to_categorize <- function(data) {
-  check_emissions_profile_any_add_values_to_categorize(data)
+#' inputs |> emissions_profile_any_add_profile_ranking()
+emissions_profile_any_add_profile_ranking <- function(data) {
+  check_emissions_profile_any_add_profile_ranking(data)
 
-  if (hasName(data, "values_to_categorize")) {
+  if (hasName(data, "profile_ranking")) {
     out <- check_crucial_names(data, "grouped_by")
   } else {
     benchmarks <- set_names(epa_benchmarks(data), flat_benchmarks(data))
     out <- map_df(benchmarks, ~ add_rank(data, .x), .id = "grouped_by")
   }
 
-  related_cols <- c("grouped_by", "values_to_categorize")
+  related_cols <- c("grouped_by", "profile_ranking")
   relocate(out, all_of(related_cols))
 }
 
-check_emissions_profile_any_add_values_to_categorize <- function(data) {
+check_emissions_profile_any_add_profile_ranking <- function(data) {
   crucial <- c(aka("tsector"), aka("xunit"), aka("isic"), aka("co2footprint"))
   walk(crucial, \(pattern) check_matches_name(data, pattern))
 }
@@ -64,7 +64,7 @@ add_rank <- function(data, .by) {
   if (identical(.by, "all")) .by <- NULL
   mutate(
     data,
-    values_to_categorize = rank_proportion(.data[[extract_name(data, aka("co2footprint"))]]),
+    profile_ranking = rank_proportion(.data[[extract_name(data, aka("co2footprint"))]]),
     .by = all_of(.by)
   )
 }

R/emissions_profile_any_at_product_level.R

@@ -10,7 +10,7 @@ emissions_profile_any_at_product_level <- function(companies,
   .co2 <- prepare_co2(co2, low_threshold, high_threshold)
 
   .co2 |>
-    emissions_profile_any_add_values_to_categorize() |>
+    emissions_profile_any_add_profile_ranking() |>
     add_risk_category(low_threshold, high_threshold) |>
     join_companies(.companies) |>
     epa_select_cols_at_product_level() |>

R/sector_profile_at_product_level.R

@@ -9,7 +9,7 @@ sector_profile_at_product_level <- function(companies,
   .scenarios <- prepare_scenarios(scenarios, low_threshold, high_threshold)
 
   .companies |>
-    spa_add_values_to_categorize(.scenarios) |>
+    spa_add_profile_ranking(.scenarios) |>
     add_risk_category(low_threshold, high_threshold, .default = NA) |>
     spa_polish_output_at_product_level() |>
     sp_select_cols_at_product_level() |>

R/sector_profile_upstream_at_product_level.R

@@ -11,7 +11,7 @@ sector_profile_upstream_at_product_level <- function(companies,
   .inputs <- prepare_inputs(inputs)
 
   .inputs |>
-    spa_add_values_to_categorize(.scenarios) |>
+    spa_add_profile_ranking(.scenarios) |>
     add_risk_category(low_threshold, high_threshold, .default = NA) |>
     join_companies(remove_col_scenario(.companies)) |>
     spa_polish_output_at_product_level() |>

R/spa.R

@@ -39,10 +39,10 @@ prepare_scenarios <- function(data, low_threshold, high_threshold) {
   data |>
     mutate(low_threshold = low_threshold, high_threshold = high_threshold) |>
     distinct() |>
-    rename(values_to_categorize = aka("co2reduce"))
+    rename(profile_ranking = aka("co2reduce"))
 }
 
-spa_add_values_to_categorize <- function(data, scenarios) {
+spa_add_profile_ranking <- function(data, scenarios) {
   left_join(
     data, scenarios,
     by = c(aka("scenario_type"), aka("xsector"), aka("xsubsector")),

R/utils.R

@@ -105,7 +105,7 @@ abort_missing_names <- function(missing_names) {
 
 add_risk_category <- function(data, low_threshold, high_threshold, ...) {
   mutate(data, risk_category = categorize_risk(
-    .data$values_to_categorize, .data$low_threshold, .data$high_threshold, ...
+    .data$profile_ranking, .data$low_threshold, .data$high_threshold, ...
   ))
 }
 

tests/testthat/test-emissions_profile_any_add_values_to_categorize.R

@@ -1,33 +1,33 @@
 test_that("works with any 'co2-like' dataset", {
   co2 <- example_products()
-  expect_no_error(emissions_profile_any_add_values_to_categorize(co2))
+  expect_no_error(emissions_profile_any_add_profile_ranking(co2))
 
   co2 <- example_inputs()
-  expect_no_error(emissions_profile_any_add_values_to_categorize(co2))
+  expect_no_error(emissions_profile_any_add_profile_ranking(co2))
 })
 
-test_that("adds columns `grouped_by` and `values_to_categorize`", {
+test_that("adds columns `grouped_by` and `profile_ranking`", {
   co2 <- example_products()
 
-  out <- emissions_profile_any_add_values_to_categorize(co2)
+  out <- emissions_profile_any_add_profile_ranking(co2)
 
-  new_names <- c("grouped_by", "values_to_categorize")
+  new_names <- c("grouped_by", "profile_ranking")
   expect_equal(setdiff(names(out), names(co2)), new_names)
 })
 
-test_that("adds columns `grouped_by` and `values_to_categorize` to the left", {
+test_that("adds columns `grouped_by` and `profile_ranking` to the left", {
   co2 <- example_products()
 
-  out <- emissions_profile_any_add_values_to_categorize(co2)
+  out <- emissions_profile_any_add_profile_ranking(co2)
 
-  new_names <- c("grouped_by", "values_to_categorize")
+  new_names <- c("grouped_by", "profile_ranking")
   expect_equal(names(out)[1:2], new_names)
 })
 
 test_that("with one company, adds one row per benchmark per company", {
   co2 <- example_products()
 
-  out <- emissions_profile_any_add_values_to_categorize(co2)
+  out <- emissions_profile_any_add_profile_ranking(co2)
 
   number_of_benchmarks <- length(flat_benchmarks(co2))
   expect_equal(nrow(out), number_of_benchmarks)
@@ -36,7 +36,7 @@ test_that("with one company, adds one row per benchmark per company", {
 test_that("with two companies, adds one row per benchmark per company", {
   co2 <- example_products(!!aka("id") := c("a", "b"))
 
-  out <- emissions_profile_any_add_values_to_categorize(co2)
+  out <- emissions_profile_any_add_profile_ranking(co2)
 
   number_of_benchmarks <- length(flat_benchmarks(co2))
   expect_equal(nrow(out), 2 * number_of_benchmarks)
@@ -47,24 +47,24 @@ test_that("without crucial columns errors gracefully", {
 
   crucial <- aka("tsector")
   bad <- select(co2, -all_of(crucial))
-  expect_error(emissions_profile_any_add_values_to_categorize(bad), crucial)
+  expect_error(emissions_profile_any_add_profile_ranking(bad), crucial)
 
   crucial <- aka("xunit")
   bad <- select(co2, -all_of(crucial))
-  expect_error(emissions_profile_any_add_values_to_categorize(bad), crucial)
+  expect_error(emissions_profile_any_add_profile_ranking(bad), crucial)
 
   crucial <- aka("isic")
   bad <- select(co2, -all_of(crucial))
-  expect_error(emissions_profile_any_add_values_to_categorize(bad), crucial)
+  expect_error(emissions_profile_any_add_profile_ranking(bad), crucial)
 
   crucial <- aka("co2footprint")
   bad <- select(co2, -all_of(crucial))
-  expect_error(emissions_profile_any_add_values_to_categorize(bad), crucial)
+  expect_error(emissions_profile_any_add_profile_ranking(bad), crucial)
 })
 
-test_that("if `values_to_categorize` is present, `grouped_by` must be present", {
-  co2 <- example_products(values_to_categorize = 1)
+test_that("if `profile_ranking` is present, `grouped_by` must be present", {
+  co2 <- example_products(profile_ranking = 1)
 
   crucial <- "grouped_by"
-  expect_error(emissions_profile_any_add_values_to_categorize(co2), crucial)
+  expect_error(emissions_profile_any_add_profile_ranking(co2), crucial)
 })

tests/testthat/test-emissions_profile_any_at_product_level.R

@@ -287,46 +287,46 @@ test_that("`*rowid` columns are passed through inputs with duplicates", {
   expect_true(hasName(out, "products_rowid"))
 })
 
-test_that("with products, uses `co2$values_to_categorize` if present (#603)", {
+test_that("with products, uses `co2$profile_ranking` if present (#603)", {
   companies <- example_companies()
   co2 <- example_products(!!aka("uid") := c("a", "b"))
   co2[extract_name(co2, aka("co2footprint"))] <- 1:2
 
-  lacks_values_to_categorize <- !hasName(co2, "values_to_categorize")
-  stopifnot(lacks_values_to_categorize)
+  lacks_profile_ranking <- !hasName(co2, "profile_ranking")
+  stopifnot(lacks_profile_ranking)
   out1 <- emissions_profile_any_at_product_level(companies, co2)
   using_computed_values <- unique(out1$risk_category)
 
-  pre_computed <- emissions_profile_any_add_values_to_categorize(co2)
-  has_values_to_categorize <- hasName(pre_computed, "values_to_categorize")
-  stopifnot(has_values_to_categorize)
+  pre_computed <- emissions_profile_any_add_profile_ranking(co2)
+  has_profile_ranking <- hasName(pre_computed, "profile_ranking")
+  stopifnot(has_profile_ranking)
 
   yields_a_different_risk_category <- 999
-  pre_computed$values_to_categorize <- yields_a_different_risk_category
+  pre_computed$profile_ranking <- yields_a_different_risk_category
   out2 <- emissions_profile_any_at_product_level(companies, pre_computed)
   using_pre_computed_values <- unique(out2$risk_category)
 
   expect_false(identical(using_computed_values, using_pre_computed_values))
 })
 
-test_that("with inputs, uses `co2$values_to_categorize` if present (#603)", {
+test_that("with inputs, uses `co2$profile_ranking` if present (#603)", {
   companies <- example_companies()
   co2 <- example_inputs(!!aka("uid") := c("a", "b"))
   # This is wrong: names(example_inputs(!!aka("co2footprint") := 1:2))
   # It yields two columns: `co2_footprint` AND `input_co2_footprint`
   co2[extract_name(co2, aka("co2footprint"))] <- 1:2
 
-  lacks_values_to_categorize <- !hasName(co2, "values_to_categorize")
-  stopifnot(lacks_values_to_categorize)
+  lacks_profile_ranking <- !hasName(co2, "profile_ranking")
+  stopifnot(lacks_profile_ranking)
   out1 <- emissions_profile_any_at_product_level(companies, co2)
   using_computed_values <- unique(out1$risk_category)
 
-  pre_computed <- emissions_profile_any_add_values_to_categorize(co2)
-  has_values_to_categorize <- hasName(pre_computed, "values_to_categorize")
-  stopifnot(has_values_to_categorize)
+  pre_computed <- emissions_profile_any_add_profile_ranking(co2)
+  has_profile_ranking <- hasName(pre_computed, "profile_ranking")
+  stopifnot(has_profile_ranking)
 
   yields_a_different_risk_category <- 999
-  pre_computed$values_to_categorize <- yields_a_different_risk_category
+  pre_computed$profile_ranking <- yields_a_different_risk_category
   out2 <- emissions_profile_any_at_product_level(companies, pre_computed)
   using_pre_computed_values <- unique(out2$risk_category)