resolve linting notes

R/dashboard_panels.R

@@ -1,6 +1,3 @@
-# message("Sourcing dashboard panels")
-
-
 homepage_panel <- function() {
   tabPanel(
     "User guide and information",
@@ -102,26 +99,24 @@ dashboard_panel <- function() {
         column(
           width = 12,
           expandable(
-            inputId = "details", label = textOutput("dropdown_label"),
+            input_id = "details", label = textOutput("dropdown_label"),
             contents =
               div(
                 id = "div_a",
-                # class = "well",
-                # style = "min-height: 100%; height: 100%; overflow-y: visible",
                 gov_row(
                   column(
                     width = 6,
                     selectizeInput("selectPhase",
                       "Select a school phase",
-                      choices = choicesPhase
+                      choices = choices_phase
                     )
                   ),
                   column(
                     width = 6,
                     selectizeInput(
                       inputId = "selectArea",
                       label = "Choose an area:",
-                      choices = choicesAreas$area_name
+                      choices = choices_areas$area_name
                     )
                   ),
                   column(
@@ -208,7 +203,7 @@ dashboard_panel <- function() {
                           width = 12,
                           selectizeInput("selectBenchLAs",
                             "Select benchmark local authorities",
-                            choices = choicesLAs$area_name,
+                            choices = choices_las$area_name,
                             multiple = TRUE,
                             options = list(maxItems = 3)
                           )

R/dfe_resources.R

@@ -7,8 +7,6 @@
 # 2023-09-21: update made to change hex codes to AF colours package
 # guidance here: https://best-practice-and-impact.github.io/afcolours/
 
-# message("Sourcing gss colour palette")
-
 suppressMessages(
   gss_colour_pallette <- afcolours::af_colours("categorical",
     colour_format = "hex", n = 6

R/dfe_template.R

@@ -1,17 +1,15 @@
 # This file contains scripts which are intended to provide standard styling
 # across dashboards. If you want to change anything in this script, please
-# talk to the DfE Statistics Development team first.
+# talk to the Explore education statistics platforms team first.
 
-# message("Sourcing dfe_template")
-valueBox <- function(value, subtitle, icon = NULL,
-                     color = "blue", width = 4,
-                     href = NULL, fontsize = "medium")
 # fontsize: can be small, medium or large
-{
-  validateColor(color)
+value_box <- function(value, subtitle, icon = NULL,
+                      color = "blue", width = 4,
+                      href = NULL, fontsize = "medium") {
+  validate_color(color)
   if (!is.null(icon)) tagAssert(icon, type = "i")
 
-  boxContent <- div(
+  box_content <- div(
     class = paste0("small-box bg-", color),
     div(
       class = "inner",
@@ -22,24 +20,24 @@ valueBox <- function(value, subtitle, icon = NULL,
   )
 
   if (!is.null(href)) {
-    boxContent <- a(href = href, boxContent)
+    box_content <- a(href = href, box_content)
   }
 
   div(
     class = if (!is.null(width)) paste0("col-sm-", width),
-    boxContent
+    box_content
   )
 }
 
-validColors <- c("blue", "dark-blue", "green", "orange", "purple", "white")
+valid_colors <- c("blue", "dark-blue", "green", "orange", "purple", "white")
 
-validateColor <- function(color) {
-  if (color %in% validColors) {
+validate_color <- function(color) {
+  if (color %in% valid_colors) {
     return(TRUE)
   }
 
   stop(
     "Invalid color: ", color, ". Valid colors are: ",
-    paste(validColors, collapse = ", "), "."
+    paste(valid_colors, collapse = ", "), "."
   )
 }

R/plotting.R

@@ -1,7 +1,4 @@
-# message("Sourcing plotting")
-
-
-createAvgRevTimeSeries <- function(df, inputArea) {
+create_avg_rev_timeseries <- function(df, input_area) {
   ggplot(df, aes(
     x = year,
     y = average_revenue_balance,
@@ -36,13 +33,13 @@ createAvgRevTimeSeries <- function(df, inputArea) {
     ylab(str_wrap("Average revenue balance", 16)) +
     scale_color_manual(
       "Area",
-      breaks = unique(c("England", inputArea)),
+      breaks = unique(c("England", input_area)),
       values = gss_colour_pallette
     )
 }
 
-plotAvgRevBenchmark <- function(dfRevenueBalance, inputArea) {
-  ggplot(dfRevenueBalance, aes(
+plot_avg_rev_benchmark <- function(df_revenue_balance, input_area) {
+  ggplot(df_revenue_balance, aes(
     x = str_wrap(area_name, width = 12),
     y = average_revenue_balance,
     fill = area_name,
@@ -71,7 +68,7 @@ plotAvgRevBenchmark <- function(dfRevenueBalance, inputArea) {
     ylab(str_wrap("Average revenue balance", 12)) +
     scale_fill_manual(
       "Area",
-      breaks = unique(dfRevenueBalance$area_name),
+      breaks = unique(df_revenue_balance$area_name),
       values = gss_colour_pallette
     )
 }

R/read_data.R

@@ -15,17 +15,17 @@ read_revenue_data <- function(
     file = "data/la_maintained_schools_revenue_reserve_final.csv") {
   # This reads in an example file. For the purposes of this demo, we're using
   # the latest LA expenditure data downloaded from the EES release.
-  dfRevenue <- read.csv(file)
+  df_revenue <- read.csv(file)
   # The time period column name has some non-ascii characters so we're just
   # going to rename it here.
-  colnames(dfRevenue)[1] <- "time_period"
-  dfRevenue <- dfRevenue %>% mutate(
+  colnames(df_revenue)[1] <- "time_period"
+  df_revenue <- df_revenue %>% mutate(
     year = as.numeric(paste0("20", substr(format(time_period), 5, 6))),
     area_name = case_when(
       geographic_level == "National" ~ country_name,
       geographic_level == "Regional" ~ region_name,
       TRUE ~ la_name
     )
   )
-  return(dfRevenue)
+  return(df_revenue)
 }

R/utils.R

@@ -1,80 +1 @@
-customDisconnectMessage <- function(refresh = "Refresh page",
-                                    links = sites_list,
-                                    publication_name = ees_pub_name,
-                                    publication_link = ees_publication) {
-  checkmate::assert_string(refresh)
-  htmltools::tagList(
-    htmltools::tags$script(
-      paste0(
-        "$(function() {",
-        "  $(document).on('shiny:disconnected', function(event) {",
-        "    $('#custom-disconnect-dialog').show();",
-        "    $('#ss-overlay').show();",
-        "  })",
-        "});"
-      )
-    ),
-    htmltools::tags$div(
-      id = "custom-disconnect-dialog",
-      style = "display: none !important;",
-      htmltools::tags$div(
-        id = "ss-connect-refresh",
-        tags$p("You've lost connection to the dashboard server - please try refreshing the page:"),
-        tags$p(tags$a(
-          id = "ss-reload-link",
-          href = "#", "Refresh page",
-          onclick = "window.location.reload(true);"
-        )),
-        if (length(links) > 1) {
-          tags$p(
-            "If this persists, you can also view the dashboard at one of our mirror sites:",
-            tags$p(
-              tags$a(href = links[1], "Site 1"),
-              " - ",
-              tags$a(href = links[2], "Site 2"),
-              if (length(links) == 3) {
-                "-"
-              },
-              if (length(links) == 3) {
-                tags$a(href = links[3], "Site 3")
-              }
-            )
-          )
-        },
-        if (!is.null(publication_name)) {
-          tags$p(
-            "All the data used in this dashboard can also be viewed or
-            downloaded via the ",
-            tags$a(
-              href = publication_link,
-              publication_name
-            ),
-            "on Explore Education Statistics."
-          )
-        },
-        tags$p(
-          "Please contact",
-          tags$a(
-            href = "mailto:[email protected]",
-            "[email protected]"
-          ),
-          "with details of any problems with this resource."
-        )
-        #  ),
-        # htmltools::tags$p("If this persists, you can view tables and data via the ",htmltools::tags$a(href ='https://explore-education-statistics.service.gov.uk/find-statistics/pupil-attendance-in-schools', "Pupil attendance in schools")," release on Explore Education Statistics and please contact [email protected] with details of what you were trying to do.")
-      )
-    ),
-    htmltools::tags$div(id = "ss-overlay", style = "display: none;"),
-    htmltools::tags$head(htmltools::tags$style(
-      glue::glue(
-        .open = "{{", .close = "}}",
-        "#custom-disconnect-dialog a {
-             display: {{ if (refresh == '') 'none' else 'inline' }} !important;
-             color: #1d70b8 !important;
-             font-size: 16px !important;
-             font-weight: normal !important;
-          }"
-      )
-    ))
-  )
-}
+# Add custom functions used across multiple places in the app into this script

global.R

@@ -54,8 +54,8 @@ sites_list <- c(site_primary, site_overflow)
 # publication name (e.g. the EES publication)
 ees_pub_name <- "Statistical publication"
 
-# Update with parent publication link
-ees_publication <- "https://explore-education-statistics.service.gov.uk/find-statistics/"
+# Update with parent publication link, using apprenticeships as an example
+ees_publication <- "https://explore-education-statistics.service.gov.uk/find-statistics/apprenticeships"
 google_analytics_key <- "Z967JJVQQX"
 
 # Read in the data
@@ -66,36 +66,36 @@ df_revbal <- read_revenue_data() %>%
   ))
 
 # Get geographical levels from data
-dfAreas <- df_revbal %>%
+df_areas <- df_revbal %>%
   select(
     geographic_level, country_name, country_code,
     region_name, region_code,
     la_name, old_la_code, new_la_code
   ) %>%
   distinct()
 
-choicesLAs <- dfAreas %>%
+choices_las <- df_areas %>%
   filter(geographic_level == "Local authority") %>%
   select(geographic_level, area_name = la_name) %>%
   arrange(area_name)
 
-choicesAreas <- dfAreas %>%
+choices_areas <- df_areas %>%
   filter(geographic_level == "National") %>%
   select(geographic_level, area_name = country_name) %>%
   rbind(
-    dfAreas %>%
+    df_areas %>%
       filter(geographic_level == "Regional") %>%
       select(geographic_level, area_name = region_name)
   ) %>%
-  rbind(choicesLAs)
+  rbind(choices_las)
 
-choicesYears <- unique(df_revbal$time_period)
+choices_years <- unique(df_revbal$time_period)
 
-choicesPhase <- unique(df_revbal$school_phase)
+choices_phase <- unique(df_revbal$school_phase)
 
-expandable <- function(inputId, label, contents) {
-  govDetails <- shiny::tags$details(
-    class = "govuk-details", id = inputId,
+expandable <- function(input_id, label, contents) {
+  gov_details <- shiny::tags$details(
+    class = "govuk-details", id = input_id,
     shiny::tags$summary(
       class = "govuk-details__summary",
       shiny::tags$span(