Create own inputs (#45)

* Fix: Re-adding input synchronisation across pages for LA

* Chore: Functionising the filtering of BDS by topic for app inputs, using raw BDS topic indicators to get dupes to appear across topics

* Chore: BDS metrics no longer needed in app inputs mod

* Feat: Converting Create Your Own inputs to not use topic to filter the BDS, in order to sort URL bookmarking

* Chore: Filtering out the discontinued indicators at the point the data dict is loaded in

* Feat: For duplicate indicators across topics, combining the topic names in BDS (mainly for Create Your Own table)

* Feat: Applying the decoipling of topic column to Create Own table (thus charts), had to update get x-axis fn to deal with multiple labels

* Feat: Functionising the dynamic topic label, though leaving out of Create Your Own for now as could have too many topics in label

* Chore: Roxgyen comments for dynamic topic label fn

* Feat: Updating sever script for new Create Your Own inputs param and removing the topic input from bookmarking

* Tests: Updating test fn to remove bds_metrics (no longer needed)

* Style: Linting indent corrections

* Fix: Topic filtering for dynamic label needs an any() wrapped around the check if topic input is all or empty

02_dev/all_la_page/all_la_dev_app_mod.R

@@ -46,7 +46,6 @@ server_mod <- function(input, output, session) {
   app_inputs <- appInputsServer(
     "all_la_inputs",
     shared_values,
-    bds_metrics,
     topic_indicator_full
   )
 

02_dev/bds_wide_to_long.qmd

@@ -1,175 +1,176 @@
----
-title: "LAIT - Shiny upgrade"
-subtitle: "Workings and development code"
-format: html
-date-modified: "`r Sys.Date()`"
-output:
-  html_document:
-  toc: true
-output-file: lait_workings
-embed-resources: true
-execute:
-  echo: false
-  cache: true
-  message: false
-  warning: false
----
-
-
-```{r src-funs}
-source(here::here("R/fn_helper_functions.R"))
-source(here::here("R/fn_load_data.R"))
-```
-
-Load the latest Data Dictionary
-
-```{r write-data_dict}
-# Load raw Data Dict from shared folder
-data_dict <- readxl::read_xlsx(
-  path = paste0(shared_folder, "/../Information for App Development/LAIT Data Dictionary (To QA!).xlsx"),
-  sheet = "Data_prod",
-  # Replace multi-space with single-space
-  .name_repair = clean_spaces
-)
-
-# Write .csv version
-write.csv(
-  data_dict,
-  here::here("01_data/02_prod/LAIT Data Dictionary.csv"),
-  row.names = FALSE
-)
-```
-
-Logic to load BDS wide and convert to long
-
-```{r pull-latest-bds-data}
-# Load raw BDS wide from shared folder
-bds_wide_raw_sf <- readxl::read_xlsx(
-  path = paste0(shared_folder, "/../Information for App Development/BDS - 2024 (JAKE).xlsx"),
-  sheet = "BDS New",
-  col_names = TRUE,
-  skip = 1,
-  # Replace multi-space with single-space
-  .name_repair = clean_spaces,
-  col_types = "text"
-)
-
-
-
-# Save to data folder
-write.csv(
-  bds_wide_raw_sf,
-  here::here("01_data/01_raw/BDS_Wide.csv"),
-  row.names = FALSE
-)
-```
-
-
-```{r load-bds}
-# Load BDS wide
-bds_wide_raw <- read.csv(
-  here::here("01_data/01_raw/BDS_Wide.csv"),
-  check.names = FALSE
-)
-
-# styler: off
-# Remove any cols that are all na
-bds_wide <- bds_wide_raw |>
-  { \(.) dplyr::select(., dplyr::all_of(non_empty_colnames(.))) }() # nolint: brace
-# styler: on
-```
-
-
-```{r wide-long}
-# Pivot BDS long on geographic cols
-bds_long <- bds_wide |>
-  tidyr::pivot_longer(
-    cols = `Barking and Dagenham`:`South West`,
-    names_to = "LA and Regions",
-    values_to = "Values"
-  ) |>
-  # Removes these lines with matching entries in year column
-  dplyr::filter(
-    Years %notin% c(
-      "-",
-      "",
-      "Trend",
-      "Change",
-      "Rank",
-      "Target",
-      "Distance",
-      "Quartile",
-      "Deviation National",
-      "% YoY change",
-      "%3yr change",
-      "2010 Target",
-      "Target 2011",
-      "NA - Distance",
-      is.na(0)
-    )
-  )
-```
-
-
-```{r bds-clean}
-# Delete lines in vector from column, remove '.'s and underscores/number
-bds_long_clean <- bds_long |>
-  dplyr::select(-line) |>
-  dplyr::mutate(
-    "LA and Regions" = stringr::str_replace_all(`LA and Regions`, "\\.", " "),
-    "LA and Regions" = stringr::str_replace_all(`LA and Regions`, "  ", "\\. "),
-
-    # Remove final _ and following digits
-    # NOTE: Also remove whitespace - 'LACStableNum_2016on'
-    `Short Desc` = trimws(sub("_\\d+$", "", `Short Desc`))
-  )
-```
-
-
-```{r bds-la_codes}
-# Load LA codes
-la_codes <- readxl::read_xlsx(
-  path = here::here("01_data/02_prod/LA code list.xlsx")
-)
-
-# Join to bds and create combined codes var
-bds_long_la <- bds_long_clean |>
-  dplyr::left_join(la_codes, by = c("LA and Regions" = "LA Name")) |>
-  dplyr::select(-Type)
-```
-
-
-```{r bds-data_dict}
-# Pull list of measures from data dictionary (primary key and filters for
-# only public-safe/in-use measures)
-# NOTE: Children_away changed to Children_Away to match BDS
-data_dict <- read.csv(
-  file = paste0("01_data/02_prod/LAIT Data Dictionary.csv"),
-  check.names = FALSE
-) |>
-  dplyr::mutate(Measure_short = trimws(Measure_short)) |>
-  dplyr::filter(!grepl("DISCONTINUE", Table_status)) |>
-  pull_uniques("Measure_short")
-
-# Filter BDS for only measures in the data dict
-bds_long_public <- bds_long_la |>
-  dplyr::filter(`Short Desc` %in% data_dict)
-```
-
-
-```{r bds-save}
-# Write out parquet version
-arrow::write_dataset(
-  bds_long_public,
-  here::here("01_data/02_prod/"),
-  format = "parquet",
-  basename_template = "bds_long_{i}.parquet"
-)
-
-# Write .csv version (for public use)
-write.csv(
-  bds_long_public,
-  here::here("01_data/02_prod/bds_long.csv"),
-  row.names = FALSE
-)
-```
+---
+title: "LAIT - Shiny upgrade"
+subtitle: "Workings and development code"
+format: html
+date-modified: "`r Sys.Date()`"
+output:
+  html_document:
+  toc: true
+output-file: lait_workings
+embed-resources: true
+execute:
+  echo: false
+  cache: true
+  message: false
+  warning: false
+---
+
+
+```{r src-funs}
+source(here::here("R/fn_helper_functions.R"))
+source(here::here("R/fn_load_data.R"))
+```
+
+Load the latest Data Dictionary
+
+```{r write-data_dict}
+# Load raw Data Dict from shared folder
+data_dict <- readxl::read_xlsx(
+  path = paste0(shared_folder, "/../Information for App Development/LAIT Data Dictionary (To QA!).xlsx"),
+  sheet = "Data_prod",
+  # Replace multi-space with single-space
+  .name_repair = clean_spaces
+) |>
+  dplyr::filter(!grepl("DISCONTINUE", Table_status))
+
+# Write .csv version
+write.csv(
+  data_dict,
+  here::here("01_data/02_prod/LAIT Data Dictionary.csv"),
+  row.names = FALSE
+)
+```
+
+Logic to load BDS wide and convert to long
+
+```{r pull-latest-bds-data}
+# Load raw BDS wide from shared folder
+bds_wide_raw_sf <- readxl::read_xlsx(
+  path = paste0(shared_folder, "/../Information for App Development/BDS - 2024 (JAKE).xlsx"),
+  sheet = "BDS New",
+  col_names = TRUE,
+  skip = 1,
+  # Replace multi-space with single-space
+  .name_repair = clean_spaces,
+  col_types = "text"
+)
+
+
+
+# Save to data folder
+write.csv(
+  bds_wide_raw_sf,
+  here::here("01_data/01_raw/BDS_Wide.csv"),
+  row.names = FALSE
+)
+```
+
+
+```{r load-bds}
+# Load BDS wide
+bds_wide_raw <- read.csv(
+  here::here("01_data/01_raw/BDS_Wide.csv"),
+  check.names = FALSE
+)
+
+# styler: off
+# Remove any cols that are all na
+bds_wide <- bds_wide_raw |>
+  { \(.) dplyr::select(., dplyr::all_of(non_empty_colnames(.))) }() # nolint: brace
+# styler: on
+```
+
+
+```{r wide-long}
+# Pivot BDS long on geographic cols
+bds_long <- bds_wide |>
+  tidyr::pivot_longer(
+    cols = `Barking and Dagenham`:`South West`,
+    names_to = "LA and Regions",
+    values_to = "Values"
+  ) |>
+  # Removes these lines with matching entries in year column
+  dplyr::filter(
+    Years %notin% c(
+      "-",
+      "",
+      "Trend",
+      "Change",
+      "Rank",
+      "Target",
+      "Distance",
+      "Quartile",
+      "Deviation National",
+      "% YoY change",
+      "%3yr change",
+      "2010 Target",
+      "Target 2011",
+      "NA - Distance",
+      is.na(0)
+    )
+  )
+```
+
+
+```{r bds-clean}
+# Delete lines in vector from column, remove '.'s and underscores/number
+bds_long_clean <- bds_long |>
+  dplyr::select(-line) |>
+  dplyr::mutate(
+    "LA and Regions" = stringr::str_replace_all(`LA and Regions`, "\\.", " "),
+    "LA and Regions" = stringr::str_replace_all(`LA and Regions`, "  ", "\\. "),
+
+    # Remove final _ and following digits
+    # NOTE: Also remove whitespace - 'LACStableNum_2016on'
+    `Short Desc` = trimws(sub("_\\d+$", "", `Short Desc`))
+  )
+```
+
+
+```{r bds-la_codes}
+# Load LA codes
+la_codes <- readxl::read_xlsx(
+  path = here::here("01_data/02_prod/LA code list.xlsx")
+)
+
+# Join to bds and create combined codes var
+bds_long_la <- bds_long_clean |>
+  dplyr::left_join(la_codes, by = c("LA and Regions" = "LA Name")) |>
+  dplyr::select(-Type)
+```
+
+
+```{r bds-data_dict}
+# Pull list of measures from data dictionary (primary key and filters for
+# only public-safe/in-use measures)
+# NOTE: Children_away changed to Children_Away to match BDS
+data_dict <- read.csv(
+  file = paste0("01_data/02_prod/LAIT Data Dictionary.csv"),
+  check.names = FALSE
+) |>
+  dplyr::mutate(Measure_short = trimws(Measure_short)) |>
+  dplyr::filter(!grepl("DISCONTINUE", Table_status)) |>
+  pull_uniques("Measure_short")
+
+# Filter BDS for only measures in the data dict
+bds_long_public <- bds_long_la |>
+  dplyr::filter(`Short Desc` %in% data_dict)
+```
+
+
+```{r bds-save}
+# Write out parquet version
+arrow::write_dataset(
+  bds_long_public,
+  here::here("01_data/02_prod/"),
+  format = "parquet",
+  basename_template = "bds_long_{i}.parquet"
+)
+
+# Write .csv version (for public use)
+write.csv(
+  bds_long_public,
+  here::here("01_data/02_prod/bds_long.csv"),
+  row.names = FALSE
+)
+```

02_dev/create_your_own_page/create_own_table_dev_mod_app.R

@@ -61,7 +61,10 @@ ui <- bslib::page_fillable(
 # Main App Server
 server <- function(input, output, session) {
   # Call the main inputs module
-  create_inputs <- Create_MainInputsServer("create_inputs", bds_metrics)
+  create_inputs <- Create_MainInputsServer(
+    "create_inputs",
+    topic_indicator_full
+  )
 
   # Year range
   year_input <- YearRangeServer(

02_dev/la_level_page/la_dev_app_mod.R

@@ -66,7 +66,6 @@ server_mod <- function(input, output, session) {
   app_inputs <- appInputsServer(
     "la_inputs",
     shared_values,
-    bds_metrics,
     metrics_raw
   )