dfe-analytical-services · cjrace · Jan 16, 2025 · Dec 31, 2024 · Dec 31, 2024 · Dec 31, 2024
diff --git a/.Rbuildignore b/.Rbuildignore
@@ -11,3 +11,4 @@
 ^data-raw$
 ^doc$
 ^Meta$
+^cran-comments\.md$
diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,20 +1,22 @@
 Type: Package
 Package: dfeR
-Title: Common DfE R tasks
-Version: 0.6.1.9000
+Title: Common Department for Education Analysis Tasks
+Version: 1.0.1
 Authors@R: c(
     person("Cam", "Race", , "[email protected]", role = c("aut", "cre")),
+    person("Department for Education, England", , , "[email protected]", role = "cph"),
     person("Laura", "Selby", , "[email protected]", role = "aut"),
     person("Adam", "Robinson", role = "aut"),
     person("Jen", "Machin", , "[email protected]", role = "ctb"),
     person("Jake", "Tufts", , "[email protected]", role = "ctb"),
     person("Rich", "Bielby", , "[email protected]", role = "ctb",
            comment = c(ORCID = "0000-0001-9070-9969")),
-    person("Menna", "Zayed", , "[email protected]", role = "ctb")
+    person("Menna", "Zayed", , "[email protected]", role = "ctb"),
+    person("Lauren", "Snaathorst", , "[email protected]", role = "ctb")
   )
-Description: This package contains R functions to allow DfE analysts to
-    re-use code for common analytical tasks that are undertaken across the
-    Department.
+Description: Preferred methods for common analytical tasks that are
+    undertaken across the Department, including number formatting, project
+    templates and curated reference data.
 License: GPL (>= 3)
 URL: https://dfe-analytical-services.github.io/dfeR/,
     https://github.com/dfe-analytical-services/dfeR

diff --git a/NEWS.md b/NEWS.md
@@ -1,6 +1,11 @@
-# dfeR (development version)
+# dfeR 1.0.1
 
-Added lookup data geog_time_identifiers
+Fix the spacing and printing of the z_replace() warning message, updating the eesyapi URL in the README and removed extraneous package tests.
+
+# dfeR 1.0.0
+
+Initial CRAN release.
+Added lookup data geog_time_identifiers.
 Added z_replace() to replace NA values in tables except for ones in geography and time columns that match ones in geog_time_identifiers. 
 
 # dfeR 0.6.1

diff --git a/R/create_project.R b/R/create_project.R
@@ -77,7 +77,7 @@ create_project <- function(
       "call those functions, run\n",
       "# `source('R/helper_functions.R')` at the start of your ",
       "script.\n\n",
-      "print('Your scripts and functions should be in ",
+      "message('Your scripts and functions should be in ",
       "the R folder.')"
     )
   )
@@ -175,7 +175,10 @@ create_project <- function(
 
 
   # Create the readme -----
-  file.copy("README_template.md", file.path(path, "README.md"))
+  file.copy(
+    system.file(package = "dfeR", "README_template.md"),
+    file.path(path, "README.md")
+  )
 
   # .renvignore
   file.create(paste0(path, "/.renvignore"))
@@ -242,8 +245,6 @@ create_project <- function(
     )
   }
 
-
-
   # Create a .Rprofile with a custom welcome message
   if (!file.exists(paste0(path, "/.Rprofile"))) {
     file.create(paste0(path, "/.Rprofile"))
@@ -267,13 +268,9 @@ create_project <- function(
   )
   writeLines(rprofile_content, paste0(path, "/.Rprofile"))
 
-
-
-
-
   # Successful project creation message (or delete project if fails)
   if (successful_creation) {
-    cat(
+    message(
       paste0(
         "\n\n",
         "****************************************************************\n",

diff --git a/R/datasets_documentation.R b/R/datasets_documentation.R
@@ -114,5 +114,5 @@
 #' @format ## `geog_time_identifiers`
 #' A character vector with 38 potential column names in snake case format.
 #' @source curated by explore.statistics@@education.gov.uk.
-#' \href{https://shorturl.at/j4532}{Get guidance on time and geography data.}
+#' \href{https://www.shorturl.at/j4532}{Guidance on time and geography data.}
 "geog_time_identifiers"
diff --git a/R/datasets_utils.R b/R/datasets_utils.R
@@ -19,6 +19,7 @@
 #' data frame from R memory
 #'
 #' @keywords internal
+#' @noRd
 #' @return a data frame of a tidied lookup file
 tidy_raw_lookup <- function(raw_lookup_file) {
   if (!is.data.frame(raw_lookup_file)) {
@@ -142,6 +143,7 @@ tidy_raw_lookup <- function(raw_lookup_file) {
 #' usually the output of tidy_raw_lookup
 #'
 #' @return single data.frame of all lookup files combined
+#' @noRd
 create_time_series_lookup <- function(lookups_list) {
   # Input validation ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
   # Added some quick checks based on the assumptions we make in this function
@@ -234,6 +236,7 @@ create_time_series_lookup <- function(lookups_list) {
 #' @return data.frame for the individual year of the lookup
 #'
 #' @keywords internal
+#' @noRd
 get_wd_pcon_lad_la <- function(year) {
   # Crude way to grab 2 digits, works for anything that isn't in the noughties
   year_end <- year %% 100
@@ -304,6 +307,7 @@ get_wd_pcon_lad_la <- function(year) {
 #' @return data.frame for the individual year of the lookup
 #'
 #' @keywords internal
+#' @noRd
 get_lad_region <- function(year) {
   # Crude way to grab 2 digits, works for anything that isn't in the noughties
   year_end <- year %% 100

diff --git a/R/fetch_utils.R b/R/fetch_utils.R
@@ -5,6 +5,7 @@
 #'
 #' @return nothing, unless a failure, and then it will give an error
 #' @keywords internal
+#' @noRd
 check_fetch_location_inputs <- function(year_input, country_input) {
   if (year_input != "All") {
     if (!grepl("^\\d{4}$", as.character(year_input))) {
@@ -39,6 +40,7 @@ check_fetch_location_inputs <- function(year_input, country_input) {
 #'
 #' @return a data frame of location names and codes
 #' @keywords internal
+#' @noRd
 fetch_locations <- function(lookup_data, cols, year, countries) {
   # Return only the cols we specified
   # We know their position from the dplyr selection of the lookup

diff --git a/R/get_ons_api_data.R b/R/get_ons_api_data.R
@@ -22,7 +22,7 @@
 #' Geography Portal
 #' @param query_params query parameters to pass into the API, see the ESRI
 #' documentation for more information on query parameters -
-#' \href{https://shorturl.at/5xrJT}{ESRI Query (Feature Service/Layer)}
+#' \href{https://www.shorturl.at/5xrJT}{ESRI Query (Feature Service/Layer)}
 #' @param batch_size the number of rows per query. This is 250 by default, if
 #' you hit errors then try lowering this. The API has a limit of 1000 to 2000
 #' rows per query, and in truth, the actual limit for our method is lower as
@@ -36,17 +36,19 @@
 #' @return parsed data.frame of geographic names and codes
 #'
 #' @examples
-#' if (interactive()) {
-#'   # Specify some parameters
-#'   get_ons_api_data(
-#'     data_id = "LAD23_RGN23_EN_LU",
-#'     query_params =
-#'       list(outFields = "column1, column2", outSR = "4326", f = "json")
-#'   )
+#' # Fetch everything from a data set
+#' dfeR::get_ons_api_data(data_id = "LAD23_RGN23_EN_LU")
 #'
-#'   # Just fetch everything
-#'   get_ons_api_data(data_id = "LAD23_RGN23_EN_LU")
-#' }
+#' # Specify the columns you want
+#' dfeR::get_ons_api_data(
+#'   "RGN_DEC_2023_EN_NC",
+#'   query_params = list(
+#'     where = "1=1",
+#'     outFields = "RGN23CD,RGN23NM",
+#'     outSR = 4326,
+#'     f = "json"
+#'   )
+#' )
 get_ons_api_data <- function(data_id,
                              query_params =
                                list(

diff --git a/R/toggle_message.R b/R/toggle_message.R
@@ -10,6 +10,8 @@
 #' @param verbose logical, usually a variable passed from the function you are
 #' using this within
 #'
+#' @return No return value, called for side effects
+#'
 #' @export
 #'
 #' @examples

diff --git a/R/z_replace.R b/R/z_replace.R
@@ -3,7 +3,7 @@
 #' @description
 #' Replaces `NA` values in tables except for ones in time and geography
 #' columns that must be included in DfE official statistics.
-#' \href{https://shorturl.at/chy76}{Get more guidance on Open Data Standards.}
+#' \href{https://www.shorturl.at/chy76}{Guidance on our Open Data Standards.}
 #'
 #' @details
 
@@ -87,7 +87,7 @@ z_replace <- function(data,
     stop(
       "Your table has geography and/or time column(s) that are not ",
       "in snake_case.\nPlease amend your column names to match the formatting",
-      "to dfeR::geog_time_identifiers."
+      " of dfeR::geog_time_identifiers."
     )
   }
 

diff --git a/README.Rmd b/README.Rmd
@@ -13,7 +13,7 @@ knitr::opts_chunk$set(
 )
 ```
 
-# dfeR <a href="http://dfe-analytical-services.github.io/dfeR/"><img src="man/figures/logo.png" align="right" height="138" /></a>
+# dfeR <a href="https://dfe-analytical-services.github.io/dfeR/"><img src="man/figures/logo.png" align="right" height="138" /></a>
 
 <!-- badges: start -->
 [![R-CMD-check](https://github.com/dfe-analytical-services/dfeR/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/dfe-analytical-services/dfeR/actions/workflows/R-CMD-check.yaml)
@@ -38,13 +38,13 @@ Functionality for dfeR is expected to focus around the following:
 4. API wrappers commonly needed in DfE analysis (where they don't have their own separate package)
 5. Geography lookup files and helper functions
 
-Documentation for what has been included in the package so far is on our [pkgdown site](http://dfe-analytical-services.github.io/dfeR/).
+Documentation for what has been included in the package so far is on our [pkgdown site](https://dfe-analytical-services.github.io/dfeR/).
 
 ### Relevant other packages
 
 We also maintain the [dfeshiny](https://github.com/dfe-analytical-services/dfeshiny) package, and expect any functions specific to R Shiny applications will live there.
 
-For connecting to data in the [explore education statistics](https://explore-education-statistics.service.gov.uk/), we are building the [eesyapi](https://github.com/dfe-analytical-services/eesyapi) package. 
+For connecting to data in the [explore education statistics](https://explore-education-statistics.service.gov.uk/), we are building the [eesyapi](https://github.com/dfe-analytical-services/eesyapi.R) package. 
 
 There is a [giasr](https://github.com/dfe-analytical-services/giasr) package, which has been developed for connecting to data in the [get information about schools service](https://get-information-schools.service.gov.uk/).
 
@@ -54,7 +54,13 @@ While we have some DfE specific data in the dfeR package taken from the [Open Ge
 
 ## Installation
 
-dfeR is not currently available on CRAN. For the time being you can install the development version from GitHub.
+dfeR is available on CRAN and you can install directly from there:
+
+``` r
+install.packages("dfeR")
+```
+
+You can install the development version from GitHub.
 
 If you are using [renv](https://rstudio.github.io/renv/articles/renv.html) in your project (recommended):
 
@@ -73,7 +79,7 @@ devtools::install_github("dfe-analytical-services/dfeR")
 
 ## Proxy
 
-The need for setting proxy settings in order to be able to work with R and Git within the DfE estate has now ended. If you previously run the proxy script in previous versions of the dfeR package, then contact the [Statistics Development Team]([email protected]) to assist in cleaning out your system settings.
+The need for setting proxy settings in order to be able to work with R and Git within the DfE estate has now ended. If you previously run the proxy script in previous versions of the dfeR package, then contact the [Statistics Development Team](mailto:[email protected]) to assist in cleaning out your system settings.
 
 ---
-Original file line number
+Diff line change
@@ Expand Up / @@ -11,3 +11,4 @@ @@
     ^data-raw$
     ^doc$
     ^Meta$
+    ^cran-comments\.md$