diff --git a/.Rbuildignore b/.Rbuildignore
index e8fd69d..b0c77d4 100644
--- a/.Rbuildignore
+++ b/.Rbuildignore
@@ -11,3 +11,4 @@
 ^\.github$
 .*\.xlsx$
 .*\.code-workspace$
+^\.lintr$
diff --git a/.lintr b/.lintr
new file mode 100644
index 0000000..6608207
--- /dev/null
+++ b/.lintr
@@ -0,0 +1,10 @@
+linters: linters_with_defaults(
+    commented_code_linter = NULL,
+    indentation_linter = NULL
+  ) # see vignette("lintr")
+encoding: "UTF-8"
+exclusions: list(
+    "vignettes/get_started.Rmd",
+    "vignettes/multiple_reports.Rmd",
+    "inst/Rmd/Report.Rmd"
+  )
diff --git a/DESCRIPTION b/DESCRIPTION
index 3a25cc4..09c8570 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
 Package: SPCreporter
 Title: Creates Metric Reports using Statistical Process Control in the NHS style
-Version: 0.2.0.9004
+Version: 0.2.0.9005
 Authors@R: c(
     person("Tom", "Smith",, "tomsmith_uk@hotmail.com", role = c("aut", "cre")),
     person("Fran", "Barton",, "fbarton@alwaysdata.net", role = "aut"))
@@ -15,7 +15,7 @@ Description: Takes a dataset file and a configuration file to produce an HTML
 License: MIT + file LICENSE
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.3.1
+RoxygenNote: 7.3.2
 URL: https://github.com/ThomUK/SPCreporter,
     https://thomuk.github.io/SPCreporter/
 BugReports: https://github.com/ThomUK/SPCreporter/issues
diff --git a/NAMESPACE b/NAMESPACE
index a78c8f4..2695ea0 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -10,6 +10,7 @@ importFrom(dplyr,pick)
 importFrom(ggplot2,aes)
 importFrom(glue,glue)
 importFrom(lubridate,days)
+importFrom(rlang,"%||%")
 importFrom(rlang,":=")
 importFrom(rlang,.data)
 importFrom(tidyselect,all_of)
diff --git a/R/SPCreporter-package.R b/R/SPCreporter-package.R
index d7222a7..5bfaafa 100644
--- a/R/SPCreporter-package.R
+++ b/R/SPCreporter-package.R
@@ -7,7 +7,7 @@
 #' @importFrom ggplot2 aes
 #' @importFrom glue glue
 #' @importFrom lubridate days
-#' @importFrom rlang := .data
+#' @importFrom rlang := %||% .data
 #' @importFrom tidyselect all_of any_of everything
 #' @importFrom utils head tail
 ## usethis namespace: end
diff --git a/R/checking_functions.R b/R/checking_functions.R
index 95eb730..f9d8c59 100644
--- a/R/checking_functions.R
+++ b/R/checking_functions.R
@@ -1,18 +1,19 @@
 #' Check the incoming measure data and transform as needed
 #'
-#' @param measure_data list. A list of data frames containing a combination of aggregated data and event data
+#' @param measure_data list. A list of data frames containing a combination of
+#'  aggregated data and event data
 #'
 #' @returns The input list of data frames, after checking for necessary columns
 #' @noRd
 check_measure_data <- function(measure_data) {
-  assertthat::assert_that(
+  assert_that(
     inherits(measure_data, "list"),
     msg = "check_measure_data: The data must be a list."
   )
 
   measure_data <- rlang::set_names(measure_data, tolower)
 
-  assertthat::assert_that(
+  assert_that(
     any(c("week", "month") %in% names(measure_data)),
     msg = paste0(
       "check_measure_data: ",
@@ -30,10 +31,9 @@ check_measure_data <- function(measure_data) {
     )
   measure_data |>
     purrr::keep_at(allowed_names) |>
-    purrr::iwalk(
-      \(x, nm) check_for_required_columns(
-        x, nm, required_columns = c("ref", "measure_name"))
-    ) |>
+    purrr::iwalk(\(x, nm) {
+      check_for_required_columns(x, nm, c("ref", "measure_name"))
+    }) |>
     purrr::map(\(x) dplyr::mutate(x, across("ref", as.character)))
 }
 
@@ -49,24 +49,23 @@ check_measure_data <- function(measure_data) {
 #' @returns The input list of data frames, after checking for necessary columns
 #' @noRd
 check_a_data <- function(a_data) {
-  assertthat::assert_that(
+  assert_that(
     inherits(a_data, "list"),
     msg = "check_measure_data: The data must be a list."
   )
 
-  # We now only retain data frames from the list if they have a name
-  # matching one of the allowed aggregation levels. We then check that each
-  # data frame has the required columns and the 'ref' column is a character type
+  # We now only retain data frames from the list if they have a name matching
+  # one of the allowed aggregation levels. We then check that each data frame
+  # has the required columns and the 'ref' column is a character type.
   allowed_names <- c(
     "day", "week", "month",
     "calendar_year", "financial_year"
     )
   a_data |>
     purrr::keep_at(allowed_names) |>
-    purrr::iwalk(
-      \(x, nm) check_for_required_columns(
-        x, nm, required_columns = c("ref", "measure_name", "comment"))
-    )
+    purrr::iwalk(\(x, nm) {
+      check_for_required_columns(x, nm, c("ref", "measure_name", "comment"))
+    })
 }
 
 
@@ -82,18 +81,18 @@ check_a_data <- function(a_data) {
 #' @noRd
 check_e_data <- function(e_data) {
 
-  if(is.null(e_data)) stop("The 'events' worksheet is missing from 'measure_data'.")
+  if (is.null(e_data)) {
+    stop("The 'events' worksheet is missing from 'measure_data'.")
+  }
 
-  assertthat::assert_that(
+  assert_that(
     inherits(e_data, "data.frame"),
     msg = "check_event_data: The data must be a data frame."
   )
 
-  e_data |>
-    check_for_required_columns(
-      "events",
-      required_columns = c("ref", "measure_name", "event_date_or_datetime")
-    ) |>
+  check_for_required_columns(
+    e_data, "events", c("ref", "measure_name", "event_date_or_datetime")
+  ) |>
     dplyr::mutate(across("ref", as.character))
 }
 
@@ -108,7 +107,7 @@ check_e_data <- function(e_data) {
 #' @returns The input data frame after some checks and transformations
 #' @noRd
 check_report_config <- function(report_config) {
-  assertthat::assert_that(
+  assert_that(
     inherits(report_config, "data.frame"),
     msg = "check_report_config: The report config must be a data frame."
   )
@@ -145,12 +144,12 @@ check_report_config <- function(report_config) {
 #' @returns The input data frame after some checks and transformations
 #' @noRd
 check_measure_config <- function(measure_config) {
-  assertthat::assert_that(
+  assert_that(
     inherits(measure_config, "data.frame"),
     msg = "check_measure_config: config_data must be a data frame"
   )
 
-  # check for column names, and provide a helpful error message if needed
+  # Check for column names, and provide a helpful error message if needed
   required_columns <- c(
     "ref",
     "measure_name",
@@ -174,19 +173,20 @@ check_measure_config <- function(measure_config) {
   )
 
   measure_config |>
-    # check required cols are present
+    # Check required cols are present
     check_for_required_columns("measure_config", required_columns) |>
     check_for_optional_columns(optional_columns) |>
     dplyr::select(c(all_of(required_columns), any_of(optional_columns))) |>
 
     dplyr::mutate(
-      # default all cols to character (empty cols are imported as logical NAs)
+      # Default all cols to character (empty cols are imported as logical NAs)
       across(everything(), as.character),
       across("unit", tolower),
       across("improvement_direction", tolower),
       # " marks in the comment mess up the render process later
       across("rebase_comment", \(x) stringr::str_replace_all(x, "\\\"", "'")),
-      # target and allowable_days_lag are the only cols that should end up numeric
+      # `target` and `allowable_days_lag` are the only cols that should
+      # end up as numeric.
       across("target", \(x) as.numeric(dplyr::na_if(x, "-"))),
       across("allowable_days_lag", \(x) as.integer(tidyr::replace_na(x, "0")))
     )
@@ -207,7 +207,7 @@ check_measure_config <- function(measure_config) {
 #' @noRd
 check_measure_names <- function(ref_no, measure_data, measure_config) {
   # check that the config table includes this ref_no number
-  assertthat::assert_that(
+  assert_that(
     ref_no %in% measure_config[["ref"]],
     msg = glue(
       "check_measure_names: ",
@@ -215,7 +215,7 @@ check_measure_names <- function(ref_no, measure_data, measure_config) {
       "data frame.")
   )
 
-  # find the titles to compare
+  # Find the titles to compare
   m_titles <- measure_data |>
     dplyr::filter(if_any("ref", \(x) x == ref_no)) |>
     dplyr::pull("measure_name") |>
@@ -225,7 +225,7 @@ check_measure_names <- function(ref_no, measure_data, measure_config) {
     dplyr::pull("measure_name") |>
     unique()
 
-  assertthat::assert_that(
+  assert_that(
     length(c_title) == 1,
     msg = glue(
       "check_measure_names: ",
@@ -234,16 +234,22 @@ check_measure_names <- function(ref_no, measure_data, measure_config) {
       )
     )
 
-  # warn when the titles don't match
+  # Warn when the titles don't match
   m_titles |>
-    purrr::walk(
-      \(x) ifelse(
+    purrr::walk(\(x) {
+      ifelse(
         x == c_title,
         usethis::ui_silence(TRUE),
-        usethis::ui_warn(
-          c("check_measure_names: There is a name mismatch for measure ref: {ref_no}. The title in the data bundle is '{x}'. The title in the measure config is '{c_title}'.")
-      )))
-
+        usethis::ui_warn(c(
+          paste0(
+            "check_measure_names: There is a name mismatch for measure ref: ",
+            "{ref_no}."
+          ),
+          "The title in the data bundle is '{x}'.",
+          "The title in the measure config is '{c_title}'."
+        ))
+      )
+    })
   invisible(TRUE)
 }
 
@@ -266,14 +272,17 @@ check_for_required_columns <- function(.data, df_name, required_columns) {
   missing_columns <- setdiff(required_columns, names(.data))
 
   if (length(missing_columns)) {
-    # find the name of the first missing col for the error message
-    first_missing_column <- missing_columns[1]
-
-    # throw the error
-    usethis::ui_stop(
-      "check_for_required_columns: Column '{first_missing_column}' is missing from the '{df_name}' data frame. Check for typos in the column names."
-    )
-  } else .data
+    # Find the name of the first missing col for the error message
+    first_missing_column <- missing_columns[1] # nolint
+
+    # Throw the error
+    usethis::ui_stop(paste0(
+      "check_for_required_columns: Column '{first_missing_column}' is missing ",
+      "from the '{df_name}' data frame. Check for typos in the column names."
+    ))
+  } else {
+    .data
+  }
 }
 
 
@@ -293,19 +302,20 @@ check_for_optional_columns <- function(.data, optional_columns) {
   missing_columns <- setdiff(optional_columns, names(.data))
   if (length(missing_columns)) {
     # find the name of the first missing col for the console message
-    first_missing_column <- missing_columns[1]
+    first_missing_column <- missing_columns[1] # nolint
+
+    usethis::ui_info(paste0(
+      "check_for_optional_columns: Optional column '{first_missing_column}' ",
+      "is missing. Adding it."
+    ))
 
-    usethis::ui_info(
-      c(
-        "check_for_optional_columns: Optional column '{first_missing_column}' is missing. Adding it."
-      )
-    )
     missing_columns |>
-      purrr::reduce(
-        \(x, y) tibble::add_column(x, {{y}} := NA_character_),
-        .init = .data
-      )
-  } else .data
+      purrr::reduce(\(x, y) {
+        tibble::add_column(x, {{y}} := NA_character_)
+      }, .init = .data)
+  } else {
+    .data
+  }
 }
 
 
@@ -316,28 +326,28 @@ check_for_optional_columns <- function(.data, optional_columns) {
 
 #' Check all required data items are provided
 #'
-#' @param report_config A data frame. The report config detailing required report items
+#' @param report_config A data frame. The report config detailing required
+#'  report items
 #' @param measure_data Data frame in wide format
 #'
 #' @returns logical TRUE if check is successful, else an error message
 check_dataset_is_complete <- function(report_config, measure_data) {
 
   missing_data <- report_config |>
-    dplyr::select(all_of(c("ref", "measure_name", "aggregation"))) |>
+    dplyr::select(c("ref", "measure_name", "aggregation")) |>
     dplyr::anti_join(measure_data, by = c("ref", "aggregation"))
 
-
-  # build an error message if there are missing data items
-  assertthat::assert_that(
+  # Build an error message if there are missing data items
+  assert_that(
     nrow(missing_data) == 0,
     msg = usethis::ui_stop(
-      dplyr::slice(missing_data, 1) |>
-        stringr::str_glue_data(
-          "check_dataset_is_complete: ",
-          "Data is missing for {nrow(missing_data)} report items. ",
-          "The first is ref {ref}, '{measure_name}', aggregation: {aggregation}."
-          )
-      ))
-
+      glue::glue_data(
+        dplyr::slice(missing_data, 1),
+        "check_dataset_is_complete: ",
+        "Data is missing for {nrow(missing_data)} report items. ",
+        "The first is ref {ref}, '{measure_name}', aggregation: {aggregation}"
+      )
+    )
+  )
   invisible(TRUE)
 }
diff --git a/R/helper_functions.R b/R/helper_functions.R
index cf44d85..2dd1e33 100644
--- a/R/helper_functions.R
+++ b/R/helper_functions.R
@@ -2,23 +2,31 @@
 #'
 #' @param .data data frame. Data frame in wide format
 #'
-#' @returns data frame. Data frame in long format
+#' @returns A data frame in long format
 #' @noRd
 lengthen_measure_data <- function(.data) {
-  assertthat::assert_that(
+  assert_that(
     inherits(.data, "data.frame"),
     msg = "lengthen_measure_data: The data must be a data frame."
   )
 
   # Should match date strings of the form 2022-06-01
-  ymd_regex <- "^20[0-9]{2}-[0-9]{1,2}-[0-9]{1,2}$"
-  init_cols <- c("aggregation", "measure_prefix", "ref", "measure_name", "comment")
+  ymd_rx <- "^20[0-9]{2}-[0-9]{1,2}-[0-9]{1,2}$"
+  init_cols <- c(
+    "aggregation",
+    "measure_prefix",
+    "ref",
+    "measure_name",
+    "comment"
+  )
 
-  assertthat::assert_that(
+  assert_that(
     all(purrr::map_lgl(
-      names(.data), \(x) x %in% init_cols |
+      names(.data), \(x) {
+        x %in% init_cols |
         stringr::str_detect(x, "^[0-9]{5}$") |
-        stringr::str_detect(x, ymd_regex)
+        stringr::str_detect(x, ymd_rx)
+      }
     )),
     msg = usethis::ui_stop(
       paste(
@@ -27,27 +35,24 @@ lengthen_measure_data <- function(.data) {
         stringr::str_flatten_comma(paste0("'", init_cols, "'")),
         "and valid date formats.",
         "One invalid column name found is:",
-        head(
-          stringr::str_subset(
-            setdiff(names(.data), init_cols),
-            stringr::str_glue("^[0-9]{5}$|{ymd_regex}"),
-            negate = TRUE
-          ),
-          1
-        ),
+        head(stringr::str_subset(
+          setdiff(names(.data), init_cols), glue("^[0-9]{5}$|{ymd_rx}"), TRUE
+        ), 1),
         collapse = " "
       )
     )
   )
 
-  # pivot incoming measure_data from wide to long,
-  # and convert date column to date format
+  # Pivot incoming measure_data from wide to long, and convert date column
+  # to date format.
   .data |>
-    tidyr::pivot_longer(!any_of(init_cols), names_to = "date", values_drop_na = TRUE) |>
+    tidyr::pivot_longer(
+      !any_of(init_cols), names_to = "date", values_drop_na = TRUE
+    ) |>
     dplyr::mutate(across("date", quietly_convert_date)) |>
     # Sort data from oldest to latest by measure - it should already be sorted
-    # (pivot_longer draws from L-R wide data)... but let's make sure
-    dplyr::arrange(across(all_of(c("ref", "date"))))
+    # (pivot_longer draws from L-R wide data)... but let's make sure.
+    dplyr::arrange(pick(c("ref", "date")))
 }
 
 
@@ -64,13 +69,13 @@ lengthen_measure_data <- function(.data) {
 #' @returns A character string suitable for inclusion in the report
 #' @noRd
 get_target_text <- function(target, improvement_direction, unit) {
-  imp_dir <- tolower(improvement_direction)
+  imp_dir <- tolower(improvement_direction) # nolint
 
-  string <- dplyr::case_when(
+  string <- dplyr::case_when( # nolint
     is.na(target) ~ "-",
     imp_dir == "neutral" ~ "Neutral",
     unit == "%" ~ paste0(round(target * 100, 1), "%"),
-    TRUE ~ as.character(round(target, 2)) # covers decimal and integer
+    .default = as.character(round(target, 2)) # covers decimal and integer
   )
 
   dplyr::case_when(
@@ -80,7 +85,7 @@ get_target_text <- function(target, improvement_direction, unit) {
     !is.na(target) & imp_dir == "decrease" ~ paste0("\u2264 ", string),
     # \u2265 is: ≥
     !is.na(target) & imp_dir == "increase" ~ paste0("\u2265 ", string),
-    TRUE ~ string
+    .default = string
   )
 }
 
@@ -96,7 +101,6 @@ get_target_text <- function(target, improvement_direction, unit) {
 #' @param aggregation string. e.g. "month"
 #'
 #' @returns A date in "%d-%b-%Y" (day-month-year) format
-#'
 #' @noRd
 get_updatedto_text <- function(last_date, aggregation) {
   assert_that(
@@ -108,7 +112,7 @@ get_updatedto_text <- function(last_date, aggregation) {
     msg = "get_updatedto_text: Multiple values for `aggregation` provided"
   )
 
-  last_date <- as.Date(last_date) # handles dttm being passed in by mistake
+  last_date <- as.Date(last_date) # Handles dttm being passed in by mistake
 
   # Rename "calendar_year" and "none" aggregations to work with ceiling_date()
   agg <- dplyr::case_when(
@@ -118,7 +122,7 @@ get_updatedto_text <- function(last_date, aggregation) {
     .default = aggregation
   )
 
-  # allowed values
+  # Allowed values
   assert_that(
     all(agg %in% c("day", "week", "month", "year")),
     msg = glue("get_updatedto_text: invalid aggregation ({agg}) provided")
@@ -141,7 +145,7 @@ get_updatedto_text <- function(last_date, aggregation) {
 
 # This function generates warnings due to the way if_else works with dates
 # We will wrap it in a quietly adverb to handle the warnings, which are not
-# warnings we need to worry about
+# warnings we need to worry about.
 convert_date <- function(x) {
   ymd_regex <- "^20[0-9]{2}-[0-9]{1,2}-[0-9]{1,2}$"
   if_else(
@@ -158,9 +162,10 @@ quietly_convert_date <- function(...) {
 
 
 #' Parse rebase dates
+#'
 #' Parse dates from the config spreadsheet into a format suitable for use in
-#' the SPC calculation function. Only needed as a helper function for
-#' `align_rebase_dates()`
+#'  the SPC calculation function. Only needed as a helper function for
+#'  `align_rebase_dates()`
 #'
 #' @param input character. A vector of length 1, containing quoted dates in ymd
 #' format, separated with commas eg '"2020-01-01", "2020-03-05"'
@@ -171,14 +176,14 @@ parse_rebase_dates <- function(input) {
   if (is.na(input)) {
     NULL
   } else {
-    # parse into individual character strings
+    # Parse into individual character strings
     vector <- input |>
       stringr::str_split_1("\\s*,\\s*") |>
-      stringr::str_remove_all("\\\"") |> # remove internal quotes
-      stringr::str_trim() # trim white space
+      stringr::str_remove_all("\\\"") |> # Remove internal quotes
+      stringr::str_trim() # Trim white space
 
-    # wrap the date parsing in tryCatch() to stop()
-    # if excel dates are not perfectly formed.
+    # Wrap the date parsing in tryCatch() to stop() if excel dates are not
+    # properly formed.
     tryCatch(
       lubridate::ymd(vector),
       error = function(c) stop("error in parse_rebase_dates: ", c),
@@ -235,10 +240,10 @@ align_rebase_dates <- function(input, measure_data) {
 #' @returns string. Name of the assurance type
 #' @noRd
 get_assurance_type <- function(spc, improvement_direction) {
-  imp_dir <- tolower(improvement_direction)
-  upl <- spc[["upl"]][1]
-  lpl <- spc[["lpl"]][1]
-  target <- spc[["target"]][1]
+  imp_dir <- tolower(improvement_direction) # nolint
+  upl <- spc[["upl"]][1] # nolint
+  lpl <- spc[["lpl"]][1] # nolint
+  target <- spc[["target"]][1] # nolint
 
   a <- dplyr::case_when(
     imp_dir == "neutral" ~ "Neutral",
@@ -248,7 +253,7 @@ get_assurance_type <- function(spc, improvement_direction) {
     upl < target & imp_dir == "decrease" ~ "PASS_TARG",
     lpl > target & imp_dir == "decrease" ~ "FAIL_TARG",
     upl < target & imp_dir == "increase" ~ "FAIL_TARG",
-    TRUE ~ ""
+    .default = ""
   )
 
   if (a == "") {
@@ -265,15 +270,13 @@ get_assurance_type <- function(spc, improvement_direction) {
 #' @param spc data frame. As returned from the {NHSRplotthedots} SPC package
 #' @param improvement_direction string. "Increase", "Decrease", or "Neutral"
 #'
-#' @return string. Name of the variation type
+#' @returns string. Name of the variation type
 #' @noRd
 #'
 get_variation_type <- function(spc, improvement_direction) {
-  vari <- tail(spc[["point_type"]], 1)
-  relative_to_mean <- tail(spc[["relative_to_mean"]], 1)
-  # need to provide a default value so the case_when works
-  if (is.null(relative_to_mean)) relative_to_mean <- 0
-  imp_dir <- tolower(improvement_direction)
+  vari <- tail(spc[["point_type"]], 1) # nolint
+  relative_to_mean <- tail(spc[["relative_to_mean"]], 1) %||% 0 # nolint
+  imp_dir <- tolower(improvement_direction) # nolint
 
   v <- dplyr::case_when(
     vari == "common_cause" ~ "CC",
@@ -282,10 +285,10 @@ get_variation_type <- function(spc, improvement_direction) {
     vari == "special_cause_concern" & imp_dir == "increase" ~ "SC_LO_CON",
     vari == "special_cause_concern" & imp_dir == "decrease" ~ "SC_HI_CON",
     vari == "special_cause_neutral" & relative_to_mean == -1 ~ "SC_LO_NEUTRAL",
-    vari == "special_cause_neutral" & relative_to_mean %in% c(1, 0) ~ "SC_HI_NEUTRAL",
+    vari == "special_cause_neutral" & relative_to_mean %in% c(1, 0) ~ "SC_HI_NEUTRAL", # nolint
     vari == "special_cause_neutral_low" ~ "SC_LO_NEUTRAL",
     vari == "special_cause_neutral_high" ~ "SC_HI_NEUTRAL",
-    TRUE ~ ""
+    .default = ""
   )
 
   if (v == "") {
@@ -317,25 +320,33 @@ get_variation_type <- function(spc, improvement_direction) {
 calculate_stale_data <- function(updated_to, lag, cutoff_dttm) {
   updated_to <- tryCatch(
     lubridate::dmy(updated_to),
-    warning = \(w) "calculate_stale_data: The updated_to date is not in the required '%d-%b-%Y' format."
+    warning = \(w) {
+      paste0(
+        "calculate_stale_data: The updated_to date is not in the required ",
+        "'%d-%b-%Y' format."
+      )
+    }
   )
 
-  assertthat::assert_that(
+  assert_that(
     !any(is.na(updated_to)),
     all(inherits(updated_to, "Date")),
-    msg = "calculate_stale_data: Unable to convert the updated_to argument text to a valid date."
+    msg = paste0(
+      "calculate_stale_data: Unable to convert the updated_to argument ",
+      "text to a valid date."
+    )
   )
 
-  assertthat::assert_that(
+  assert_that(
     all(lag %% 1 == 0),
     msg = "calculate_stale_data: The lag argument must be an integer."
   )
 
-  assertthat::assert_that(
+  assert_that(
     all(inherits(cutoff_dttm, "POSIXct")),
     msg = "calculate_stale_data: The cutoff_dttm argument must be a POSIXct."
   )
 
-  lag <- lubridate::days(lag) + lubridate::hms("23:59:59") # convert to a period
+  lag <- days(lag) + lubridate::hms("23:59:59") # Convert to a period
   if_else((updated_to + lag) < cutoff_dttm, "stale", "fresh")
 }
diff --git a/R/process_event_data_t.R b/R/process_event_data_t.R
index aae9bb6..14e4355 100644
--- a/R/process_event_data_t.R
+++ b/R/process_event_data_t.R
@@ -1,34 +1,42 @@
 #' Process event data into a time-between data frame
 #'
 #' @param event_data data frame. Raw event data
-#' @param data_cutoff_dttm POSIXct. The data cutoff datetime used to calculate the final point position
+#' @param data_cutoff_dttm POSIXct. The data cutoff datetime used to calculate
+#'  the final point position
 #'
-#' @return data frame. A data frame with calculated dates and time-between information added
+#' @returns A data frame with calculated dates and time-between information
 #' @noRd
-process_event_data_t <- function(event_data, data_cutoff_dttm){
+process_event_data_t <- function(event_data, data_cutoff_dttm) {
 
-  if(nrow(event_data) == 0) return(NULL)
+  if (nrow(event_data) == 0) return(NULL)
 
-  processed_data <- event_data |>
-    dplyr::mutate(
-      aggregation = "none"
+  event_data |>
+    dplyr::mutate(aggregation = "none") |>
+    # Remove events after the cutoff time (should only happen for
+    # retrospective reports).
+    dplyr::filter(
+      if_any("event_date_or_datetime", \(x) x <= data_cutoff_dttm)
     ) |>
-    dplyr::filter(.data$event_date_or_datetime < data_cutoff_dttm) |> # remove events after the cutoff time (should only happen for retrospective reports)
-    dplyr::group_by(.data$ref) |>
-    dplyr::arrange(.data$event_date_or_datetime) |>
+    dplyr::group_by(pick("ref")) |>
+    dplyr::arrange(pick("event_date_or_datetime")) |>
 
-    # add the theoretical "today" event to each group
-    dplyr::group_modify(~ tibble::add_row(.x, event_date_or_datetime = data_cutoff_dttm)) |>
+    # Add the theoretical "today" event to each group
+    dplyr::group_modify(\(x, y) {
+      tibble::add_row(x, event_date_or_datetime = data_cutoff_dttm)
+    }) |>
 
-    # calculate the time between events, in days
+    # Calculate the time between events, in days
     dplyr::mutate(
-      time_between = difftime(.data$event_date_or_datetime, dplyr::lag(.data$event_date_or_datetime), units = "days"),
-      time_between = as.integer(.data$time_between),
+      time_between = as.integer(difftime(
+        .data[["event_date_or_datetime"]],
+        dplyr::lag(.data[["event_date_or_datetime"]]),
+        units = "days"
+      ))
     ) |>
-    dplyr::filter(!is.na(.data$time_between)) |>
+    dplyr::filter(if_any("time_between", \(x) !is.na(x))) |>
     dplyr::ungroup() |>
 
-    # fill in the gaps left by adding the "today" event
+    # Fill in the gaps left by adding the "today" event
     tidyr::fill("aggregation", "measure_name") |>
     dplyr::relocate("aggregation") |>
     dplyr::rename(
diff --git a/R/spcr_make_data_bundle.R b/R/spcr_make_data_bundle.R
index 826698e..50a5c9b 100644
--- a/R/spcr_make_data_bundle.R
+++ b/R/spcr_make_data_bundle.R
@@ -3,53 +3,57 @@
 #' @param measure_data list. List containing data frames of data in wide format
 #' @param report_config data frame. Config information for the report
 #' @param measure_config data frame. Config information for the measures
-#' @param data_cutoff_dttm POSIXct. The data cutoff date-time (the last date-time for data in the report eg. month-end)
+#' @param data_cutoff_dttm POSIXct. The data cutoff date-time (the last
+#'  date-time for data in the report eg. month-end)
 #'
-#' @returns data frame. A nested data frame containing source data for the report
+#' @returns data frame. A nested data frame containing source data for the
+#'  report
 #' @export
 spcr_make_data_bundle <- function(
     measure_data = test_measure_data,
     report_config = test_report_config,
     measure_config = test_measure_config,
     data_cutoff_dttm = Sys.time()) {
-  # check measure_data (list) columns and set `ref` column to character
+  # Check measure_data (list) columns and set `ref` column to character
   measure_data <- check_measure_data(measure_data)
-  # check report_config columns and set `ref` column to character
+  # Check report_config columns and set `ref` column to character
   report_config <- check_report_config(report_config)
-  # check measure_config columns and set `ref` column to character
+  # Check measure_config columns and set `ref` column to character
   measure_config <- check_measure_config(measure_config)
 
-  # measure data can contain two types of worksheet
-  # 1. a wide-format sheet containing aggregated counts, with dated columns (a_data)
-  # 2. a long-format sheet containing event-list data (e_data).
-  # separate them into a_data and e_data
+  # Measure data can contain two types of worksheet:
+  #   1. a wide-format sheet containing aggregated counts, with dated columns
+  #   (a_data)
+  #   2. a long-format sheet containing event-list data (e_data).
+  # Separate them into a_data and e_data:
   e_data <- measure_data |>
     purrr::pluck("events")
 
   a_data <- measure_data |>
     purrr::discard_at("events")
 
-  # a_data is closely related to the measure_data, but we use a different function to check it
+  # a_data is closely related to the measure_data, but we use a different
+  # function to check it.
   a_data <- check_a_data(a_data)
 
-  # check event_data columns and set `ref` column to character
+  # Check event_data columns and set `ref` column to character
   e_data <- check_e_data(e_data)
 
-  # process event data into time-between data
+  # Process event data into time-between data
   e_data_time_between <- process_event_data_t(e_data, data_cutoff_dttm)
 
-  # reduce measure_data list to a single data frame
+  # Reduce measure_data list to a single data frame
   a_data_df <- a_data |>
     dplyr::bind_rows(.id = "aggregation")
 
 
   # Create long version of the aggregated data, sorted by date (within each
-  # ref), and with the processed event data added to the end
+  # ref), and with the processed event data added to the end.
   measure_data_long <- a_data_df |>
     lengthen_measure_data() |>
     dplyr::bind_rows(e_data_time_between)
 
-  # check all required data is supplied
+  # Check all required data is supplied
   check_dataset_is_complete(report_config, measure_data_long)
 
   # Check reference numbers and measure names agree across both data frames.
@@ -61,17 +65,13 @@ spcr_make_data_bundle <- function(
 
   # measure_data in long format is joined on to the config files as a nested df
   # column. Then we mutate the data frame row by row, adding new variables and
-  # tidying up / formatting variables ready for reporting
+  # tidying up / formatting variables ready for reporting.
   nested_data <- report_config |>
-    # use measure names from report_config not from measure_config
+    # Use measure names from report_config not from measure_config
     dplyr::left_join(dplyr::select(measure_config, !"measure_name"), "ref") |>
-    dplyr::mutate(
-      across("measure_name",
-        \(x) if_else(
-          .data[["spc_chart_type"]] == "t", paste(x, "(time-between)"), x
-        )
-      )
-    ) |>
+    dplyr::mutate(across("measure_name", \(x) {
+      if_else(.data[["spc_chart_type"]] == "t", paste(x, "(time-between)"), x)
+    })) |>
     dplyr::nest_join(
       measure_data_long,
       by = c("ref", "aggregation"),
@@ -80,57 +80,55 @@ spcr_make_data_bundle <- function(
     # Pull most recent date from each data frame in the measure_data column
     dplyr::mutate(
       data_cutoff_dttm = as.POSIXct(data_cutoff_dttm),
-      last_date = purrr::map_vec(.data[["measure_data"]], \(x) max(x[["date"]], na.rm = TRUE)),
-      # pull most recent data point from each df in the measure_data column
+      last_date = purrr::map_vec(.data[["measure_data"]], \(x) {
+        max(x[["date"]], na.rm = TRUE)
+      }),
+      # Pull most recent data point from each df in the measure_data column
       last_data_point = purrr::map_vec(.data[["measure_data"]], \(x) {
         dplyr::slice_max(x, order_by = x[["date"]], n = 1)[["value"]]
       })
     )
 
   # Check that measure data that is supposed to be integer data is supplied as
-  # such, or raise a warning message
-  nested_data |>
-    dplyr::filter(if_any("unit", \(x) x == "integer")) |>
-    tidyr::hoist("measure_data", "value") |>
-    dplyr::select(all_of(c(x = "value", y = "ref"))) |>
-    purrr::pwalk(\(x, y) if (any(round(x) != x)) {
-      warning(
-        glue(
-          "spcr_make_data_bundle: ",
-          "Measure {y} is configured as an integer, ",
-          "but has been supplied with decimal data."
-        )
-      )
-    })
+  # such, or raise a warning message.
+  if (any(nested_data[["unit"]] == "integer")) {
+    nested_data |>
+      dplyr::filter(if_any("unit", \(x) x == "integer")) |>
+      tidyr::hoist("measure_data", "value") |>
+      dplyr::select(c(x = "value", y = "ref")) |>
+      purrr::pwalk(\(x, y) {
+        if (any(round(x) != x)) {
+          warning(glue(
+            "spcr_make_data_bundle: Measure {y} is configured as an integer, ",
+            "but has been supplied with decimal data."
+          ))
+        }
+      })
+  }
 
   nested_data |>
     dplyr::mutate(
-      across(
-        "improvement_direction",
-        \(x) dplyr::case_when(
+      across("improvement_direction", \(x) {
+        dplyr::case_when(
           .data[["spc_chart_type"]] == "t" & x == "decrease" ~ "increase",
-          # a rather unlikely situation
+          # A rather unlikely situation
           .data[["spc_chart_type"]] == "t" & x == "increase" ~ "decrease",
-          TRUE ~ x
+          .default = x
         )
-      ),
-      across(
-        "unit",
-        \(x) if_else(.data[["spc_chart_type"]] == "t", "days", x)
-      ),
-      across(
-        "target",
-        \(x) if_else(.data[["spc_chart_type"]] == "t", NA, x)
-      ),
+      }),
+      across("unit", \(x) if_else(.data[["spc_chart_type"]] == "t", "days", x)),
+      across("target", \(x) if_else(.data[["spc_chart_type"]] == "t", NA, x)),
       across("target_set_by", \(x) if_else(is.na(x), "-", x)),
-      across("last_data_point", \(x) dplyr::case_when(
-        is.na(x) ~ NA_character_,
-        x == Inf ~ NA_character_,
-        unit == "%" ~ paste0(round(x * 100, 1), "%"),
-        unit == "decimal" ~ as.character(round(x, 2)),
-        unit == "days" ~ paste0(x, "d"),
-        TRUE ~ as.character(round(x))
-      ))
+      across("last_data_point", \(x) {
+        dplyr::case_when(
+          is.na(x) ~ NA_character_,
+          x == Inf ~ NA_character_,
+          unit == "%" ~ paste0(round(x * 100, 1), "%"),
+          unit == "decimal" ~ as.character(round(x, 2)),
+          unit == "days" ~ paste0(x, "d"),
+          .default = as.character(round(x))
+        )
+      })
     ) |>
     dplyr::mutate(
       target_text = get_target_text(
@@ -141,7 +139,7 @@ spcr_make_data_bundle <- function(
       updated_to = purrr::map2_chr(
         .data[["last_date"]],
         .data[["aggregation"]],
-        get_updatedto_text # use map2_chr as this doesn't handle vectors well
+        get_updatedto_text # Use map2_chr as this doesn't handle vectors well
       ),
       stale_data = calculate_stale_data(
         .data[["updated_to"]],
diff --git a/R/spcr_make_report.R b/R/spcr_make_report.R
index 3bb38fe..55d1179 100644
--- a/R/spcr_make_report.R
+++ b/R/spcr_make_report.R
@@ -1,24 +1,38 @@
 #' Make the SPC Report
 #'
-#' @param data_bundle data frame. The pre-processed bundle of information (ideally made with `spcr_make_data_bundle()`)
-#' @param report_title string. The report title, printed at the top of the report
+#' @param data_bundle data frame. The pre-processed bundle of information
+#'  (ideally made with `spcr_make_data_bundle()`)
+#' @param report_title string. The report title, printed at the top of the
+#'  report
 #' @param subtitle string. The report subtitle, printed at the top of the report
-#' @param document_title string. A title for the document, as used in the HTML `<title>` tag or as the PDF document title. If left as NULL (the default), this function will use the `report_title` parameter and the current date to construct a title
+#' @param document_title string. A title for the document, as used in the HTML
+#'  `<title>` tag or as the PDF document title. If left as NULL (the default),
+#'  this function will use the `report_title` parameter and the current date
+#'  to construct a title
 #' @param report_ref string. A unique reference for the report
 #' @param logo_path string. File path of the logo to be used on the report
-#' @param department string. A text suffix positioned underneath the logo, for eg. department name
+#' @param department string. A text label positioned underneath the logo,
+#'  for example the department name
 #' @param department_text_colour string. The colour of the department text
 #' @param intro string. Intro text printed at the head of the report
 #' @param author_name string. The author's name
 #' @param author_email string. The author's contact email address
-#' @param paper_colour string. Customise the background colour using a hex code, or CSS colour name
-#' @param accordion_colour string. Customise the accordion colour using a hex code, or CSS colour name
-#' @param stale_colour string. Customise the date lozenge to indicate that data is stale, using a hex code, or CSS colour name
-#' @param fresh_colour string. Customise the date lozenge to indicate that data is up to date, using a hex code, or CSS colour name
-#' @param output_directory string. The name of the directory in which to save the resulting report
-#' @param output_type vector. Specify what output types are needed.  Default is c("html", "csv"). "pdf" is also possible.
-#' @param include_dq_icon logical. Whether to include the data quality icon on the final report
-#' @param annotate_limits logical. Whether to add annotations to a secondary y axis for process limits and mean
+#' @param paper_colour string. Customise the background colour using a hex
+#'  code, or CSS colour name
+#' @param accordion_colour string. Customise the accordion colour using a hex
+#'  code, or CSS colour name
+#' @param stale_colour string. Customise the date lozenge to indicate that
+#'  data is stale, using a hex code, or CSS colour name
+#' @param fresh_colour string. Customise the date lozenge to indicate that
+#'  data is up to date, using a hex code, or CSS colour name
+#' @param output_directory string. The name of the directory in which to save
+#'  the resulting report
+#' @param output_type vector. Specify what output types are needed. The
+#'  default is c("html", "csv"). "pdf" is also possible.
+#' @param include_dq_icon logical. Whether to include the data quality icon
+#'  on the final report
+#' @param annotate_limits logical. Whether to add annotations to a
+#'  secondary y axis for process limits and mean
 #'
 #' @export
 spcr_make_report <- function(
@@ -45,35 +59,35 @@ spcr_make_report <- function(
   start_time <- Sys.time()
 
   # This dttm is the same for every row in the data bundle. The first will do.
-  data_cutoff_dttm <- data_bundle[["data_cutoff_dttm"]][[1]]
+  data_cutoff_dttm <- data_bundle[["data_cutoff_dttm"]][[1]] # nolint
 
   # Create list of source data for SPC charts
   spc_data <- data_bundle |>
-    dplyr::select(all_of(c(
+    dplyr::select(c(
       "target",
       "rebase_dates",
       "improvement_direction",
       "measure_data"
-    ))) |>
+    )) |>
     purrr::pmap(make_spc_data, .progress = "SPC data")
 
   # Create list of SPC charts
   spc_charts <- data_bundle |>
-    dplyr::select(all_of(c(
+    dplyr::select(c(
       "ref",
       "measure_name",
       "data_source",
       "unit",
       "spc_chart_type",
       "aggregation"
-    ))) |>
+    )) |>
     dplyr::mutate(label_limits = annotate_limits) |>
     dplyr::mutate(spc_data = spc_data) |>
     purrr::pmap(make_spc_chart, .progress = "SPC charts")
 
 
   tmp_files <- data_bundle |>
-    dplyr::select(all_of(c(x = "ref", y = "aggregation"))) |>
+    dplyr::select(c(x = "ref", y = "aggregation")) |>
     purrr::pmap_chr(\(x, y) glue("tmp_{x}_{y}_")) |>
     tempfile(fileext = ".png")
 
@@ -83,7 +97,7 @@ spcr_make_report <- function(
   spc_chart_uris <- tmp_files |>
     purrr::map_chr(knitr::image_uri)
 
-  data_bundle_full <- data_bundle |>
+  data_bundle_full <- data_bundle |> # nolint
     dplyr::mutate(
       spc_data = spc_data,
       spc_chart_uri = spc_chart_uris,
@@ -130,8 +144,8 @@ spcr_make_report <- function(
     gsub(" ", "_", report_title), "_", time_stamp, ".html"
   )
 
-  # create a document title (HTML <title>), unless already supplied
-  # `pagetitle` in YAML/Pandoc
+  # Create a document title (HTML <title>), unless already supplied
+  # `pagetitle` in YAML/Pandoc.
   # https://community.rstudio.com/t/r-markdown-html-output-title/47294
   if (is.null(document_title)) {
     document_title <- paste0(
@@ -139,7 +153,7 @@ spcr_make_report <- function(
     )
   }
 
-  # render the html output
+  # Render the html output
   usethis::ui_info("Making HTML output...")
 
   rmarkdown::render(
@@ -155,24 +169,24 @@ spcr_make_report <- function(
     output_file = output_file_name
   )
 
-  # print the full path to the console
+  # Print the full path to the console
   wd <- getwd() |>
-    stringr::str_remove("^\\\\{1}") # if network location, remove an initial '\'
+    stringr::str_remove("^\\\\{1}") # If network location, remove an initial '\'
   path <- file.path(wd, output_directory, output_file_name)
   usethis::ui_info("HTML filepath: {path}")
   usethis::ui_done("HTML output complete.")
 
-  # open the result in the browser
+  # Open the result in the browser
   utils::browseURL(path)
 
-  # render a pdf if needed
+  # Render a pdf if needed
   if ("pdf" %in% output_type) {
     convert_to_pdf(path)
   }
 
   beepr::beep()
 
-  process_duration <- lubridate::as.period(Sys.time() - start_time) |>
+  process_duration <- lubridate::as.period(Sys.time() - start_time) |> # nolint
     round() |>
     tolower()
 
@@ -208,7 +222,7 @@ make_spc_data <- function(
   ) {
   measure_data |>
     # remove duplicate dttms using `slice_max` to keep just one row per date
-    dplyr::slice_max(value, n = 1, with_ties = FALSE, by = "date") |>
+    dplyr::slice_max(pick("value"), n = 1, with_ties = FALSE, by = "date") |>
     NHSRplotthedots::ptd_spc(
       rebase = align_rebase_dates(rebase_dates, measure_data),
       value_field = "value",
@@ -236,7 +250,7 @@ make_spc_chart <- function(
       percentage_y_axis = unit == "%",
       main_title = paste0("#", ref, " - ", measure_name),
       x_axis_label = NULL,
-      y_axis_label = if_else(spc_chart_type == "t", "Days since previous occurrence", ""),
+      y_axis_label = if_else(spc_chart_type == "t", "Days since previous occurrence", ""), # nolint
       x_axis_breaks = "1 month",
       x_axis_date_format = if_else(aggregation == "week", "%d-%b-%Y", "%b '%y"),
       label_limits = label_limits,
@@ -252,7 +266,7 @@ make_spc_chart <- function(
       legend.margin = ggplot2::margin(t = 0, r = 0, b = 0, l = 0, unit = "pt")
     )
 
-  # conditionally add the "hollow" final data point to rare-event charts
+  # Conditionally add the "hollow" final data point to rare-event charts
   if (spc_chart_type == "t") {
     plot +
       ggplot2::annotate(
@@ -261,7 +275,7 @@ make_spc_chart <- function(
         y = dplyr::last(spc_data[["y"]]),
         shape = "circle filled",
         colour = "grey65", # #a6a6a6 (matches plotthedots grey)
-        fill = NA,   # so the PTD dot can be seen
+        fill = NA, # So the PTD dot can be seen
         size = 5,
         stroke = 2
       )
diff --git a/man/check_dataset_is_complete.Rd b/man/check_dataset_is_complete.Rd
index 189bbfb..9649330 100644
--- a/man/check_dataset_is_complete.Rd
+++ b/man/check_dataset_is_complete.Rd
@@ -7,7 +7,8 @@
 check_dataset_is_complete(report_config, measure_data)
 }
 \arguments{
-\item{report_config}{A data frame. The report config detailing required report items}
+\item{report_config}{A data frame. The report config detailing required
+report items}
 
 \item{measure_data}{Data frame in wide format}
 }
diff --git a/man/spcr_make_data_bundle.Rd b/man/spcr_make_data_bundle.Rd
index c16e56f..a676c42 100644
--- a/man/spcr_make_data_bundle.Rd
+++ b/man/spcr_make_data_bundle.Rd
@@ -18,10 +18,12 @@ spcr_make_data_bundle(
 
 \item{measure_config}{data frame. Config information for the measures}
 
-\item{data_cutoff_dttm}{POSIXct. The data cutoff date-time (the last date-time for data in the report eg. month-end)}
+\item{data_cutoff_dttm}{POSIXct. The data cutoff date-time (the last
+date-time for data in the report eg. month-end)}
 }
 \value{
-data frame. A nested data frame containing source data for the report
+data frame. A nested data frame containing source data for the
+report
 }
 \description{
 Make a bundle of data
diff --git a/man/spcr_make_report.Rd b/man/spcr_make_report.Rd
index 695238e..9f267b7 100644
--- a/man/spcr_make_report.Rd
+++ b/man/spcr_make_report.Rd
@@ -27,19 +27,25 @@ spcr_make_report(
 )
 }
 \arguments{
-\item{data_bundle}{data frame. The pre-processed bundle of information (ideally made with \code{spcr_make_data_bundle()})}
+\item{data_bundle}{data frame. The pre-processed bundle of information
+(ideally made with \code{spcr_make_data_bundle()})}
 
-\item{report_title}{string. The report title, printed at the top of the report}
+\item{report_title}{string. The report title, printed at the top of the
+report}
 
 \item{subtitle}{string. The report subtitle, printed at the top of the report}
 
-\item{document_title}{string. A title for the document, as used in the HTML \verb{<title>} tag or as the PDF document title. If left as NULL (the default), this function will use the \code{report_title} parameter and the current date to construct a title}
+\item{document_title}{string. A title for the document, as used in the HTML
+\verb{<title>} tag or as the PDF document title. If left as NULL (the default),
+this function will use the \code{report_title} parameter and the current date
+to construct a title}
 
 \item{report_ref}{string. A unique reference for the report}
 
 \item{logo_path}{string. File path of the logo to be used on the report}
 
-\item{department}{string. A text suffix positioned underneath the logo, for eg. department name}
+\item{department}{string. A text label positioned underneath the logo,
+for example the department name}
 
 \item{department_text_colour}{string. The colour of the department text}
 
@@ -49,21 +55,29 @@ spcr_make_report(
 
 \item{author_email}{string. The author's contact email address}
 
-\item{paper_colour}{string. Customise the background colour using a hex code, or CSS colour name}
+\item{paper_colour}{string. Customise the background colour using a hex
+code, or CSS colour name}
 
-\item{accordion_colour}{string. Customise the accordion colour using a hex code, or CSS colour name}
+\item{accordion_colour}{string. Customise the accordion colour using a hex
+code, or CSS colour name}
 
-\item{stale_colour}{string. Customise the date lozenge to indicate that data is stale, using a hex code, or CSS colour name}
+\item{stale_colour}{string. Customise the date lozenge to indicate that
+data is stale, using a hex code, or CSS colour name}
 
-\item{fresh_colour}{string. Customise the date lozenge to indicate that data is up to date, using a hex code, or CSS colour name}
+\item{fresh_colour}{string. Customise the date lozenge to indicate that
+data is up to date, using a hex code, or CSS colour name}
 
-\item{output_directory}{string. The name of the directory in which to save the resulting report}
+\item{output_directory}{string. The name of the directory in which to save
+the resulting report}
 
-\item{output_type}{vector. Specify what output types are needed.  Default is c("html", "csv"). "pdf" is also possible.}
+\item{output_type}{vector. Specify what output types are needed. The
+default is c("html", "csv"). "pdf" is also possible.}
 
-\item{include_dq_icon}{logical. Whether to include the data quality icon on the final report}
+\item{include_dq_icon}{logical. Whether to include the data quality icon
+on the final report}
 
-\item{annotate_limits}{logical. Whether to add annotations to a secondary y axis for process limits and mean}
+\item{annotate_limits}{logical. Whether to add annotations to a
+secondary y axis for process limits and mean}
 }
 \description{
 Make the SPC Report
diff --git a/reprex.R b/reprex.R
deleted file mode 100644
index 170843a..0000000
--- a/reprex.R
+++ /dev/null
@@ -1,395 +0,0 @@
-cutoff_date <- lubridate::floor_date(Sys.Date(), unit = "month") - lubridate::as.period("1d")
-cutoff_dttm <- (cutoff_date + 1) - lubridate::as.period("1s")
-data_cutoff_dttm <- cutoff_dttm
-def_start_date <- lubridate::as_datetime("2020-01-01")
-bnet_start <- lubridate::as_datetime("2022-12-01")
-m_prefix <- "fh_m"
-prefix <- \(x, mp = m_prefix) paste0(mp, "_", x)
-
-
-rep_config <- "Maternity_Services_Report" |>
-  FH027MaternityReporting::get_report_config() |>
-  dplyr::filter(if_any("ref", \(x) x %in% c("6", "132", "197")))
-
-measure_config <- FH027MaternityReporting::get_measure_config() |>
-  dplyr::filter(if_any("measure_prefix", \(x) x == m_prefix))
-
-
-report_refs <- sort(unique(as.numeric(rep_config[["ref"]])))
-completed_refs <- unique(c(
-  57, 74, 85, 90, 118, 132, 172, 195:196, 203:205, # excel
-  197, 250, # eobs
-  75:77, 79:81, 84, 86:88, 104, 108, 194, # datix
-  # 43, 48, 50, 53:55, 174, 320, # misc other long
-  53:55, # hie
-  # 45, 200, # kilometrics
-  33, 40, 62, 63 # medway
-))
-bnet_refs <- prefix(setdiff(report_refs, completed_refs))
-
-bnet_config <- rep_config |>
-  dplyr::filter(if_any("measure_id", \(x) x %in% bnet_refs))
-
-
-bnet_data <- DataHoover::dh_build_report_dataset(
-  measure_config = measure_config,
-  report_config = bnet_config,
-  start_dttm = bnet_start,
-  end_dttm = cutoff_dttm,
-  output_format = "long"
-)
-
-bnet_event_refs <- prefix(c(
-  2:3, 8, 11, 13, 15, 31, 37, 39, 161:162, 178, 180, 207:212, 222:223,
-  257, 261:262, 265:267, 269:270, 273:281, 311, 316:317
-))
-
-bnet_data_out <- bnet_data[["event_lists"]] |>
-  purrr::keep_at(as.character(bnet_event_refs)) |>
-  purrr::map(\(x) DataHoover::dh_aggregate(x, bnet_start, cutoff_dttm, "month")) |>
-  purrr::list_rbind() |>
-  dplyr::bind_rows(bnet_data[["month"]]) |>
-  dplyr::rename_with(tolower) |>
-  dplyr::rename(ref = "measure_ref") |>
-  # 'kilometrics':
-  dplyr::mutate(
-    across("value",
-      \(x) dplyr::if_else(
-        .data[["ref"]] %in% c("45", "200") & .data[["date"]] >= bnet_start,
-        x * 1000,
-        x
-      )
-    )
-  )
-
-cf_id_cols <- c("measure_prefix", "ref", "measure_name", "comment")
-cf_cutoff <- lubridate::ymd("2022-11-01")
-
-cf_refs <- c(2, 43, 45, 48, 50, 161, 174, 200, 267, 320)
-
-xl6_data <- "Careflow Data" |>
-  FH027MaternityReporting:::create_network_path() |>
-  FH027MaternityReporting:::read_sheet("month") |>
-  dplyr::mutate(across("ref", as.character)) |>
-  dplyr::mutate(comment = "Read in from Careflow Data Excel file.") |>
-  dplyr::mutate(measure_prefix = "fh_m", .before = "ref") |>
-  dplyr::select(all_of(cf_id_cols) | matches("^\\d{4}\\-\\d{2}\\-\\d{2}$")) |>
-  tidyr::pivot_longer(
-    cols = !any_of(cf_id_cols),
-    names_to = "date",
-    names_transform = list(date = as.POSIXct)
-  ) |>
-  dplyr::filter(if_any("date", \(x) x <= cf_cutoff)) |>
-  dplyr::filter(if_any("value", \(x) !is.na(x))) |>
-  dplyr::filter(if_any("ref", \(x) x %in% as.character(cf_refs)))
-
-
- if ("132" %in% rep_config[["ref"]]) {
-  xl2_data <- "Maternal Deaths" |>
-    FH027MaternityReporting:::create_network_path() |>
-    FH027MaternityReporting:::read_sheet("none") |>
-    dplyr::mutate(Measure_Prefix = "fh_m", .before = "Measure_Ref") |>
-    dplyr::mutate(across("Measure_Ref", as.character))
-  assertthat::assert_that(identical(names(xl2_data), tb_cols))
-} else {
-  xl2_data <- NULL
-}
-
-
-eobs_st <- lubridate::as_datetime("2021-03-01")
-eobs_refs <- prefix(c(197, 250))
-# nums & denoms for M197 & M250:
-eobs_event_refs <- prefix(251:254)
-eobs_config <- rep_config |>
-  dplyr::filter(if_any("measure_id", \(x) x %in% eobs_refs))
-
-
-if (nrow(eobs_config) > 0) {
-  eobs_data <- DataHoover::dh_build_report_dataset(
-    measure_config = measure_config,
-    report_config = eobs_config,
-    start_dttm = eobs_st,
-    end_dttm = cutoff_dttm,
-    aggregation_levels = "month",
-    output_format = "long"
-  )
-  eobs_data_out <- eobs_data[["event_lists"]] |>
-  purrr::keep_at(eobs_event_refs) |>
-  purrr::map(\(x) DataHoover::dh_aggregate(x, eobs_st, cutoff_dttm, "month")) |>
-  purrr::list_rbind() |>
-  dplyr::bind_rows(eobs_data[["month"]]) |>
-  dplyr::rename_with(tolower) |>
-  dplyr::rename(ref = "measure_ref")
-  assertthat::assert_that(identical(names(eobs_data_out), pref_cols))
-} else {
-  eobs_data_out <- NULL
-}
-
-rare_refs <- rep_config |>
-  dplyr::filter(if_any("spc_chart_type", \(x) x == "t")) |>
-  dplyr::pull("ref") |>
-  unique()
-pref_rare_refs <- prefix(rare_refs)
-
-
-
-
-rare_data <- list(
-  bnet_data[["event_lists"]]
-) |>
-  purrr::list_flatten() |>
-  purrr::keep_at(pref_rare_refs) |>
-  purrr::list_rbind() |>
-  dplyr::bind_rows(xl2_data) |>
-  dplyr::filter(if_any("Measure_Ref", \(x) x %in% rare_refs))
-
-if (nrow(rare_data) == 0) {
-  rare_data <- tibble::tibble(
-    measure_prefix = character(),
-    ref = character(),
-    measure_name = character(),
-    comment = character(),
-    event_date_or_datetime = as.Date(character())
-  )
-} else {
-  rare_data <- rare_data |>
-    dplyr::rename_with(tolower) |>
-    dplyr::arrange(pick(c("measure_ref", "dttm"))) |>
-    dplyr::select(all_of(c(
-      "measure_prefix",
-      ref = "measure_ref",
-      "measure_name",
-      "comment",
-      "id",
-      event_date_or_datetime = "dttm")
-    )) |>
-    dplyr::distinct()
-}
-
-main_data <- FH027MaternityReporting::get_main_data(report_config = rep_config)
-
-
-
-mc_cols <- c("measure_prefix", "ref", "measure_name", "numerator_ref", "denominator_ref")
-core_cols <- c("ref", "measure_name", "comment", "date", "value")
-pref_cols <- c("measure_prefix", core_cols)
-tb_cols <- c("Measure_Prefix", "Measure_Ref", "Measure_Name", "Comment", "ID", "DTTM")
-ignore_refs <- c(
-    "x", as.character(c(2, 43:44, 48:50, 53:57, 64, 74:77, 102, 132, 187, 320))
-  )
-da_id_cols <- c("measure_prefix", "ref", "measure_name", "comment")
-da_cutoff <- lubridate::ymd("2022-11-01")
-
-
-xl5_data <- "Division Analyst" |>
-    FH027MaternityReporting:::create_network_path() |>
-    FH027MaternityReporting:::read_sheet("month") |>
-    dplyr::mutate(across("ref", as.character)) |>
-    dplyr::filter(if_any("ref", \(x) !x %in% ignore_refs)) |>
-    dplyr::mutate(measure_prefix = "fh_m", .before = "ref") |>
-    dplyr::mutate(comment = "Read in from Division Analyst Excel file.") |>
-    dplyr::select(all_of(da_id_cols) | matches("^[0-9]+$")) |>
-    tidyr::pivot_longer(
-      cols = !any_of(da_id_cols),
-      names_to = "date",
-      names_transform = list(
-        date = \(x) as.Date(as.integer(x), origin = "1899-12-30")
-      )
-    ) |>
-    dplyr::filter(if_any("date", \(x) x <= da_cutoff)) |>
-    dplyr::filter(if_any("value", \(x) !is.na(x))) |>
-    dplyr::filter(if_any("ref", \(x) x == "6"))
-
-
-bnet_data <- DataHoover::dh_build_report_dataset(
-    measure_config = measure_config,
-    report_config = rep_config,
-    start_dttm = bnet_start,
-    end_dttm = cutoff_dttm,
-    output_format = "long"
-  )
-bnet_data_out <- bnet_data[["month"]] |>
-  dplyr::rename_with(tolower) |>
-  dplyr::rename(ref = "measure_ref")
-
-
-src_data <- list(
-  xl5_data,  # DA spreadsheet
-  bnet_data_out,
-  eobs_data_out
-) |>
-  dplyr::bind_rows() |>
-  dplyr::distinct()
-
-src_data_wide <- src_data |>
-  dplyr::select(all_of(pref_cols)) |>
-  dplyr::distinct() |>
-  dplyr::mutate(
-    across("comment", \(x) stringr::str_flatten(unique(x), " / ")),
-    .by = c("measure_prefix", "ref")
-  ) |>
-  dplyr::distinct() |>
-  dplyr::arrange(date) |>
-  tidyr::pivot_wider(names_from = "date") |>
-  dplyr::arrange(as.numeric(grep("\\d+", .data[["ref"]], value = TRUE)))
-
-
-n_months <- lubridate::interval(def_start_date, cutoff_date) |>
-  lubridate::as.period("months") |>
-  stringr::str_extract("^\\d+") |>
-  as.numeric()
-assertthat::assert_that(
-  ncol(src_data_wide) == (n_months + 1) + (length(pref_cols) - 2)
-)
-
-main_data <- list(month = src_data_wide, events = rare_data)
-
-
-main_bundle <- FH027MaternityReporting::generate_main_bundle(
-  main_data = main_data,
-  report_config = rep_config,
-  measure_config = measure_config
-)
-
-FH027MaternityReporting::generate_main_report(
-  data_bundle = main_bundle,
-  report_config = rep_config,
-  measure_config = measure_config
-)
-
-
-rbds <- main_bundle[["rebase_dates"]]
-rbds
-
-parse_rebase_dates(rbds)
-rbds_dates <- purrr::map(rbds, parse_rebase_dates)
-m_data <- main_bundle[["measure_data"]]
-
-pull_closest_date <- function(date, dates_list) {
-  if (is.null(date)) NA
-  else {
-    later_dates <- dates_list[dates_list >= date]
-    if (length(later_dates)) min(later_dates) else date
-  }
-}
-
-rbds_dates |>
-  purrr::map2_dbl(m_data, \(x, y) pull_closest_date(x, y[["date"]])) |>
-  lubridate::as_datetime() |>
-  lubridate::as_date()
-
-
-
-# --- 
-
-
-main_data <- FH027MaternityReporting::get_main_data()
-
-report_config <- "Maternity_Services_Report" |>
-  FH027MaternityReporting:::get_report_config()
-measure_config <- FH027MaternityReporting:::get_measure_config() |>
-  dplyr::filter(if_any("measure_prefix", \(x) x == m_prefix))
-
-data_cutoff_dttm <- (cutoff_date + 1) - lubridate::as.period("1s")
-
-measure_data <- check_measure_data(main_data)
-report_config <- check_report_config(report_config)
-measure_config <- check_measure_config(measure_config)
-
-
-e_data <- measure_data |>
-  purrr::pluck("events")
-a_data <- measure_data |>
-  purrr::discard_at("events")
-a_data <- check_a_data(a_data)
-e_data <- check_e_data(e_data)
-e_data_time_between <- process_event_data_t(e_data, data_cutoff_dttm)
-
-
-a_data_df <- a_data |>
-  dplyr::bind_rows(.id = "aggregation")
-
-measure_data_long <- a_data_df |>
-  lengthen_measure_data() |>
-  dplyr::bind_rows(e_data_time_between)
-check_dataset_is_complete(report_config, measure_data_long)
-
-report_config |>
-    dplyr::pull("ref") |>
-    purrr::walk(\(x) check_measure_names(x, measure_data_long, measure_config))
-
-
-nested_data1 <- report_config |>
-    # use measure names from report_config not from measure_config
-    dplyr::left_join(dplyr::select(measure_config, !"measure_name"), "ref") |>
-    dplyr::mutate(
-      measure_name = dplyr::case_when(
-        spc_chart_type == "t" ~ paste(measure_name, "(time-between)"),
-        TRUE ~ measure_name
-      )
-    )
-nested_data2 <- nested_data1 |>
-    dplyr::nest_join(
-      measure_data_long,
-      by = c("ref", "aggregation"),
-      name = "measure_data"
-    ) |>
-
-    # pull most recent date from each data frame in the measure_data column
-    dplyr::mutate(
-      data_cutoff_dttm = as.POSIXct(data_cutoff_dttm),
-      last_date = purrr::map_vec(.data[["measure_data"]], \(x) max(x[["date"]], na.rm = TRUE))
-    )
-nested_data3 <- nested_data2 |>
-    # pull most recent data point from each data frame in the measure_data column
-    dplyr::mutate(
-      last_data_point = purrr::map_vec(.data[["measure_data"]], \(x) {
-        dplyr::slice_max(x, order_by = x[["date"]], n = 1)[["value"]]
-      }
-      )
-    )
-nested_data3 |>
-    dplyr::mutate(
-      across("improvement_direction",
-             \(x) dplyr::case_when(
-               .data[["spc_chart_type"]] == "t" & x == "decrease" ~ "increase",
-               # a rather unlikely situation
-               .data[["spc_chart_type"]] == "t" & x == "increase" ~ "decrease",
-               TRUE ~ x))
-      ) |>
-    dplyr::mutate(
-      across("unit",
-             \(x) if_else(.data[["spc_chart_type"]] == "t", "days", x))
-      ) |>
-    dplyr::mutate(
-      across("target",
-             \(x) if_else(.data[["spc_chart_type"]] == "t", NA, x))
-      ) |>
-    dplyr::mutate(
-      across("last_data_point", \(x) dplyr::case_when(
-        is.na(x) ~ NA_character_,
-        x == Inf ~ NA_character_,
-        unit == "%" ~ paste0(round(x * 100, 1), "%"),
-        unit == "decimal" ~ as.character(round(x, 2)),
-        unit == "days" ~ paste0(x, "d"),
-        TRUE ~ as.character(round(x))))
-      ) |>
-    dplyr::mutate(
-      target_text = get_target_text(
-        .data[["target"]],
-        .data[["improvement_direction"]],
-        .data[["unit"]]
-        ),
-      updated_to = get_updatedto_text(
-        .data[["last_date"]],
-        .data[["aggregation"]]
-        )
-      )
-
-
-
-main_bundle <- FH027MaternityReporting::generate_main_bundle()
-
-View(main_bundle)
-
-
diff --git a/tests/testthat/test-calculate_stale_data.R b/tests/testthat/test-calculate_stale_data.R
index 9b6ab56..e5f1538 100644
--- a/tests/testthat/test-calculate_stale_data.R
+++ b/tests/testthat/test-calculate_stale_data.R
@@ -18,13 +18,16 @@
     lag <- 0
     cutoff_dttm <- as.POSIXct("2020-01-31 23:59:59")
 
-    # introduce the error
+    # Introduce the error
     updated_to <- as.POSIXct("2020-01-31")
 
-    # this will generate a warning message due to the incorrect date format
+    # This will generate a warning message due to the incorrect date format
     expect_error(
       calculate_stale_data(updated_to, lag, cutoff_dttm),
-      "calculate_stale_data: Unable to convert the updated_to argument text to a valid date."
+      paste0(
+        "calculate_stale_data: Unable to convert the updated_to ",
+        "argument text to a valid date."
+      )
     )
   })
 
@@ -32,7 +35,7 @@
   test_that({
 
     updated_to <- "31-Jan-2020"
-    # introduce an error
+    # Introduce an error
     lag <- 0.1
     cutoff_dttm <- as.POSIXct("2020-01-31 23:59:59")
 
@@ -48,7 +51,7 @@
     updated_to <- "31-Jan-2020"
     lag <- 0
     cutoff_dttm <- as.POSIXct("2020-01-31 23:59:59")
-    # introduce an error
+    # Introduce an error
     cutoff_dttm <- as.Date(cutoff_dttm)
 
     expect_error(
@@ -62,7 +65,7 @@
 
     updated_to <- "31-Jan-2020"
     lag <- 0
-    # report one month later
+    # Report one month later
     cutoff_dttm <- as.POSIXct("2020-02-28 23:59:59")
 
     expect_equal(
diff --git a/tests/testthat/test-check_measure_data.R b/tests/testthat/test-check_measure_data.R
index 32673bc..043abef 100644
--- a/tests/testthat/test-check_measure_data.R
+++ b/tests/testthat/test-check_measure_data.R
@@ -10,7 +10,10 @@
   test_that({
     expect_error(
       check_measure_data(list(`Once in a blue moon` = 1)),
-      "check_measure_data: One element of measure_data must be named 'week' or 'month'"
+      paste0(
+        "check_measure_data: One element of measure_data must be ",
+        "named 'week' or 'month'"
+      )
     )
   })
 
@@ -28,11 +31,10 @@
 
 "list containing either 'week' or 'month' is allowed" |>
   test_that({
-
     expect_no_error(
       list(
-        week = data.frame(ref = 1, measure_name = "M1", comment = NA)
         # month list item is not provided
+        week = data.frame(ref = 1, measure_name = "M1", comment = NA)
       ) |>
         check_measure_data()
     )
@@ -50,7 +52,8 @@
   test_that({
     expect_no_error(
       list(
-        Week = data.frame(ref = 1, measure_name = "M1", comment = NA) # Week not week
+        # Week not week
+        Week = data.frame(ref = 1, measure_name = "M1", comment = NA)
       ) |>
         check_measure_data()
     )
@@ -95,7 +98,7 @@ measure_data <- list(
 
 "it coerces refs to character vectors" |>
   test_that({
-    # create the error by assigning numeric refs
+    # Create the error by assigning numeric refs
     measure_data[["week"]]$ref <- c(1, 2, 3)
     measure_data[["month"]]$ref <- c(1, 2, 3)
 
@@ -109,19 +112,25 @@ measure_data <- list(
 
 "it errors helpfully when column names are missing or mis-spelled" |>
   test_that({
-    # create the error by removing a required column
+    # Create the error by removing a required column
     measure_data[["week"]]$ref <- NULL
 
     expect_error(
       check_measure_data(measure_data),
-      "check_for_required_columns: Column 'ref' is missing from the 'week' data frame. Check for typos in the column names."
+      paste0(
+        "check_for_required_columns: Column 'ref' is missing from the ",
+        "'week' data frame. Check for typos in the column names."
+      )
     )
 
-    # error persists when the column is mis-spelled
+    # Error persists when the column is mis-spelled
     measure_data[["week"]]$Reference <- c(1, 2, 3)
 
     expect_error(
       check_measure_data(measure_data),
-      "check_for_required_columns: Column 'ref' is missing from the 'week' data frame. Check for typos in the column names."
+      paste0(
+        "check_for_required_columns: Column 'ref' is missing from the ",
+        "'week' data frame. Check for typos in the column names."
+      )
     )
   })
diff --git a/tests/testthat/test-checking_functions.R b/tests/testthat/test-checking_functions.R
index 05c3f85..dcae5e1 100644
--- a/tests/testthat/test-checking_functions.R
+++ b/tests/testthat/test-checking_functions.R
@@ -2,13 +2,13 @@
 "check_dataset_is_complete: happy path" |>
   test_that({
 
-    # this function is called when before the aggregation is manually changed from
-    # "events" to "none", so we need to create the renaming here
+    # This function is called when before the aggregation is manually changed
+    # from "events" to "none", so we need to create the renaming here.
     measure_data_df <- test_measure_data |>
       dplyr::bind_rows(.id = "aggregation") |>
       dplyr::mutate(aggregation = dplyr::case_when(
         aggregation == "events" ~ "none",
-        TRUE ~ aggregation
+        .default = aggregation
       ))
 
     expect_no_error(
@@ -26,7 +26,7 @@
       dplyr::bind_rows(.id = "aggregation") |>
       dplyr::mutate(aggregation = dplyr::case_when(
         aggregation == "events" ~ "none",
-        TRUE ~ aggregation
+        .default = aggregation
       ))
 
     report_config_plus_one <- test_report_config |>
@@ -38,19 +38,26 @@
         report_config_plus_one,
         measure_data_df
       ),
-      "Data is missing for 1 report items. The first is ref 9999, 'test', aggregation: week."
+      paste0(
+        "check_dataset_is_complete: ",
+        "Data is missing for 1 report items. The first is ref 9999, 'test', ",
+        "aggregation: week"
+      )
     )
 
     report_config_plus_two <- test_report_config |>
-      tibble::add_row(ref = 9998, measure_name = "test", aggregation = "none") |>
-      tibble::add_row(ref = 9999, measure_name = "test", aggregation = "week")
+      tibble::add_row(ref = 998, measure_name = "test", aggregation = "none") |>
+      tibble::add_row(ref = 999, measure_name = "test", aggregation = "week")
 
     expect_error(
       check_dataset_is_complete(
         report_config_plus_two,
         measure_data_df
       ),
-      "Data is missing for 2 report items. The first is ref 9998, 'test', aggregation: none."
+      paste0(
+        "Data is missing for 2 report items. The first is ref 998, 'test', ",
+        "aggregation: none"
+      )
     )
   })
 
@@ -59,7 +66,7 @@
 # check measure config
 "check measure config: coerces refs to character vectors" |>
   test_that({
-    # create the error by assigning numeric refs
+    # Create the error by assigning numeric refs
     measure_config <- tibble::tibble(
       ref = c(1, 2, 3),
       measure_name = c("M1", "M2", "M3"),
@@ -87,10 +94,10 @@
     )
   })
 
-"check measure config: errors helpfully when column names are missing or mis-spelled" |>
+"check measure config: errors helpfully when column names are missing or mis-spelled" |> # nolint
   test_that({
 
-    # create the error by omitting a required column (unit)
+    # Create the error by omitting a required column (unit)
     measure_config <- tibble::tibble(
       ref = c("1", "2", "3"),
       measure_name = c("M1", "M2", "M3"),
@@ -109,10 +116,13 @@
 
     expect_error(
       check_measure_config(measure_config),
-      "check_for_required_columns: Column 'unit' is missing from the 'measure_config' data frame. Check for typos in the column names."
+      paste0(
+        "check_for_required_columns: Column 'unit' is missing from the ",
+        "'measure_config' data frame. Check for typos in the column names."
+      )
     )
 
-    # error persists when the column is mis-spelled
+    # Error persists when the column is mis-spelled
     measure_config <- tibble::tibble(
       ref = c("1", "2", "3"),
       measure_name = c("M1", "M2", "M3"),
@@ -131,14 +141,17 @@
 
     expect_error(
       check_measure_config(measure_config),
-      "check_for_required_columns: Column 'unit' is missing from the 'measure_config' data frame. Check for typos in the column names."
+      paste0(
+        "check_for_required_columns: Column 'unit' is missing from the ",
+        "'measure_config' data frame. Check for typos in the column names."
+      )
     )
   })
 
 
 
 
-# check measure names
+# Check measure names
 "check measure names: happy path" |>
   test_that({
 
@@ -199,7 +212,7 @@
 
 
 
-# check report config
+# Check report config
 "check report config: coerces refs to character vectors" |>
   test_that({
 
@@ -221,10 +234,10 @@
     )
   })
 
-"check report config: errors helpfully when column names are missing or mis-spelled" |>
+"check report config: errors helpfully when column names are missing or mis-spelled" |> # nolint
   test_that({
 
-    # create the error by omitting a required column ('domain')
+    # Create the error by omitting a required column ('domain')
     report_config <- tibble::tibble(
       ref = c("1", "2", "3", "1", "2", "3"),
       measure_name = c("M1", "M2", "M3", "M1", "M2", "M3"),
@@ -235,10 +248,13 @@
 
     expect_error(
       check_report_config(report_config),
-      "check_for_required_columns: Column 'domain' is missing from the 'report_config' data frame. Check for typos in the column names."
+      paste0(
+        "check_for_required_columns: Column 'domain' is missing from the ",
+        "'report_config' data frame. Check for typos in the column names."
+      )
     )
 
-    # error persists when the column is mis-spelled
+    # Error persists when the column is mis-spelled
     report_config <- tibble::tibble(
       ref = c("1", "2", "3", "1", "2", "3"),
       measure_name = c("M1", "M2", "M3", "M1", "M2", "M3"),
@@ -249,14 +265,17 @@
 
     expect_error(
       check_report_config(report_config),
-      "check_for_required_columns: Column 'domain' is missing from the 'report_config' data frame. Check for typos in the column names."
+      paste0(
+        "check_for_required_columns: Column 'domain' is missing from the ",
+        "'report_config' data frame. Check for typos in the column names."
+      )
     )
   })
 
 "check report config: missing optional columns does not throw an error" |>
   test_that({
 
-    # assign numeric refs
+    # Assign numeric refs
     report_config <- tibble::tibble(
       ref = c(1, 2, 3, 1, 2, 3),
       measure_name = c("M1", "M2", "M3", "M1", "M2", "M3"),
@@ -268,7 +287,10 @@
 
     expect_message(
       check_report_config(report_config),
-      "i check_for_optional_columns: Optional column 'report_comment' is missing. Adding it."
+      paste0(
+        "i check_for_optional_columns: Optional column 'report_comment' ",
+        "is missing. Adding it."
+      )
     )
 
   })
@@ -306,7 +328,7 @@
 
     aggregated_datasheet <- tibble::tibble(
       ref = c(1, 2, 3),
-      # measure_name = c("M1", "M2", "M3"), # missing column
+      # measure_name = c("M1", "M2", "M3"), # Missing column
       comment = c("comment", "comment", "comment")
     )
 
@@ -325,7 +347,10 @@
 
     expect_error(
       check_measure_data(measure_data),
-      "check_for_required_columns: Column 'measure_name' is missing from the 'week' data frame. Check for typos in the column names."
+      paste0(
+        "check_for_required_columns: Column 'measure_name' is missing ",
+        "from the 'week' data frame. Check for typos in the column names."
+      )
     )
 
   })
@@ -355,7 +380,7 @@
 
     datasheet <- tibble::tibble(
       ref = c(1, 2, 3),
-      # measure_name = c("M1", "M2", "M3"), # missing column
+      # measure_name = c("M1", "M2", "M3"), # Missing column
       comment = c("comment", "comment", "comment")
     )
 
@@ -366,7 +391,10 @@
 
     expect_error(
       check_a_data(a_data),
-      "check_for_required_columns: Column 'measure_name' is missing from the 'week' data frame. Check for typos in the column names."
+      paste0(
+        "check_for_required_columns: Column 'measure_name' is missing ",
+        "from the 'week' data frame. Check for typos in the column names."
+      )
     )
 
   })
@@ -394,12 +422,16 @@
       ref = c(1, 2, 3),
       measure_name = c("M1", "M2", "M3"),
       comment = c("comment", "comment", "comment"),
-      # event_date_or_datetime = "there will be dates here" # missing column
+      # event_date_or_datetime = "there will be dates here" # Missing column
     )
 
     expect_error(
       check_e_data(e_data),
-      "check_for_required_columns: Column 'event_date_or_datetime' is missing from the 'events' data frame. Check for typos in the column names."
+      paste0(
+        "check_for_required_columns: Column 'event_date_or_datetime' ",
+        "is missing from the 'events' data frame. Check for typos in the ",
+        "column names."
+      )
     )
 
   })
diff --git a/tests/testthat/test-get_assurance_type.R b/tests/testthat/test-get_assurance_type.R
index 2b8548c..1786b75 100644
--- a/tests/testthat/test-get_assurance_type.R
+++ b/tests/testthat/test-get_assurance_type.R
@@ -65,11 +65,11 @@ test_that("it returns correct string in failing conditions", {
   )
 
 
-  # improvement direction = decrease
+  # Improvement direction = decrease
   spc <- data.frame(
     upl = 3,
     lpl = 1,
-    target = 0 # the target is below process limits
+    target = 0 # The target is below process limits
   )
 
   expect_equal(
@@ -79,11 +79,11 @@ test_that("it returns correct string in failing conditions", {
 })
 
 test_that("it returns correct string in passing conditions", {
-  # improvement direction = increase
+  # Improvement direction = increase
   spc <- data.frame(
     upl = 3,
     lpl = 1,
-    target = 0.5 # the target is below process limits
+    target = 0.5 # The target is below process limits
   )
 
   expect_equal(
@@ -91,9 +91,9 @@ test_that("it returns correct string in passing conditions", {
     "PASS_TARG"
   )
 
-  # improvement direction = decrease
+  # Improvement direction = decrease
   spc <- data.frame(
-    target = 4, # the target is above process limits
+    target = 4, # The target is above process limits
     upl = 3,
     lpl = 1
   )
diff --git a/tests/testthat/test-helper_functions.R b/tests/testthat/test-helper_functions.R
index b605eff..b87dca5 100644
--- a/tests/testthat/test-helper_functions.R
+++ b/tests/testthat/test-helper_functions.R
@@ -1,6 +1,6 @@
 "updatedto_text handles dttms correctly 1" |>
   test_that({
-    # failing test for current behaviour (11 March 2024)
+    # Failing test for current behaviour (11 March 2024)
 
     d1 <- lubridate::as_date("2024-02-01")
     d2 <- lubridate::as_datetime("2024-02-01")
@@ -21,12 +21,12 @@
 
 "updatedto_text handles dttms correctly 2" |>
   test_that({
-    # failing test for current behaviour (11 March 2024)
+    # Failing test for current behaviour (11 March 2024)
 
     d1 <- lubridate::as_date("2024-02-01")
     d2 <- lubridate::as_datetime("2024-02-01")
 
-    # the function needs to operate on a date not a datetime
+    # The function needs to operate on a date not a datetime
     d1 <- as.Date(d1)
     d2 <- as.Date(d2)
 
@@ -34,8 +34,8 @@
 
     aggregation <- "month"
 
-    o1 <- lubridate::ceiling_date(d1, aggregation) - lubridate::days(1)
-    o2 <- lubridate::ceiling_date(d2, aggregation) - lubridate::days(1)
+    o1 <- lubridate::ceiling_date(d1, aggregation) - days(1)
+    o2 <- lubridate::ceiling_date(d2, aggregation) - days(1)
 
     expect_equal(o1, desired_result)
     expect_equal(o2, desired_result)
@@ -45,7 +45,7 @@
 "general input/output test for get_updatedto_text() part 1" |>
   test_that({
     d1 <- lubridate::as_date("2024-02-01") # A Thursday
-    exp_out <- "29-Feb-2024" # character not date
+    exp_out <- "29-Feb-2024" # Character not date
 
     od1 <- get_updatedto_text(d1, "none")
     expect_identical(od1, exp_out)
@@ -54,21 +54,21 @@
     expect_identical(od2, exp_out)
 
     od3 <- get_updatedto_text(d1, "day")
-    expect_identical(od3, "01-Feb-2024") # character not date
+    expect_identical(od3, "01-Feb-2024") # Character not date
 
     od4 <- get_updatedto_text(d1, "calendar_year")
-    expect_identical(od4, "31-Dec-2024") # character not date
+    expect_identical(od4, "31-Dec-2024") # Character not date
 
     od5 <- get_updatedto_text(d1, "week")
     # Should give us the following Sunday (4 Feb)
-    expect_identical(od5, "04-Feb-2024") # character not date
+    expect_identical(od5, "04-Feb-2024") # Character not date
   })
 
 
 "general input/output test for get_updatedto_text() part 2" |>
   test_that({
     d1 <- lubridate::as_date("2024-01-01") # A Monday
-    exp_out <- "31-Jan-2024" # character not date
+    exp_out <- "31-Jan-2024" # Character not date
 
     od1 <- get_updatedto_text(d1, "none")
     expect_identical(od1, exp_out)
@@ -77,21 +77,21 @@
     expect_identical(od2, exp_out)
 
     od3 <- get_updatedto_text(d1, "day")
-    expect_identical(od3, "01-Jan-2024") # character not date
+    expect_identical(od3, "01-Jan-2024") # Character not date
 
     od4 <- get_updatedto_text(d1, "calendar_year")
-    expect_identical(od4, "31-Dec-2024") # character not date
+    expect_identical(od4, "31-Dec-2024") # Character not date
 
     od5 <- get_updatedto_text(d1, "week")
     # Should give us the following Sunday (7 Jan)
-    expect_identical(od5, "07-Jan-2024") # character not date
+    expect_identical(od5, "07-Jan-2024") # Character not date
 
-    # financial year still to be implemented
+    # Financial year still to be implemented
 
 
     # try some errors
     expect_error(
-      get_updatedto_text(d1, "quarter"), # not implemented
+      get_updatedto_text(d1, "quarter"), # Not implemented
       "get_updatedto_text: invalid aggregation (quarter) provided",
       fixed = TRUE
     )
diff --git a/tests/testthat/test-lengthen_measure_data.R b/tests/testthat/test-lengthen_measure_data.R
index 2e2f2b2..6510057 100644
--- a/tests/testthat/test-lengthen_measure_data.R
+++ b/tests/testthat/test-lengthen_measure_data.R
@@ -40,25 +40,31 @@
 
 "check input names" |>
   test_that({
-    ymd_regex <- "^20[0-9]{2}-[0-9]{1,2}-[0-9]{1,2}$"
+    ymd_rx <- "^20[0-9]{2}-[0-9]{1,2}-[0-9]{1,2}$"
     init_cols <- c("ref", "measure_name", "comment")
 
     df_names <- c("ref", "measure_name", "2022-01-01", "90210")
 
     expect_true(
       all(purrr::map_lgl(
-        df_names, \(x) x %in% init_cols |
-          stringr::str_detect(x, "^[0-9]{5}$") |
-          stringr::str_detect(x, ymd_regex)))
+        df_names, \(x) {
+          x %in% init_cols |
+            stringr::str_detect(x, "^[0-9]{5}$") |
+            stringr::str_detect(x, ymd_rx)
+        }
+      ))
     )
 
     df_names <- c(df_names, "other")
 
     expect_false(
-      all(purrr::map_lgl(
-      df_names, \(x) x %in% init_cols |
-        stringr::str_detect(x, "^[0-9]{5}$") |
-        stringr::str_detect(x, ymd_regex)))
+      all(
+        purrr::map_lgl(df_names, \(x) {
+          x %in% init_cols |
+            stringr::str_detect(x, "^[0-9]{5}$") |
+            stringr::str_detect(x, ymd_rx)
+        })
+      )
     )
   })
 
@@ -77,7 +83,9 @@
     )
 
     out1 <- .data |>
-      tidyr::pivot_longer(!any_of(init_cols), names_to = "date", values_drop_na = TRUE)
+      tidyr::pivot_longer(
+        !any_of(init_cols), names_to = "date", values_drop_na = TRUE
+      )
 
     tibble::tibble(
       ref = c(1, 2, 2),
@@ -90,7 +98,9 @@
 
 
     out2 <- .data |>
-      tidyr::pivot_longer(!any_of(init_cols), names_to = "date", values_drop_na = TRUE) |>
+      tidyr::pivot_longer(
+        !any_of(init_cols), names_to = "date", values_drop_na = TRUE
+      ) |>
       dplyr::mutate(across("date", quietly_convert_date))
 
     tibble::tibble(
@@ -102,4 +112,3 @@
     ) |>
       expect_equal(out2)
   })
-
diff --git a/tests/testthat/test-process_event_data_t.R b/tests/testthat/test-process_event_data_t.R
index 44c863c..47ac407 100644
--- a/tests/testthat/test-process_event_data_t.R
+++ b/tests/testthat/test-process_event_data_t.R
@@ -4,7 +4,9 @@
     e_data <- tibble::tibble(
       "ref" = c(123, 123, 123),
       "measure_name" = "Name",
-      "event_date_or_datetime" = as.POSIXct(c("2020-01-01", "2020-01-03", "2020-01-13"))
+      "event_date_or_datetime" = as.POSIXct(c(
+        "2020-01-01", "2020-01-03", "2020-01-13"
+      ))
     )
 
     cutoff_dttm <- as.POSIXct("2020-01-31 23:59:59")
@@ -18,7 +20,12 @@
       c("aggregation", "ref", "measure_name", "date", "value")
     )
 
-    expect_equal(result[["date"]], as.POSIXct(c("2020-01-03 00:00:00", "2020-01-13 00:00:00", "2020-01-31 23:59:59")))
+    expect_equal(
+      result[["date"]],
+      as.POSIXct(c(
+        "2020-01-03 00:00:00", "2020-01-13 00:00:00", "2020-01-31 23:59:59"
+      ))
+    )
     expect_equal(result[["value"]], c(2, 10, 18))
 
   })
diff --git a/tests/testthat/test-spcr_make_data_bundle.R b/tests/testthat/test-spcr_make_data_bundle.R
index d0e9cc6..3a46317 100644
--- a/tests/testthat/test-spcr_make_data_bundle.R
+++ b/tests/testthat/test-spcr_make_data_bundle.R
@@ -24,7 +24,7 @@
     )
   })
 
-"spcr_make_data_bundle: there is a helpful error if the 'events' worksheet is missing" |>
+"spcr_make_data_bundle: there is a helpful error if the 'events' worksheet is missing" |> # nolint
   test_that({
 
     measure_data_no_events <- test_measure_data
@@ -33,7 +33,7 @@
     expect_error(
       spcr_make_data_bundle(
         measure_data_no_events,
-        test_report_config, # note this will still be calling for t charts
+        test_report_config, # Note this will still be calling for t charts
         test_measure_config
       ),
       "The 'events' worksheet is missing from 'measure_data'."
@@ -41,7 +41,7 @@
 
   })
 
-"spcr_make_data_bundle: it is possible to make a data_bundle if no event data is supplied" |>
+"spcr_make_data_bundle: it is possible to make a data_bundle if no event data is supplied" |> # nolint
   test_that({
 
     measure_data_no_events <- test_measure_data
@@ -53,7 +53,7 @@
     )
 
     report_config <- test_report_config |>
-      dplyr::filter(spc_chart_type != "t") # event data needed for t charts
+      dplyr::filter(spc_chart_type != "t") # Event data needed for t charts
 
     expect_no_error(
       spcr_make_data_bundle(
@@ -70,8 +70,9 @@
 "test data bundle process" |>
   test_that({
 
-    # stub out the Sys.time call with a repeating value
-    mockery::stub(spcr_make_data_bundle, "Sys.time", as.POSIXct("2023-12-04 21:25:25"))
+    # Stub out the Sys.time call with a repeating value
+    spcr_make_data_bundle |>
+      mockery::stub("Sys.time", as.POSIXct("2023-12-04 21:25:25"))
 
     db <- spcr_make_data_bundle(
       test_measure_data,
@@ -79,8 +80,8 @@
       test_measure_config
     )
 
-    # some spot checks on the above conversion of the last_data_point to the
-    # appropriate character format
+    # Some spot checks on the above conversion of the last_data_point to the
+    # appropriate character format.
     expect_equal(db[["last_data_point"]][[1]], "222")
     expect_equal(db[["last_data_point"]][[2]], "73%")
     expect_equal(db[["last_data_point"]][[3]], "0.46")
@@ -94,7 +95,8 @@
     out <- spcr_make_data_bundle(
       measure_data = test_measure_data,
       report_config = test_report_config,
-      measure_config = test_measure_config)
+      measure_config = test_measure_config
+    )
 
     expect_length(out, 27)
     expect_equal(nrow(out), nrow(test_report_config))
@@ -125,14 +127,16 @@
 
   })
 
-# this is more properly a test for the check_measure_names() function
-# but it's good to test it as part of the make_bundle() workflow too
+# This is more properly a test for the check_measure_names() function
+# but it's good to test it as part of the make_bundle() workflow too.
 "error for name mismatches before other errors" |>
   test_that({
 
-    # a measure_name mismatch in the measure config will throw a warning
+    # A measure_name mismatch in the measure config will throw a warning
     test_measure_config2 <- test_measure_config |>
-      dplyr::mutate(across("measure_name", \(x) stringr::str_replace(x, "Capacity", "Capaciteeee")))
+      dplyr::mutate(across("measure_name", \(x) {
+        stringr::str_replace(x, "Capacity", "Capaciteeee")
+      }))
 
     expect_warning(
       spcr_make_data_bundle(
@@ -140,13 +144,20 @@
         report_config = test_report_config,
         measure_config = test_measure_config2
       ),
-      "check_measure_names: There is a name mismatch for measure ref: 5. The title in the data bundle is 'Capacity'. The title in the measure config is 'Capaciteeee'."
+      paste0(
+        "check_measure_names: There is a name mismatch for measure ref: 5.\n",
+        "The title in the data bundle is 'Capacity'.\n",
+        "The title in the measure config is 'Capaciteeee'."
+      )
     )
 
-    # a measure_name mismatch in the measure data will throw a warning
+    # A measure_name mismatch in the measure data will throw a warning
     test_measure_data2 <- test_measure_data |>
-      purrr::modify_at("month", \(x)
-      dplyr::mutate(x, across("measure_name", \(x) stringr::str_replace(x, "Widgets", "widgets"))))
+      purrr::modify_at("month", \(x) {
+        dplyr::mutate(x, across("measure_name", \(x) {
+          stringr::str_replace(x, "Widgets", "widgets")
+        }))
+      })
 
     expect_warning(
       spcr_make_data_bundle(
@@ -154,19 +165,24 @@
         report_config = test_report_config,
         measure_config = test_measure_config
       ),
-      "check_measure_names: There is a name mismatch for measure ref: 11. The title in the data bundle is 'widgets'. The title in the measure config is 'Widgets'."
+      paste0(
+        "check_measure_names: There is a name mismatch for measure ref: 11.\n",
+        "The title in the data bundle is 'widgets'.\n",
+        "The title in the measure config is 'Widgets'."
+      )
     )
 
-    # but a measure_name change in the report config should not throw an error
+    # But a measure_name change in the report config should not throw an error
     test_report_config2 <- test_report_config |>
-      dplyr::mutate(across("measure_name", \(x) stringr::str_replace(x, "Widgets", "widgets")))
+      dplyr::mutate(across("measure_name", \(x) {
+        stringr::str_replace(x, "Widgets", "widgets")
+      }))
 
     expect_no_error(
       spcr_make_data_bundle(
         measure_data = test_measure_data,
         report_config = test_report_config2,
         measure_config = test_measure_config
-        )
       )
-
+    )
   })