From 333d6bf1363e8d45fddc86e993571e6755d7b28b Mon Sep 17 00:00:00 2001
From: Kelly Barnes <kbarnes@carpentries.org>
Date: Wed, 8 Nov 2023 08:52:38 -0500
Subject: [PATCH 1/7] introduces scheduling groups fun

---
 R/instructor_training.R | 62 +++++++++++++++++++++++++++++++++++++++++
 1 file changed, 62 insertions(+)

diff --git a/R/instructor_training.R b/R/instructor_training.R
index ee433d0..761ebf4 100644
--- a/R/instructor_training.R
+++ b/R/instructor_training.R
@@ -139,6 +139,68 @@ map_timezones <- function(df) {
   return(df)
 }
 
+#' Create Scheduling Groups
+#'
+#'
+#' @param df Dataframe; The data frame containing timezone information. Comes from Trainer Quarterly Availability Form.
+#'
+#' @return Dataframe; The data frame with an additional 'sched_group'
+#' column.
+#' Throws an error if no matching column or multiple matching columns are found.
+#'
+#' @importFrom stringr str_detect
+#' @importFrom dplyr rename mutate
+#' @export
+#'
+#' @examples
+#' \dontrun{
+#'   # Assume 'data_with_timezones' is a data frame with an appropriate timezone column
+#'   grouped_timezones <- map_timezones(data_with_timezones)
+#'   print(grouped_timezones)
+#' }
+#'
+map_scheduling_group <- function(df) {
+  # The regex pattern matches both spaces and dots
+  matching_cols <-
+    grepl(
+      "^What time zone are you located in",
+      names(df),
+      ignore.case = TRUE
+    )
+  if (sum(matching_cols) > 1) {
+    stop("Error: Multiple matching columns found.")
+  }
+  if (sum(matching_cols) == 0) {
+    stop("No matching column name found.")
+  }
+  col_index <- which(matching_cols)
+  df <- df %>%
+    rename(timezone = names(df)[col_index])
+
+  df <- df %>%
+    mutate(
+      FD_ET = ifelse(
+        str_detect(timezone, "UTC[-]7|UTC[-]6|UTC[-]5|UTC[-]4|UTC[-]3|UTC[-]2[:]?30"), "FD_ET", NA), #EST +/- 2, also includes Newfoundland timezone
+      FD_PT = ifelse(
+        str_detect(timezone, "UTC[-]10|UTC[-]9|UTC[-]8|UTC[-]7|UTC[-]6"), "FD_PT", NA), # PST +/- 2
+      FD_CET = ifelse(
+        str_detect(timezone, "UTC[-]1|UTC[ ]?0|UTC[+]1|UTC[+]2"), "FD_CET", NA), # CEST +/- 2
+      FD_AET = ifelse(
+        str_detect(timezone, "UTC[+]12|UTC[+]11|UTC[+]10|UTC[+]9|UTC[+]8"), "FD_AET", NA), # AEST +/- 2
+      HD_PM_PT = ifelse(
+        str_detect(timezone, "UTC[+]10|UTC[+]11|UTC[+]12|UTC[-]12|UTC[-]11|UTC[-]10|UTC[-]9|UTC[-]8|UTC[-]7|UTC[-]6"), "HD_PM_PT", NA), # PST + 6 hours before and 2 hours after
+      HD_PM_ET = ifelse(
+        str_detect(timezone, "UTC[-]11|UTC[-]10|UTC[-]9|UTC[-]8|UTC[-]7|UTC[-]6|UTC[-]5|UTC[-]4|UTC[-]3"), "HD_PM_ET", NA),
+      HD_PM_CET = ifelse(
+        str_detect(timezone, "UTC[-]5|UTC[-]4|UTC[-]3|UTC[-]2[:]?30|UTC[-]2|UTC[-]1|UTC[ ]?0|UTC[+]1|UTC[+]2|UTC[+]3"), "HD_PM_CET", NA),
+      HD_PM_AET = ifelse(
+        str_detect(timezone, "UTC[+]4|UTC[+]5|UTC[+]6|UTC[+]7|UTC[+]8|UTC[+]9|UTC[+]10|UTC[+]11|UTC[+]12"), "HD_PM_AET", NA)
+    )
+
+
+  return(df)
+}
+
 #' Extract Quarter and Year Information from Data Frame Name
 #'
 #' This function extracts the quarter and year information from a given data frame name.

From 0d2933b4a8096039c2ab817032b23019555526b8 Mon Sep 17 00:00:00 2001
From: Kelly Barnes <kbarnes@carpentries.org>
Date: Fri, 10 Nov 2023 11:11:20 -0500
Subject: [PATCH 2/7] create load_libraries function

---
 DESCRIPTION           |  2 ++
 NAMESPACE             |  3 +++
 R/tools.R             | 35 +++++++++++++++++++++++++++++++++++
 man/load_libraries.Rd | 14 ++++++++++++++
 4 files changed, 54 insertions(+)
 create mode 100644 man/load_libraries.Rd

diff --git a/DESCRIPTION b/DESCRIPTION
index 8cad6ff..08d4771 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -12,10 +12,12 @@ Imports:
   stringr, 
   ggplot2,
   airtabler,
+  paintbrush, 
   lubridate, 
   rlang
 Remotes:
   bergant/airtabler,
+  klbarnes20/paintbrush
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)
 RoxygenNote: 7.2.3
diff --git a/NAMESPACE b/NAMESPACE
index 0aeff55..abd71e3 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -9,6 +9,7 @@ export(calculate_dropout_rate)
 export(calculate_rate)
 export(calculate_reengagement_rate)
 export(calculate_wksurvey_item_mean)
+export(clean_select_all_responses)
 export(count_trainings)
 export(count_trainings_rel_yr)
 export(count_trainings_yr)
@@ -16,7 +17,9 @@ export(extract_year_quarter)
 export(fetch_airtable)
 export(fetch_redash)
 export(generate_plot)
+export(load_libraries)
 export(map_availability)
+export(map_scheduling_group)
 export(map_timezones)
 export(preprocess_trainee_data)
 export(save_plot)
diff --git a/R/tools.R b/R/tools.R
index 444698c..a73c942 100644
--- a/R/tools.R
+++ b/R/tools.R
@@ -48,3 +48,38 @@ set_time_frame <-  function(dat, col, start, end) {
 
   return(df)
 }
+
+#' Clean Select All Survey Response Data
+#'
+#' @param dat
+#' @param col
+#'
+#' @return
+#' @export
+#'
+#' @examples
+clean_select_all_responses <- function(dat, col) {
+  col_sym <- sym(col)
+  response_table <- data %>%
+    separate_rows(col_sym, sep = ",") %>%
+    mutate(col = str_trim(col)) %>%
+    count(col)
+  return(response_table)
+}
+
+#' Load Libraries
+#'
+#' @param libraries
+#'
+#' @return
+#' @export
+#'
+#' @examples
+load_libraries <- function(libraries) {
+  for (lib in libraries) {
+    if (!require(lib, character.only = TRUE)) {
+      install.packages(lib)
+      library(lib, character.only = TRUE)
+    }
+  }
+}
diff --git a/man/load_libraries.Rd b/man/load_libraries.Rd
new file mode 100644
index 0000000..f6002c4
--- /dev/null
+++ b/man/load_libraries.Rd
@@ -0,0 +1,14 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/tools.R
+\name{load_libraries}
+\alias{load_libraries}
+\title{Load Libraries}
+\usage{
+load_libraries(libraries)
+}
+\arguments{
+\item{libraries}{}
+}
+\description{
+Load Libraries
+}

From 5b119528313f563a7f940a520e08e1f168e994ef Mon Sep 17 00:00:00 2001
From: Kelly Barnes <kbarnes@carpentries.org>
Date: Fri, 10 Nov 2023 12:05:17 -0500
Subject: [PATCH 3/7] adds calculate net promoter

---
 NAMESPACE            |  1 +
 R/surveys.R          | 44 ++++++++++++++++++++++++++++++++++++++++++++
 man/calculate_nps.Rd | 14 ++++++++++++++
 3 files changed, 59 insertions(+)
 create mode 100644 R/surveys.R
 create mode 100644 man/calculate_nps.Rd

diff --git a/NAMESPACE b/NAMESPACE
index abd71e3..fe9432d 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -6,6 +6,7 @@ export(calculate_checkout_not_finished)
 export(calculate_checkout_rate)
 export(calculate_checkout_started)
 export(calculate_dropout_rate)
+export(calculate_nps)
 export(calculate_rate)
 export(calculate_reengagement_rate)
 export(calculate_wksurvey_item_mean)
diff --git a/R/surveys.R b/R/surveys.R
new file mode 100644
index 0000000..9e5c802
--- /dev/null
+++ b/R/surveys.R
@@ -0,0 +1,44 @@
+
+
+#' Calculate Net Promoter Score
+#'
+#' #'How to calculate net promoter score: https://monkeylear.com/blog/nps-analysis/
+#'
+#' @param dat
+#' @param col
+#'
+#' @return
+#' @export
+#'
+
+#'
+#' @examples
+calculate_nps <- function(dat, col) {
+  # Ensure col is a character vector of length 1
+  if (!is.character(col) || length(col) != 1) {
+    stop("Error: 'col' should be a single column name as character.")
+  }
+
+  # Check in the column exists in the data frame
+  if (!col %in% names(dat)) {
+    stop("Error: Specified column does not exist in the data frame.")
+  }
+
+  # Check if hte dat in the column is numeric
+  if (!is.numeric(dat[[col]])) {
+    stop("Error: Data in the specified column is not numeric.")
+  }
+  # Calculate net promoter score
+  table <- dat %>%
+    mutate(Category = case_when(
+      .[[col]] <= 6 ~ 'Detractor',
+      .[[col]] %in% 7:8 ~ 'Passive',
+      .[[col]] >= 9 ~ 'Promoter',
+      TRUE ~ NA_character_
+    )) %>%
+    filter(!is.na(Category)) %>%
+    group_by(Category) %>%
+    summarise(Number = n(), .groups = 'drop') %>%
+    mutate(Percent = (Number / sum(Number)))
+
+}
diff --git a/man/calculate_nps.Rd b/man/calculate_nps.Rd
new file mode 100644
index 0000000..30fcb9b
--- /dev/null
+++ b/man/calculate_nps.Rd
@@ -0,0 +1,14 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/surveys.R
+\name{calculate_nps}
+\alias{calculate_nps}
+\title{Calculate Net Promoter Score}
+\usage{
+calculate_nps(dat, col)
+}
+\arguments{
+\item{col}{}
+}
+\description{
+#'How to calculate net promoter score: https://monkeylear.com/blog/nps-analysis/
+}

From 5b7c43916c36991178dac9f4490b8fb2f8527f74 Mon Sep 17 00:00:00 2001
From: Kelly Barnes <kbarnes@carpentries.org>
Date: Fri, 10 Nov 2023 14:17:09 -0500
Subject: [PATCH 4/7] adds new plot functions

---
 NAMESPACE                      |  5 ++++
 R/plotting.R                   | 53 ++++++++++++++++++++++++++++++++++
 man/add_text_geom.Rd           | 20 +++++++++++++
 man/custom_scale_x_discrete.Rd | 14 +++++++++
 man/percent_label.Rd           | 14 +++++++++
 5 files changed, 106 insertions(+)
 create mode 100644 man/add_text_geom.Rd
 create mode 100644 man/custom_scale_x_discrete.Rd
 create mode 100644 man/percent_label.Rd

diff --git a/NAMESPACE b/NAMESPACE
index fe9432d..42b163f 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -1,5 +1,6 @@
 # Generated by roxygen2: do not edit by hand
 
+export(add_text_geom)
 export(badged_n_days)
 export(calculate_avg_time_to_checkout)
 export(calculate_checkout_not_finished)
@@ -14,14 +15,18 @@ export(clean_select_all_responses)
 export(count_trainings)
 export(count_trainings_rel_yr)
 export(count_trainings_yr)
+export(custom_scale_x_discrete)
 export(extract_year_quarter)
 export(fetch_airtable)
 export(fetch_redash)
+export(gather_and_summarise)
 export(generate_plot)
+export(group_by_summarise)
 export(load_libraries)
 export(map_availability)
 export(map_scheduling_group)
 export(map_timezones)
+export(percent_label)
 export(preprocess_trainee_data)
 export(save_plot)
 export(set_time_frame)
diff --git a/R/plotting.R b/R/plotting.R
index 4b5fa38..7b6dd1c 100644
--- a/R/plotting.R
+++ b/R/plotting.R
@@ -57,3 +57,56 @@ save_plot <- function(dir, plot) {
   print(path)
   ggsave(path, plot = plot, device = 'png', dpi = 300, width = 4, height = 3)
 }
+
+#' Add Data Labels to Plot
+#'
+#' @param label_type
+#' @param accuracy
+#' @param color
+#' @param vjust
+#' @param fontface
+#'
+#' @return
+#' @export
+#'
+#' @examples
+add_text_geom <- function(label_type = "count", accuracy = 0.1, color = "white", vjust = 1.6, fontface = "bold") {
+  if (label_type == "count") {
+    plot + geom_text(aes(label = count), color = color, vjust = vjust, fontface = fontface)
+  } else if (label_type == "percent") {
+    geom_text(aes(label = scales::label_percent(accuracy = accuracy)(percent)), color = color, vjust = vjust, fontface = fontface)
+  }
+}
+
+#' Format and Text Wrap X Axis Labels
+#'
+#' @param labels
+#' @param wrap_width
+#'
+#' @return
+#' @export
+#'
+#' @examples
+custom_scale_x_discrete <- function(labels, wrap_width = 15) {
+  scale_x_discrete(
+    drop = FALSE,
+    labels = function(x) lapply(
+      strwrap(labels, width = wrap_width, simplify = FALSE),
+      paste,
+      collapse = "\n"
+    )
+  )
+}
+
+#' Add Percent Sign to Data Label
+#'
+#' @param x
+#' @param decimal
+#'
+#' @return
+#' @export
+#'
+#' @examples
+percent_label <- function(x, decimal = 1) {
+  paste0(round(x, decimal), "%")
+}
diff --git a/man/add_text_geom.Rd b/man/add_text_geom.Rd
new file mode 100644
index 0000000..d614256
--- /dev/null
+++ b/man/add_text_geom.Rd
@@ -0,0 +1,20 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/plotting.R
+\name{add_text_geom}
+\alias{add_text_geom}
+\title{Add Data Labels to Plot}
+\usage{
+add_text_geom(
+  label_type = "count",
+  accuracy = 0.1,
+  color = "white",
+  vjust = 1.6,
+  fontface = "bold"
+)
+}
+\arguments{
+\item{fontface}{}
+}
+\description{
+Add Data Labels to Plot
+}
diff --git a/man/custom_scale_x_discrete.Rd b/man/custom_scale_x_discrete.Rd
new file mode 100644
index 0000000..148451f
--- /dev/null
+++ b/man/custom_scale_x_discrete.Rd
@@ -0,0 +1,14 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/plotting.R
+\name{custom_scale_x_discrete}
+\alias{custom_scale_x_discrete}
+\title{Format and Text Wrap X Axis Labels}
+\usage{
+custom_scale_x_discrete(labels, wrap_width = 15)
+}
+\arguments{
+\item{wrap_width}{}
+}
+\description{
+Format and Text Wrap X Axis Labels
+}
diff --git a/man/percent_label.Rd b/man/percent_label.Rd
new file mode 100644
index 0000000..613441e
--- /dev/null
+++ b/man/percent_label.Rd
@@ -0,0 +1,14 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/plotting.R
+\name{percent_label}
+\alias{percent_label}
+\title{Add Percent Sign to Data Label}
+\usage{
+percent_label(x, decimal = 1)
+}
+\arguments{
+\item{decimal}{}
+}
+\description{
+Add Percent Sign to Data Label
+}

From da57e2ae1b5af4911152d90c5b00a2aecd4dd0db Mon Sep 17 00:00:00 2001
From: Kelly Barnes <kbarnes@carpentries.org>
Date: Fri, 10 Nov 2023 14:17:32 -0500
Subject: [PATCH 5/7] adds new data manipulation funs

---
 R/surveys.R                       | 40 +++++++++++++++++++++++++++++++
 R/tools.R                         | 28 ++++++++++++++++++++++
 man/clean_select_all_responses.Rd | 14 +++++++++++
 man/gather_and_summarise.Rd       | 14 +++++++++++
 man/group_by_summarise.Rd         | 14 +++++++++++
 man/map_scheduling_group.Rd       | 27 +++++++++++++++++++++
 6 files changed, 137 insertions(+)
 create mode 100644 man/clean_select_all_responses.Rd
 create mode 100644 man/gather_and_summarise.Rd
 create mode 100644 man/group_by_summarise.Rd
 create mode 100644 man/map_scheduling_group.Rd

diff --git a/R/surveys.R b/R/surveys.R
index 9e5c802..81e1521 100644
--- a/R/surveys.R
+++ b/R/surveys.R
@@ -42,3 +42,43 @@ calculate_nps <- function(dat, col) {
     mutate(Percent = (Number / sum(Number)))
 
 }
+
+#' Gather Questions into One Table to Graph Together
+#'
+#' @param dat
+#' @param questions
+#' @param levels
+#' @param labels
+#'
+#' @return
+#' @export
+#'
+#' @examples
+gather_and_summarise <- function(dat, questions, levels, labels){
+  # Validation Checks
+  if (!is.data.frame(dat)) {
+    stop("Error: 'dat' should be a data frame.")
+  }
+
+  if (!all(questions %in% names(dat))) {
+    stop("Error: Some questions in 'questions' are not column names in 'dat'.")
+  }
+
+  if (length(levels) != length(labels)) {
+    stop("Error: The length of 'levels' and 'labels' must be the same.")
+  }
+
+  # Convert the selected columns into a long format
+  tryCatch({
+    table <- dat %>%
+      select(all_of(questions)) %>%
+      gather(key = "Question", value = "Answer") %>%
+      mutate(Answer = factor(Answer, levels = levels, labels = labels)) %>%
+      group_by(Question, Answer) %>%
+      summarize(Number = n())
+
+    return(table)
+  }, error = function(e) {
+    stop("Error in processing data: ", e$message)
+  })
+}
diff --git a/R/tools.R b/R/tools.R
index a73c942..155cff5 100644
--- a/R/tools.R
+++ b/R/tools.R
@@ -83,3 +83,31 @@ load_libraries <- function(libraries) {
     }
   }
 }
+
+#' Group By and Summarise
+#'
+#' @param dat
+#' @param col
+#' @param convert_to_percent
+#'
+#' @return
+#' @export
+#'
+#' @examples
+group_by_summarise <- function(dat, col, convert_to_percent = FALSE){
+  col_sym <- sym(col) #convert column name to symbol
+  table <- dat %>%
+    group_by(!!col_sym) %>% # unquote the symbol
+    summarise(count = n()) %>%
+    arrange(desc(count))
+
+  # Optionally convert count to percent
+  if (convert_to_percent) {
+    total_count <- sum(table$count)
+    table <- table %>%
+      mutate(percent = count / total_count * 100)
+  }
+
+  return(table)
+
+}
diff --git a/man/clean_select_all_responses.Rd b/man/clean_select_all_responses.Rd
new file mode 100644
index 0000000..7564bb7
--- /dev/null
+++ b/man/clean_select_all_responses.Rd
@@ -0,0 +1,14 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/tools.R
+\name{clean_select_all_responses}
+\alias{clean_select_all_responses}
+\title{Clean Select All Survey Response Data}
+\usage{
+clean_select_all_responses(dat, col)
+}
+\arguments{
+\item{col}{}
+}
+\description{
+Clean Select All Survey Response Data
+}
diff --git a/man/gather_and_summarise.Rd b/man/gather_and_summarise.Rd
new file mode 100644
index 0000000..8652278
--- /dev/null
+++ b/man/gather_and_summarise.Rd
@@ -0,0 +1,14 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/surveys.R
+\name{gather_and_summarise}
+\alias{gather_and_summarise}
+\title{Gather Questions into One Table to Graph Together}
+\usage{
+gather_and_summarise(dat, questions, levels, labels)
+}
+\arguments{
+\item{labels}{}
+}
+\description{
+Gather Questions into One Table to Graph Together
+}
diff --git a/man/group_by_summarise.Rd b/man/group_by_summarise.Rd
new file mode 100644
index 0000000..f8d0df3
--- /dev/null
+++ b/man/group_by_summarise.Rd
@@ -0,0 +1,14 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/tools.R
+\name{group_by_summarise}
+\alias{group_by_summarise}
+\title{Group By and Summarise}
+\usage{
+group_by_summarise(dat, col, convert_to_percent = FALSE)
+}
+\arguments{
+\item{convert_to_percent}{}
+}
+\description{
+Group By and Summarise
+}
diff --git a/man/map_scheduling_group.Rd b/man/map_scheduling_group.Rd
new file mode 100644
index 0000000..78dee48
--- /dev/null
+++ b/man/map_scheduling_group.Rd
@@ -0,0 +1,27 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/instructor_training.R
+\name{map_scheduling_group}
+\alias{map_scheduling_group}
+\title{Create Scheduling Groups}
+\usage{
+map_scheduling_group(df)
+}
+\arguments{
+\item{df}{Dataframe; The data frame containing timezone information. Comes from Trainer Quarterly Availability Form.}
+}
+\value{
+Dataframe; The data frame with an additional 'sched_group'
+column.
+Throws an error if no matching column or multiple matching columns are found.
+}
+\description{
+Create Scheduling Groups
+}
+\examples{
+\dontrun{
+  # Assume 'data_with_timezones' is a data frame with an appropriate timezone column
+  grouped_timezones <- map_timezones(data_with_timezones)
+  print(grouped_timezones)
+}
+
+}

From 91b19143069216edc3222e7e55241e6f7dc24c2b Mon Sep 17 00:00:00 2001
From: Kelly Barnes <kbarnes@carpentries.org>
Date: Thu, 23 Nov 2023 10:49:57 -0500
Subject: [PATCH 6/7] documents and fixes tests

---
 DESCRIPTION                               |  9 ++-
 NAMESPACE                                 |  9 ++-
 R/instructor_training.R                   |  6 +-
 R/plotting.R                              | 80 +++++++++++++++++------
 R/surveys.R                               | 46 +++++++++----
 R/tools.R                                 | 64 +++++++++++++-----
 man/add_text_geom.Rd                      | 28 ++++++--
 man/calculate_nps.Rd                      | 21 +++++-
 man/clean_select_all_responses.Rd         | 19 +++++-
 man/custom_scale_x_discrete.Rd            | 29 +++++++-
 man/extract_year_quarter.Rd               |  2 +-
 man/gather_and_summarise.Rd               | 26 +++++++-
 man/group_by_summarise.Rd                 | 22 ++++++-
 man/load_libraries.Rd                     | 14 +++-
 man/percent_label.Rd                      | 17 ++++-
 tests/testthat/test-instructor_training.R | 22 ++++---
 16 files changed, 318 insertions(+), 96 deletions(-)

diff --git a/DESCRIPTION b/DESCRIPTION
index 08d4771..ccfcc03 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -8,16 +8,15 @@ Description: What the package does (one paragraph).
 License: MIT + file LICENSE
 Imports: 
   dplyr,
-  googlesheets4,
   stringr, 
   ggplot2,
   airtabler,
-  paintbrush, 
   lubridate, 
-  rlang
+  rlang,
+  scales,
+  tidyr
 Remotes:
-  bergant/airtabler,
-  klbarnes20/paintbrush
+  bergant/airtabler
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)
 RoxygenNote: 7.2.3
diff --git a/NAMESPACE b/NAMESPACE
index 42b163f..172186d 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -36,9 +36,13 @@ export(trainees_n_days)
 import(dplyr)
 importFrom(airtabler,airtable)
 importFrom(dplyr,case_when)
+importFrom(dplyr,count)
 importFrom(dplyr,filter)
+importFrom(dplyr,group_by)
 importFrom(dplyr,mutate)
 importFrom(dplyr,rename)
+importFrom(dplyr,select)
+importFrom(dplyr,summarize)
 importFrom(ggplot2,aes_string)
 importFrom(ggplot2,facet_grid)
 importFrom(ggplot2,geom_col)
@@ -46,7 +50,10 @@ importFrom(ggplot2,geom_text)
 importFrom(ggplot2,ggplot)
 importFrom(ggplot2,ggsave)
 importFrom(lubridate,year)
-importFrom(paintbrush,theme_carpentries)
 importFrom(rlang,sym)
+importFrom(scales,label_percent)
 importFrom(stringr,str_detect)
+importFrom(stringr,str_trim)
+importFrom(tidyr,gather)
+importFrom(tidyr,separate_rows)
 importFrom(utils,read.csv)
diff --git a/R/instructor_training.R b/R/instructor_training.R
index 761ebf4..ce6c75e 100644
--- a/R/instructor_training.R
+++ b/R/instructor_training.R
@@ -119,7 +119,7 @@ map_timezones <- function(df) {
       stringr::str_detect(timezone, "\\bUTC[-]2[:]?30\\b") ~ "TZ3",
       stringr::str_detect(timezone, "\\bUTC[-]3\\b") ~ "TZ3",
       stringr::str_detect(timezone, "\\bUTC[-]1\\b") ~ "TZ3",
-      stringr::str_detect(timezone, "\\bUTC[ ]?0\\b") ~ "TZ4",
+      stringr::str_detect(timezone, "\\bUTC[)]\\b") ~ "TZ4",
       stringr::str_detect(timezone, "\\bUTC[+]1\\b") ~ "TZ4",
       stringr::str_detect(timezone, "\\bUTC[+]2\\b") ~ "TZ4",
       stringr::str_detect(timezone, "\\bUTC[+]3\\b") ~ "TZ4",
@@ -184,7 +184,7 @@ map_scheduling_group <- function(df) {
       FD_PT = ifelse(
         str_detect(timezone, "UTC[-]10|UTC[-]9|UTC[-]8|UTC[-]7|UTC[-]6"), "FD_PT", NA), # PST +/- 2
       FD_CET = ifelse(
-        str_detect(timezone, "UTC[-]1|UTC[ ]?0|UTC[+]1|UTC[+]2"), "FD_CET", NA), # CEST +/- 2
+        str_detect(timezone, "UTC[-]1|UTC[)]|UTC[+]1|UTC[+]2"), "FD_CET", NA), # CEST +/- 2
       FD_AET = ifelse(
         str_detect(timezone, "UTC[+]12|UTC[+]11|UTC[+]10|UTC[+]9|UTC[+]8"), "FD_AET", NA), # AEST +/- 2
       HD_PM_PT = ifelse(
@@ -204,7 +204,7 @@ map_scheduling_group <- function(df) {
 #' Extract Quarter and Year Information from Data Frame Name
 #'
 #' This function extracts the quarter and year information from a given data frame name.
-#' The name is expected to be in the format "Q[1-4]_[YYYY]" where [1-4] is the quarter and [YYYY] is the year.
+#' The name is expected to be in the format "Q(1-4)_(YYYY)" where (1-4) is the quarter and (YYYY) is the year.
 #'
 #' @param filename Dataframe; The data frame whose name you want to analyze.
 #'
diff --git a/R/plotting.R b/R/plotting.R
index 7b6dd1c..70e1187 100644
--- a/R/plotting.R
+++ b/R/plotting.R
@@ -13,7 +13,6 @@
 #' @return A ggplot object representing the generated plot.
 #' @export
 #' @importFrom ggplot2 ggplot aes_string geom_col geom_text facet_grid
-#' @importFrom paintbrush theme_carpentries
 #
 #'
 #' @examples
@@ -27,8 +26,7 @@ generate_plot <- function(dat, x, y, fill = NULL) {
   plot <- ggplot(dat, aes_string(x = x, y = y, fill = fill)) +
     geom_col(position = position_dodge(width = 0.9)) +
     geom_text(aes(label = after_stat(y)), stat = "identity", vjust = -0.3, position = position_dodge(width = 0.9)) +
-    facet_grid(year ~ quarter) +
-    theme_carpentries()
+    facet_grid(year ~ quarter)
   return(plot)
 }
 
@@ -58,35 +56,67 @@ save_plot <- function(dir, plot) {
   ggsave(path, plot = plot, device = 'png', dpi = 300, width = 4, height = 3)
 }
 
-#' Add Data Labels to Plot
-#'
-#' @param label_type
-#' @param accuracy
-#' @param color
-#' @param vjust
-#' @param fontface
-#'
-#' @return
+#' Add Data Labels to a ggplot2 Plot
+#'
+#' This function adds text labels to a ggplot2 plot. It supports two types of labels: counts and percentages.
+#' The labels can be customized in terms of their accuracy, color, vertical adjustment, and font face.
+#'
+#' @param label_type A character string specifying the type of label to add.
+#'                   Acceptable values are "count" for count labels and "percent" for percentage labels.
+#' @param accuracy An optional numeric value specifying the number of decimal places for percentage labels.
+#'                 Only applicable if `label_type` is "percent". Default is 0.1.
+#' @param color A character string specifying the color of the text labels. Default is "white".
+#' @param vjust A numeric value for vertical adjustment of the text labels.
+#'              Positive values move text up, and negative values move it down. Default is 1.6.
+#' @param fontface A character string specifying the font face for text labels.
+#'                 Common values are "plain", "bold", "italic", "bold.italic". Default is "bold".
+#' @param nudge_x A numeric value specifying horizontal adjustment of the text labels.
+#'                Positive values move text to the right, and negative values move it to the left. Default is 0.
+#'
+#' @importFrom ggplot2 geom_text
+#' @importFrom scales label_percent
+#'
+#' @return A ggplot2 layer with the specified text labels added.
 #' @export
 #'
 #' @examples
-add_text_geom <- function(label_type = "count", accuracy = 0.1, color = "white", vjust = 1.6, fontface = "bold") {
+
+
+add_text_geom <- function(label_type = "count", accuracy = 0.1, color = "white", vjust = 1.6, fontface = "bold", nudge_x = 0) {
   if (label_type == "count") {
-    plot + geom_text(aes(label = count), color = color, vjust = vjust, fontface = fontface)
+    plot + geom_text(aes(label = count), color = color, vjust = vjust, nudge_x = nudge_x, fontface = fontface)
   } else if (label_type == "percent") {
     geom_text(aes(label = scales::label_percent(accuracy = accuracy)(percent)), color = color, vjust = vjust, fontface = fontface)
   }
 }
 
-#' Format and Text Wrap X Axis Labels
+#' Format and Text Wrap X Axis Labels in ggplot2
+#'
+#' This function applies text wrapping to x-axis labels in a ggplot2 plot.
+#' It allows for customizing the width of the wrap, making long labels more readable by breaking them into multiple lines.
 #'
-#' @param labels
-#' @param wrap_width
+#' @param labels A vector of labels to be used for the x-axis.
+#'               These labels should correspond to the categories or values present on the x-axis.
+#' @param wrap_width An integer specifying the maximum width (in characters) before wrapping a label onto the next line.
+#'                   The default value is 15.
 #'
-#' @return
+#' @return A ggplot2 scale layer, specifically a modified `scale_x_discrete`,
+#'         with the labels formatted to wrap text based on the specified `wrap_width`.
 #' @export
 #'
 #' @examples
+#' # Example using the diamonds dataset from ggplot2
+#' library(ggplot2)
+#' data(diamonds)
+#'
+#' # Create artificial long labels for illustration
+#' long_labels <- c("Fair Quality Cut", "Good Quality Cut", "Very Good Quality Cut",
+#'                  "Premium Quality Cut", "Ideal Quality Cut")
+#' names(long_labels) <- levels(diamonds$cut)
+#'
+#' basic_plot <- ggplot(diamonds, aes(x = cut, y = price)) + geom_bar(stat = "identity")
+#' # Apply custom scale with wrapped labels
+#' basic_plot + custom_scale_x_discrete(labels = long_labels, wrap_width = 10)
 custom_scale_x_discrete <- function(labels, wrap_width = 15) {
   scale_x_discrete(
     drop = FALSE,
@@ -100,13 +130,21 @@ custom_scale_x_discrete <- function(labels, wrap_width = 15) {
 
 #' Add Percent Sign to Data Label
 #'
-#' @param x
-#' @param decimal
+#' This function formats numeric values as percentages. It rounds the numbers to the specified decimal places and appends a percent sign.
+#'
+#' @param x Numeric vector; the values to be formatted as percentages.
+#' @param decimal Integer; the number of decimal places to round the numeric values.
+#'               Defaults to 1, indicating one decimal place.
 #'
-#' @return
+#' @return A character vector with the numeric values formatted as percentages.
 #' @export
 #'
 #' @examples
+#' # Example usage of percent_label
+#' numeric_values <- c(0.123, 0.456, 0.789)
+#' percent_labels <- percent_label(numeric_values)
+#' print(percent_labels)
+#' # Output: "12.3%", "45.6%", "78.9%"
 percent_label <- function(x, decimal = 1) {
   paste0(round(x, decimal), "%")
 }
diff --git a/R/surveys.R b/R/surveys.R
index 81e1521..90a2c0b 100644
--- a/R/surveys.R
+++ b/R/surveys.R
@@ -1,18 +1,24 @@
 
 
-#' Calculate Net Promoter Score
+#' Calculate Net Promoter Score (NPS)
 #'
-#' #'How to calculate net promoter score: https://monkeylear.com/blog/nps-analysis/
+#' This function calculates the Net Promoter Score from survey data based on respondents' ratings.
+#' NPS is a measure of customer loyalty and is calculated using the formula:
+#' Percentage of Promoters - Percentage of Detractors.
+#' For more information on NPS, visit: https://monkeylearn.com/blog/nps-analysis/
 #'
-#' @param dat
-#' @param col
+#' @param dat A data frame containing survey data.
+#' @param col A character string specifying the name of the column containing NPS ratings (expected to be numeric).
 #'
-#' @return
+#' @return A data frame summarizing the number and percentage of respondents in each category:
+#'         Promoters, Passives, and Detractors.
 #' @export
-#'
-
 #'
 #' @examples
+#' # Example usage with a sample data frame
+#' sample_data <- data.frame(rating = sample(0:10, 100, replace = TRUE))
+#' nps_result <- calculate_nps(sample_data, "rating")
+#' print(nps_result)
 calculate_nps <- function(dat, col) {
   # Ensure col is a character vector of length 1
   if (!is.character(col) || length(col) != 1) {
@@ -43,17 +49,31 @@ calculate_nps <- function(dat, col) {
 
 }
 
-#' Gather Questions into One Table to Graph Together
+#' Gather Questions into One Table for Graphing
+#'
+#' This function transforms survey data by converting selected question columns into a long format
+#' suitable for comparison and graphing. It facilitates analysis across multiple questions.
+#'
+#' @param dat A data frame containing survey data.
+#' @param questions A character vector of column names in 'dat' representing the questions to be summarized.
+#' @param levels A vector of the levels (possible responses) for the questions.
+#' @param labels A vector of labels corresponding to the 'levels' vector for re-labeling responses.
 #'
-#' @param dat
-#' @param questions
-#' @param levels
-#' @param labels
+#' @importFrom dplyr select mutate group_by summarize
+#' @importFrom tidyr gather
 #'
-#' @return
+#' @return A data frame in long format, with each row representing a response to a question,
+#'         along with the count of each response type.
 #' @export
 #'
 #' @examples
+#' # Example usage with a sample data frame
+#' sample_data <- data.frame(Q1 = sample(1:5, 100, replace = TRUE), Q2 = sample(1:5, 100, replace = TRUE))
+#' questions <- c("Q1", "Q2")
+#' levels <- 1:5
+#' labels <- c("Strongly Disagree", "Disagree", "Neutral", "Agree", "Strongly Agree")
+#' summarised_data <- gather_and_summarise(sample_data, questions, levels, labels)
+#' print(summarised_data)
 gather_and_summarise <- function(dat, questions, levels, labels){
   # Validation Checks
   if (!is.data.frame(dat)) {
diff --git a/R/tools.R b/R/tools.R
index 155cff5..b62a145 100644
--- a/R/tools.R
+++ b/R/tools.R
@@ -49,32 +49,49 @@ set_time_frame <-  function(dat, col, start, end) {
   return(df)
 }
 
-#' Clean Select All Survey Response Data
+#' Clean and Summarize "Select All That Apply" Survey Responses
 #'
-#' @param dat
-#' @param col
+#' This function processes survey data where respondents could select multiple answers (e.g., "Select all that apply" questions).
+#' It separates the responses, trims whitespace, and counts the occurrences of each unique response.
 #'
-#' @return
+#' @param dat A data frame containing the survey data.
+#' @param col A character string specifying the name of the column with the "select all" responses.
+#'
+#' @importFrom dplyr mutate count
+#' @importFrom tidyr separate_rows
+#' @importFrom stringr str_trim
+#'
+#' @return A data frame with each row representing a unique response from the specified column
+#'         and its count in the survey.
 #' @export
 #'
 #' @examples
+#' # Example usage with a sample data frame
+#' sample_data <- data.frame(responses = c("Option 1, Option 2", "Option 2, Option 3", "Option 1, Option 3, Option 2","Option 2","Option 3"))
+#' cleaned_responses <- clean_select_all_responses(sample_data, "responses")
+#' print(cleaned_responses)
 clean_select_all_responses <- function(dat, col) {
   col_sym <- sym(col)
-  response_table <- data %>%
-    separate_rows(col_sym, sep = ",") %>%
-    mutate(col = str_trim(col)) %>%
-    count(col)
+  response_table <- dat %>%
+    separate_rows(!!col_sym, sep = ",") %>%
+    mutate(!!col_sym := str_trim(!!col_sym)) %>%
+    count(!!col_sym)
   return(response_table)
 }
 
-#' Load Libraries
+#' Load a List of R Libraries, Installing if Necessary
+#'
+#' This function iterates through a list of R package names, checks if they are installed,
+#' and loads them into the R session. It installs any package that is not already installed.
 #'
-#' @param libraries
+#' @param libraries A character vector of R package names to be loaded.
 #'
-#' @return
+#' @return None; the function is called for its side effects (loading libraries).
 #' @export
 #'
 #' @examples
+#' # Example usage to load dplyr and ggplot2
+#' load_libraries(c("dplyr", "ggplot2"))
 load_libraries <- function(libraries) {
   for (lib in libraries) {
     if (!require(lib, character.only = TRUE)) {
@@ -84,28 +101,39 @@ load_libraries <- function(libraries) {
   }
 }
 
-#' Group By and Summarise
+#' Group Data by a Specified Column and Summarize Counts
 #'
-#' @param dat
-#' @param col
-#' @param convert_to_percent
+#' This function groups a data frame by the values in a specified column, then calculates
+#' the count of records in each group. Optionally, it can convert these counts into percentages.
 #'
-#' @return
+#' @param dat A data frame to be analyzed.
+#' @param col A character string specifying the column name by which to group the data.
+#' @param convert_to_percent A logical value; if TRUE, convert counts to percentages.
+#'                           Default is FALSE.
+#'
+#' @return A data frame with each group (from the specified column) and its count (and optionally, percentage).
 #' @export
 #'
 #' @examples
+#' # Example usage with a sample data frame
+#' set.seed(1)  # for reproducibility
+#' sample_data <- data.frame(category = sample(c("A", "B", "C"), 120, replace = TRUE, prob = c(0.3, 0.5, 0.2)))
+
+#' summary_table <- group_by_summarise(sample_data, "category", convert_to_percent = TRUE)
+#' print(summary_table)
 group_by_summarise <- function(dat, col, convert_to_percent = FALSE){
   col_sym <- sym(col) #convert column name to symbol
   table <- dat %>%
     group_by(!!col_sym) %>% # unquote the symbol
-    summarise(count = n()) %>%
+    summarise(count = n(), .groups = 'drop') %>%
     arrange(desc(count))
 
   # Optionally convert count to percent
   if (convert_to_percent) {
     total_count <- sum(table$count)
+
     table <- table %>%
-      mutate(percent = count / total_count * 100)
+      mutate(percent = (count / total_count) * 100)
   }
 
   return(table)
diff --git a/man/add_text_geom.Rd b/man/add_text_geom.Rd
index d614256..ad23076 100644
--- a/man/add_text_geom.Rd
+++ b/man/add_text_geom.Rd
@@ -2,19 +2,39 @@
 % Please edit documentation in R/plotting.R
 \name{add_text_geom}
 \alias{add_text_geom}
-\title{Add Data Labels to Plot}
+\title{Add Data Labels to a ggplot2 Plot}
 \usage{
 add_text_geom(
   label_type = "count",
   accuracy = 0.1,
   color = "white",
   vjust = 1.6,
-  fontface = "bold"
+  fontface = "bold",
+  nudge_x = 0
 )
 }
 \arguments{
-\item{fontface}{}
+\item{label_type}{A character string specifying the type of label to add.
+Acceptable values are "count" for count labels and "percent" for percentage labels.}
+
+\item{accuracy}{An optional numeric value specifying the number of decimal places for percentage labels.
+Only applicable if \code{label_type} is "percent". Default is 0.1.}
+
+\item{color}{A character string specifying the color of the text labels. Default is "white".}
+
+\item{vjust}{A numeric value for vertical adjustment of the text labels.
+Positive values move text up, and negative values move it down. Default is 1.6.}
+
+\item{fontface}{A character string specifying the font face for text labels.
+Common values are "plain", "bold", "italic", "bold.italic". Default is "bold".}
+
+\item{nudge_x}{A numeric value specifying horizontal adjustment of the text labels.
+Positive values move text to the right, and negative values move it to the left. Default is 0.}
+}
+\value{
+A ggplot2 layer with the specified text labels added.
 }
 \description{
-Add Data Labels to Plot
+This function adds text labels to a ggplot2 plot. It supports two types of labels: counts and percentages.
+The labels can be customized in terms of their accuracy, color, vertical adjustment, and font face.
 }
diff --git a/man/calculate_nps.Rd b/man/calculate_nps.Rd
index 30fcb9b..17eaf2f 100644
--- a/man/calculate_nps.Rd
+++ b/man/calculate_nps.Rd
@@ -2,13 +2,28 @@
 % Please edit documentation in R/surveys.R
 \name{calculate_nps}
 \alias{calculate_nps}
-\title{Calculate Net Promoter Score}
+\title{Calculate Net Promoter Score (NPS)}
 \usage{
 calculate_nps(dat, col)
 }
 \arguments{
-\item{col}{}
+\item{dat}{A data frame containing survey data.}
+
+\item{col}{A character string specifying the name of the column containing NPS ratings (expected to be numeric).}
+}
+\value{
+A data frame summarizing the number and percentage of respondents in each category:
+Promoters, Passives, and Detractors.
 }
 \description{
-#'How to calculate net promoter score: https://monkeylear.com/blog/nps-analysis/
+This function calculates the Net Promoter Score from survey data based on respondents' ratings.
+NPS is a measure of customer loyalty and is calculated using the formula:
+Percentage of Promoters - Percentage of Detractors.
+For more information on NPS, visit: https://monkeylearn.com/blog/nps-analysis/
+}
+\examples{
+# Example usage with a sample data frame
+sample_data <- data.frame(rating = sample(0:10, 100, replace = TRUE))
+nps_result <- calculate_nps(sample_data, "rating")
+print(nps_result)
 }
diff --git a/man/clean_select_all_responses.Rd b/man/clean_select_all_responses.Rd
index 7564bb7..e695fd3 100644
--- a/man/clean_select_all_responses.Rd
+++ b/man/clean_select_all_responses.Rd
@@ -2,13 +2,26 @@
 % Please edit documentation in R/tools.R
 \name{clean_select_all_responses}
 \alias{clean_select_all_responses}
-\title{Clean Select All Survey Response Data}
+\title{Clean and Summarize "Select All That Apply" Survey Responses}
 \usage{
 clean_select_all_responses(dat, col)
 }
 \arguments{
-\item{col}{}
+\item{dat}{A data frame containing the survey data.}
+
+\item{col}{A character string specifying the name of the column with the "select all" responses.}
+}
+\value{
+A data frame with each row representing a unique response from the specified column
+and its count in the survey.
 }
 \description{
-Clean Select All Survey Response Data
+This function processes survey data where respondents could select multiple answers (e.g., "Select all that apply" questions).
+It separates the responses, trims whitespace, and counts the occurrences of each unique response.
+}
+\examples{
+# Example usage with a sample data frame
+sample_data <- data.frame(responses = c("Option 1, Option 2", "Option 2, Option 3", "Option 1, Option 3, Option 2","Option 2","Option 3"))
+cleaned_responses <- clean_select_all_responses(sample_data, "responses")
+print(cleaned_responses)
 }
diff --git a/man/custom_scale_x_discrete.Rd b/man/custom_scale_x_discrete.Rd
index 148451f..342280e 100644
--- a/man/custom_scale_x_discrete.Rd
+++ b/man/custom_scale_x_discrete.Rd
@@ -2,13 +2,36 @@
 % Please edit documentation in R/plotting.R
 \name{custom_scale_x_discrete}
 \alias{custom_scale_x_discrete}
-\title{Format and Text Wrap X Axis Labels}
+\title{Format and Text Wrap X Axis Labels in ggplot2}
 \usage{
 custom_scale_x_discrete(labels, wrap_width = 15)
 }
 \arguments{
-\item{wrap_width}{}
+\item{labels}{A vector of labels to be used for the x-axis.
+These labels should correspond to the categories or values present on the x-axis.}
+
+\item{wrap_width}{An integer specifying the maximum width (in characters) before wrapping a label onto the next line.
+The default value is 15.}
+}
+\value{
+A ggplot2 scale layer, specifically a modified \code{scale_x_discrete},
+with the labels formatted to wrap text based on the specified \code{wrap_width}.
 }
 \description{
-Format and Text Wrap X Axis Labels
+This function applies text wrapping to x-axis labels in a ggplot2 plot.
+It allows for customizing the width of the wrap, making long labels more readable by breaking them into multiple lines.
+}
+\examples{
+# Example using the diamonds dataset from ggplot2
+library(ggplot2)
+data(diamonds)
+
+# Create artificial long labels for illustration
+long_labels <- c("Fair Quality Cut", "Good Quality Cut", "Very Good Quality Cut",
+                 "Premium Quality Cut", "Ideal Quality Cut")
+names(long_labels) <- levels(diamonds$cut)
+
+basic_plot <- ggplot(diamonds, aes(x = cut, y = price)) + geom_bar(stat = "identity")
+# Apply custom scale with wrapped labels
+basic_plot + custom_scale_x_discrete(labels = long_labels, wrap_width = 10)
 }
diff --git a/man/extract_year_quarter.Rd b/man/extract_year_quarter.Rd
index 9ed8fa4..1b6337f 100644
--- a/man/extract_year_quarter.Rd
+++ b/man/extract_year_quarter.Rd
@@ -15,7 +15,7 @@ The function will throw an error if the name does not match the expected format.
 }
 \description{
 This function extracts the quarter and year information from a given data frame name.
-The name is expected to be in the format "Q\link{1-4}_\link{YYYY}" where \link{1-4} is the quarter and \link{YYYY} is the year.
+The name is expected to be in the format "Q(1-4)_(YYYY)" where (1-4) is the quarter and (YYYY) is the year.
 }
 \examples{
 \dontrun{
diff --git a/man/gather_and_summarise.Rd b/man/gather_and_summarise.Rd
index 8652278..cd462a5 100644
--- a/man/gather_and_summarise.Rd
+++ b/man/gather_and_summarise.Rd
@@ -2,13 +2,33 @@
 % Please edit documentation in R/surveys.R
 \name{gather_and_summarise}
 \alias{gather_and_summarise}
-\title{Gather Questions into One Table to Graph Together}
+\title{Gather Questions into One Table for Graphing}
 \usage{
 gather_and_summarise(dat, questions, levels, labels)
 }
 \arguments{
-\item{labels}{}
+\item{dat}{A data frame containing survey data.}
+
+\item{questions}{A character vector of column names in 'dat' representing the questions to be summarized.}
+
+\item{levels}{A vector of the levels (possible responses) for the questions.}
+
+\item{labels}{A vector of labels corresponding to the 'levels' vector for re-labeling responses.}
+}
+\value{
+A data frame in long format, with each row representing a response to a question,
+along with the count of each response type.
 }
 \description{
-Gather Questions into One Table to Graph Together
+This function transforms survey data by converting selected question columns into a long format
+suitable for comparison and graphing. It facilitates analysis across multiple questions.
+}
+\examples{
+# Example usage with a sample data frame
+sample_data <- data.frame(Q1 = sample(1:5, 100, replace = TRUE), Q2 = sample(1:5, 100, replace = TRUE))
+questions <- c("Q1", "Q2")
+levels <- 1:5
+labels <- c("Strongly Disagree", "Disagree", "Neutral", "Agree", "Strongly Agree")
+summarised_data <- gather_and_summarise(sample_data, questions, levels, labels)
+print(summarised_data)
 }
diff --git a/man/group_by_summarise.Rd b/man/group_by_summarise.Rd
index f8d0df3..d25ee70 100644
--- a/man/group_by_summarise.Rd
+++ b/man/group_by_summarise.Rd
@@ -2,13 +2,29 @@
 % Please edit documentation in R/tools.R
 \name{group_by_summarise}
 \alias{group_by_summarise}
-\title{Group By and Summarise}
+\title{Group Data by a Specified Column and Summarize Counts}
 \usage{
 group_by_summarise(dat, col, convert_to_percent = FALSE)
 }
 \arguments{
-\item{convert_to_percent}{}
+\item{dat}{A data frame to be analyzed.}
+
+\item{col}{A character string specifying the column name by which to group the data.}
+
+\item{convert_to_percent}{A logical value; if TRUE, convert counts to percentages.
+Default is FALSE.}
+}
+\value{
+A data frame with each group (from the specified column) and its count (and optionally, percentage).
 }
 \description{
-Group By and Summarise
+This function groups a data frame by the values in a specified column, then calculates
+the count of records in each group. Optionally, it can convert these counts into percentages.
+}
+\examples{
+# Example usage with a sample data frame
+set.seed(1)  # for reproducibility
+sample_data <- data.frame(category = sample(c("A", "B", "C"), 120, replace = TRUE, prob = c(0.3, 0.5, 0.2)))
+summary_table <- group_by_summarise(sample_data, "category", convert_to_percent = TRUE)
+print(summary_table)
 }
diff --git a/man/load_libraries.Rd b/man/load_libraries.Rd
index f6002c4..191b0e7 100644
--- a/man/load_libraries.Rd
+++ b/man/load_libraries.Rd
@@ -2,13 +2,21 @@
 % Please edit documentation in R/tools.R
 \name{load_libraries}
 \alias{load_libraries}
-\title{Load Libraries}
+\title{Load a List of R Libraries, Installing if Necessary}
 \usage{
 load_libraries(libraries)
 }
 \arguments{
-\item{libraries}{}
+\item{libraries}{A character vector of R package names to be loaded.}
+}
+\value{
+None; the function is called for its side effects (loading libraries).
 }
 \description{
-Load Libraries
+This function iterates through a list of R package names, checks if they are installed,
+and loads them into the R session. It installs any package that is not already installed.
+}
+\examples{
+# Example usage to load dplyr and ggplot2
+load_libraries(c("dplyr", "ggplot2"))
 }
diff --git a/man/percent_label.Rd b/man/percent_label.Rd
index 613441e..d50710c 100644
--- a/man/percent_label.Rd
+++ b/man/percent_label.Rd
@@ -7,8 +7,21 @@
 percent_label(x, decimal = 1)
 }
 \arguments{
-\item{decimal}{}
+\item{x}{Numeric vector; the values to be formatted as percentages.}
+
+\item{decimal}{Integer; the number of decimal places to round the numeric values.
+Defaults to 1, indicating one decimal place.}
+}
+\value{
+A character vector with the numeric values formatted as percentages.
 }
 \description{
-Add Percent Sign to Data Label
+This function formats numeric values as percentages. It rounds the numbers to the specified decimal places and appends a percent sign.
+}
+\examples{
+# Example usage of percent_label
+numeric_values <- c(0.123, 0.456, 0.789)
+percent_labels <- percent_label(numeric_values)
+print(percent_labels)
+# Output: "12.3\%", "45.6\%", "78.9\%"
 }
diff --git a/tests/testthat/test-instructor_training.R b/tests/testthat/test-instructor_training.R
index f12d868..d0ed048 100644
--- a/tests/testthat/test-instructor_training.R
+++ b/tests/testthat/test-instructor_training.R
@@ -3,7 +3,8 @@ test_that("map_availability works with expected input and renames the column", {
   df <- data.frame(
     "Are you available to teach" = c("Yes, I am available to teach online Instructor Training",
                                      "No, I can NOT teach online events next quarter.",
-                                     "Maybe, but I am not able to schedule firmly at this time.")
+                                     "Maybe, but I am not able to schedule firmly at this time."),
+    check.names = FALSE
   )
   result <- map_availability(df)
   expect_equal(result$availability, c("yes", "no", "maybe"))
@@ -19,15 +20,15 @@ test_that("map_availability throws error if no matching column exists", {
 # Test if map_availability fails if multiple matching columns
 test_that("map_availability fails if multiple matching columns", {
   df <- data.frame(
-    "Are.you.available.to.teach" = c("Yes", "No"),
-    "Are.you.available.to.teach.online" = c("Yes", "No")
+    "Are you available to teach" = c("Yes", "No"),
+    "Are you available to teach.online" = c("Yes", "No"), check.names = FALSE
   )
   expect_error(map_availability(df), "Error: Multiple matching columns found.")
 })
 
 # Test if map_availability leaves other columns unchanged
 test_that("map_availability leaves other columns unchanged", {
-  df <- data.frame("Name" = c("Alice", "Bob"), "Are you available to teach" = c("Yes", "No"))
+  df <- data.frame("Name" = c("Alice", "Bob"), "Are you available to teach" = c("Yes", "No"), check.names = FALSE)
   df_out <- map_availability(df)
   expect_true("Name" %in% names(df_out))
 })
@@ -35,7 +36,7 @@ test_that("map_availability leaves other columns unchanged", {
 # Test if map_availability maps unknown values unchanged
 test_that("map_availability maps unknown values unchanged", {
   df <- data.frame(
-    "Are you available to teach" = c("Unknown value")
+    "Are you available to teach" = c("Unknown value"), check.names = FALSE
   )
   result <- map_availability(df)
   expect_equal(result$availability, "Unknown value")
@@ -44,7 +45,7 @@ test_that("map_availability maps unknown values unchanged", {
 
 test_that("map_timezones works with expected input", {
   df <- data.frame(
-    "What time zone are you located in?" = c("UTC+1", "UTC-5", "UTC+10")
+    "What time zone are you located in?" = c("UTC+1", "UTC-5", "UTC+10"), check.names = FALSE
   )
   result <- map_timezones(df)
   expect_equal(result$TZgroup, c("TZ4", "TZ2", "TZ6"))
@@ -52,7 +53,8 @@ test_that("map_timezones works with expected input", {
 
 test_that("map_timezones renames the timezone column", {
   df <- data.frame(
-    "What time zone are you located in?" = c("UTC+1")
+    "What time zone are you located in?" = c("UTC+1"),
+    check.names = FALSE
   )
   result <- map_timezones(df)
   expect_true("timezone" %in% names(result))
@@ -60,7 +62,7 @@ test_that("map_timezones renames the timezone column", {
 
 test_that("map_timezones handles unknown timezones", {
   df <- data.frame(
-    "What time zone are you located in?" = c("Mars Standard Time")
+    "What time zone are you located in?" = c("Mars Standard Time"), check.names = FALSE
   )
   result <- map_timezones(df)
   expect_equal(result$TZgroup, "TZother")
@@ -101,7 +103,7 @@ test_that("summarise_data_by_qtr works as expected", {
   # Step 1: Mock data frame
   mock_data <- data.frame(
     "What time zone are you located in?" = c("UTC+1", "UTC-5", "UTC+10"),
-    "Are you available to teach" = c("yes", "no", "maybe")
+    "Are you available to teach" = c("yes", "no", "maybe"), check.names = FALSE
   )
 
   # Step 2: Expected result
@@ -129,7 +131,7 @@ test_that("summarise_data_by_tz works as expected", {
   # Mock data frame
   mock_data <- data.frame(
     "What time zone are you located in?" = c("UTC+1", "UTC-5", "UTC+10"),
-    "Are you available to teach" = c("yes", "no", "maybe")
+    "Are you available to teach" = c("yes", "no", "maybe"), check.names = FALSE
   )
 
   # Expected result

From 6cc50ba2940b3934c16e9de3f247566281ba7dd1 Mon Sep 17 00:00:00 2001
From: Kelly Barnes <kbarnes@carpentries.org>
Date: Thu, 23 Nov 2023 10:58:18 -0500
Subject: [PATCH 7/7] updates NEWS

---
 NEWS.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/NEWS.md b/NEWS.md
index d1a62b3..8cb2d43 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,3 +1,3 @@
-2# caliper (development version)
+# caliper (development version)
 
 * Initial CRAN submission.