diff --git a/R/utils_charts.R b/R/utils_charts.R
index 6803b47..05aa976 100644
--- a/R/utils_charts.R
+++ b/R/utils_charts.R
@@ -115,7 +115,7 @@ gpg_trend <- function(x,
 
 gpg_pyramid <- function(x, xvar = "afc_band", yvar, yaxis_title) {
   out <- tryCatch(
-    exp = {
+    expr = {
       data <- x
       # Create chart object
       plt <- data |>
@@ -194,7 +194,7 @@ gpg_pyramid <- function(x, xvar = "afc_band", yvar, yaxis_title) {
 
 gpg_stack <- function(x, xvar, yvar, groupvar, yaxis_title) {
   out <- tryCatch(
-    exp = {
+    expr = {
       data <- x
       # Create chart object
       plt <- data |>
diff --git a/man/gpg_data.Rd b/man/gpg_data.Rd
index 3e79d37..4ad3d20 100644
--- a/man/gpg_data.Rd
+++ b/man/gpg_data.Rd
@@ -27,18 +27,20 @@ least seven columns: period, gender, hourly_rate, quartile, fte, afc_band,
 directorate.
 
 Once initiated, the class has six slots:
-\code{df}: raw data frame 
-\code{df_hdcnt}: data frame contains headcount by period 
-\code{df_hdcnt_gender}: data frame contains headcount by gender by period 
-\code{df_hdcnt_afc}: data frame contains headcount by afc band 
-\code{df_hdcnt_dir}: data frame contains headcount by directorate 
-\code{df_hrrate}: data frame contains hourly rate by gender for each grade 
+\code{df}: raw data frame
+\code{df_hdcnt}: data frame contains headcount by period
+\code{df_hdcnt_gender}: data frame contains headcount by gender by period
+\code{df_hdcnt_afc}: data frame contains headcount by afc band
+\code{df_hdcnt_dir}: data frame contains headcount by directorate
+\code{df_hrrate}: data frame contains hourly rate by gender for each grade
 \code{ending_fy}: a character vector containing ending reporting period
 (e.g. 31 March 2023). This uses for introduction paragraph
 }
 \examples{
- 
+\dontrun{
+
 library(nhsbsaGPG)
 df <- gpg_data(afc_staff)
+}
 
 }
diff --git a/man/paygap.Rd b/man/paygap.Rd
index 2e19a52..1ca4916 100644
--- a/man/paygap.Rd
+++ b/man/paygap.Rd
@@ -12,14 +12,15 @@ paygap
 }
 \description{
 A dataset containing NHSBSA employee paygap
-Directly pulled from ESR dashboard (NHS National Returns) 
+Directly pulled from ESR dashboard (NHS National Returns)
 gender, average hourly rate, median hourly rate and pay gap%
 }
 \details{
 \itemize{
    \item period. 2018/19, 2019/20 etc character
   \item avg_hr_gpg. Mean gender pay gap % based on male full-pay relevant employees
-  \item median_hr_gpg. Median gender pay gap % based on male full-pay relevant employees
-  }
+  \item median_hr_gpg. Median gender pay gap % based
+  on male full-pay relevant employees
+}
 }
 \keyword{datasets}
diff --git a/man/quartile.Rd b/man/quartile.Rd
index ab21d7b..41e328f 100644
--- a/man/quartile.Rd
+++ b/man/quartile.Rd
@@ -23,7 +23,7 @@ by quartiles
   \item male. number of male employees in each quartile
   \item quartile. split hourly_rate by quartile by gender
  }
- 
+
  @docType data
  @keywords datasets
  @name quartile
diff --git a/tests/testthat/test-utils_charts.R b/tests/testthat/test-utils_charts.R
index b031074..1651d4a 100644
--- a/tests/testthat/test-utils_charts.R
+++ b/tests/testthat/test-utils_charts.R
@@ -1,7 +1,7 @@
 library(tidyr)
 library(dplyr)
 
-df <- gpg_data(afc_staff)
+df <- gpg_data(nhsbsaGPG::afc_staff)
 x <- df$df_hdcnt_gender |>
   tidyr::pivot_wider(
     names_from = gender,
@@ -11,8 +11,8 @@ x <- df$df_hdcnt_gender |>
 
 y <- nhsbsaGPG::paygap
 
-z <- df$df_hdcnt_afc |>
-  filter(period == "2021/22") |>
+z <- df$df_hdcnt_afc |> 
+  filter(period == '2021/22') |> 
   mutate(headcount = headcount * ifelse(gender == "Male", 1, -1))
 
 testthat::test_that("gpg_trend function runs without errors", {
@@ -47,8 +47,8 @@ testthat::test_that("gpg_trend takes list as an input", {
 
 testthat::test_that("gpg_trend input data frame must contain Female,
                     Male column", {
-                      expect_equal(length(grep("Female|Male", names(x))), 2)
-                    })
+  expect_equal(length(grep("Female|Male", names(x))), 2)
+})
 
 
 testthat::test_that("gpg_trend input data frame must contain period column", {
@@ -69,14 +69,22 @@ testthat::test_that("gpg_trend function runs with paygap dataframe", {
 
 
 testthat::test_that("gpg_pyramid function runs without error", {
-  expect_silent(gpg_pyramid(z, xvar = "afc_band", yvar = "headcount",
-    yaxis_title = "Headcount"
+  expect_silent(gpg_pyramid(z ,
+                          xvar = "afc_band",
+                          yvar = "headcount",
+                          yaxis_title = "Headcount"
   ))
 })
 
 testthat::test_that("gpg_stack function runs without error", {
-  expect_silent(gpg_stack(quartile |> filter(period == "2021/22"),
-    xvar = "quartile", yvar = "percent", groupvar = "ender",
-    yaxis_title = "Males and females in pay quartile"
+  expect_silent(gpg_stack(quartile |> filter(period == "2021/22") ,
+                            xvar = "quartile",
+                            yvar = "percent",
+                            groupvar = "gender",
+                            yaxis_title = "Males and females in pay quartile"
   ))
 })
+
+
+
+