more docs

NAMESPACE

@@ -61,6 +61,7 @@ export(index_embed)
 export(is_any_class)
 export(is_consecutive)
 export(is_datetime)
+export(is_identical_to_previous)
 export(is_valid_redcap_url)
 export(is_valid_token)
 export(launch_FreesearchR)

R/plot_box.R

@@ -39,6 +39,7 @@ plot_box <- function(data, pri, sec, ter = NULL) {
 #' @export
 #'
 #' @examples
+#' mtcars |> plot_box_single("mpg")
 #' mtcars |> plot_box_single("mpg","cyl")
 plot_box_single <- function(data, pri, sec=NULL, seed = 2103) {
   set.seed(seed)

README.md

@@ -38,3 +38,13 @@ launch_FreesearchR()
 ## Code of Conduct
 
 Please note that the ***FreesearchR*** project is released with a [Contributor Code of Conduct](https://contributor-covenant.org/version/2/1/CODE_OF_CONDUCT.html). By contributing to this project, you agree to abide by its terms.
+
+## Acknowledgements
+
+Like any other project, this project was never possible without the great work of others. These are some of the sources and packages I have used:
+
+-   The ***FreesearchR*** app is build with [Shiny](https://shiny.posit.co/) and based on (*R*)[https://www.r-project.org/].
+
+-   [gtsummary](https://www.danieldsjoberg.com/gtsummary/): superb and flexible way to create publication-ready analytical and summary tables.
+
+-   [dreamRs](https://github.com/dreamRs): maintainers of a broad selection of great extensions and tools for [Shiny](https://shiny.posit.co/).

_pkgdown.yml

@@ -13,8 +13,8 @@ template:
 navbar:
   bg: primary
   structure:
-    left:  [intro, reference, roadmap, q_a, news]
-    right: [search, github]
+    left:  [intro, reference, articles, roadmap, q_a, news]
+    right: [search, github, lightswitch]
   components:
     roadmap:
       text: Roadmap

inst/apps/FreesearchR/rsconnect/shinyapps.io/agdamsbo/freesearcheR.dcf

@@ -5,6 +5,6 @@ account: agdamsbo
 server: shinyapps.io
 hostUrl: https://api.shinyapps.io/v1
 appId: 13611288
-bundleId: 10119038
+bundleId: 10156735
 url: https://agdamsbo.shinyapps.io/freesearcheR/
 version: 1

inst/apps/FreesearchR/ui.R

@@ -162,7 +162,7 @@ ui_elements <- list(
               shiny::uiOutput(outputId = "column_filter"),
               shiny::helpText("Variable ", tags$a(
                 "data type",
-                href = "https://agdamsbo.github.io/FreesearchR/articles/FreesearchR.html",
+                href = "https://agdamsbo.github.io/FreesearchR/articles/data-types.html",
                 target = "_blank",
                 rel = "noopener noreferrer"
               ), " filtering."),

man/factorize.Rd

@@ -18,5 +18,5 @@ data.frame
 Factorize variables in data.frame
 }
 \examples{
-factorize(mtcars,names(mtcars))
+factorize(mtcars, names(mtcars))
 }

man/is_identical_to_previous.Rd

@@ -0,0 +1,24 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/helpers.R
+\name{is_identical_to_previous}
+\alias{is_identical_to_previous}
+\title{Test if element is identical to the previous}
+\usage{
+is_identical_to_previous(data, no.name = TRUE)
+}
+\arguments{
+\item{data}{data. vector, data.frame or list}
+
+\item{no.name}{logical to remove names attribute before testing}
+}
+\value{
+logical vector
+}
+\description{
+Test if element is identical to the previous
+}
+\examples{
+c(1, 1, 2, 3, 3, 2, 4, 4) |> is_identical_to_previous()
+mtcars[c(1, 1, 2, 3, 3, 2, 4, 4)] |> is_identical_to_previous()
+list(1, 1, list(2), "A", "a", "a") |> is_identical_to_previous()
+}

man/remove_empty_attr.Rd

@@ -16,11 +16,15 @@ data of same class as input
 Remove empty/NA attributes
 }
 \examples{
-ds <- mtcars |> lapply(\(.x) REDCapCAST::set_attr(.x, label = NA, attr = "label")) |> dplyr::bind_cols()
+ds <- mtcars |>
+  lapply(\(.x) REDCapCAST::set_attr(.x, label = NA, attr = "label")) |>
+  dplyr::bind_cols()
 ds |>
   remove_empty_attr() |>
   str()
- mtcars |> lapply(\(.x) REDCapCAST::set_attr(.x, label = NA, attr = "label")) |> remove_empty_attr() |>
+mtcars |>
+  lapply(\(.x) REDCapCAST::set_attr(.x, label = NA, attr = "label")) |>
+  remove_empty_attr() |>
   str()
 
 }

man/subset_types.Rd

@@ -21,6 +21,6 @@ Easily subset by data type function
 }
 \examples{
 default_parsing(mtcars) |> subset_types("ordinal")
-default_parsing(mtcars) |> subset_types(c("dichotomous", "ordinal", "categorical"))
+default_parsing(mtcars) |> subset_types(c("dichotomous", "categorical"))
 #' default_parsing(mtcars) |> subset_types("factor",class)
 }

vignettes/FreesearchR.Rmd

@@ -67,6 +67,12 @@ This is the panel to get a good overview of your data, check data is classed and
 
 ### Summary
 
+Here, the data variables can be inspected with a simple visualisation and a few key measures. Also, data filtering is available at two levels: 
+
+   - Data type filtering allows to filter by variable [data type]()
+   
+   - Observations level filtering allow to filter data by variable
+
 ### Modify