moving notes on visuals

inst/apps/FreesearchR/www/notes_visuals.md

@@ -1,11 +0,0 @@
-# Basic visualisations
-
-The goal of ***FreesearchR*** is to keep things simple. Visuals can get very complicated. We provide a selection of plots, that helps visualise typical clinical and will be enough for most use cases, and for publishing to most journals.
-
-If you want to go further, have a look at these sites with suggestions and sample code for data plotting:
-
--   [*R* Charts](https://r-charts.com/): Extensive gallery with great plots
-
--   [*R* Graph gallery](https://r-graph-gallery.com/): Another gallery with great graphs
-
--   [graphics principles](https://graphicsprinciples.github.io/): Easy to follow recommendations for clear visuals. 

vignettes/visuals.Rmd

@@ -0,0 +1,55 @@
+---
+title: "On visuals"
+output: rmarkdown::html_vignette
+vignette: >
+  %\VignetteIndexEntry{visuals}
+  %\VignetteEngine{knitr::rmarkdown}
+  %\VignetteEncoding{UTF-8}
+---
+
+```{r, include = FALSE}
+knitr::opts_chunk$set(
+  collapse = TRUE,
+  comment = "#>"
+)
+options(rmarkdown.html_vignette.check_title = FALSE)
+```
+
+```{r setup}
+library(FreesearchR)
+```
+
+## Basic visualisations
+
+The goal of ***FreesearchR*** is to keep things simple. Visuals can get very complicated. We provide a selection of plots, that helps visualise typical clinical and will be enough for most use cases, and for publishing to most journals.
+
+If you want to go further, have a look at these sites with suggestions and sample code for data plotting:
+
+-   [*R* Charts](https://r-charts.com/): Extensive gallery with great plots
+
+-   [*R* Graph gallery](https://r-graph-gallery.com/): Another gallery with great graphs
+
+-   [graphics principles](https://graphicsprinciples.github.io/): Easy to follow recommendations for clear visuals. 
+
+
+### Available plots
+
+Below are the available plot types listed.
+
+```{r echo = FALSE, eval = TRUE}
+c("continuous", "dichotomous", "categorical") |> 
+  lapply(\(.x){
+    dplyr::bind_cols(
+      dplyr::tibble("Data type"=.x),
+      supported_plots() |> 
+      lapply(\(.y){
+        if (.x %in% .y$primary.type){
+          .y[c("descr","note")]|> dplyr::bind_cols()
+        }
+})|> 
+  dplyr::bind_rows() |> 
+  setNames(c("Plot type","Description")))
+  }) |> 
+  dplyr::bind_rows() |> 
+  knitr::kable()
+```