mirror of
https://github.com/agdamsbo/FreesearchR.git
synced 2025-09-12 01:49:39 +02:00
56 lines
1.5 KiB
Text
56 lines
1.5 KiB
Text
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---
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title: "On visuals"
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output: rmarkdown::html_vignette
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vignette: >
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%\VignetteIndexEntry{visuals}
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%\VignetteEngine{knitr::rmarkdown}
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%\VignetteEncoding{UTF-8}
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---
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```{r, include = FALSE}
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knitr::opts_chunk$set(
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collapse = TRUE,
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comment = "#>"
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)
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options(rmarkdown.html_vignette.check_title = FALSE)
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```
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```{r setup}
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library(FreesearchR)
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```
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## Basic visualisations
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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.
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If you want to go further, have a look at these sites with suggestions and sample code for data plotting:
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- [*R* Charts](https://r-charts.com/): Extensive gallery with great plots
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- [*R* Graph gallery](https://r-graph-gallery.com/): Another gallery with great graphs
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- [graphics principles](https://graphicsprinciples.github.io/): Easy to follow recommendations for clear visuals.
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### Available plots
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Below are the available plot types listed.
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```{r echo = FALSE, eval = TRUE}
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c("continuous", "dichotomous", "categorical") |>
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lapply(\(.x){
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dplyr::bind_cols(
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dplyr::tibble("Data type"=.x),
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supported_plots() |>
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lapply(\(.y){
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if (.x %in% .y$primary.type){
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.y[c("descr","note")]|> dplyr::bind_cols()
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}
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})|>
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dplyr::bind_rows() |>
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setNames(c("Plot type","Description")))
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}) |>
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dplyr::bind_rows() |>
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knitr::kable()
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```
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