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https://github.com/openpharma/visR

A package to wrap functionality for plots, tables and diagrams adhering to graphical principles.
https://github.com/openpharma/visR

Last synced: about 2 months ago
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A package to wrap functionality for plots, tables and diagrams adhering to graphical principles.

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README

        

---
output: github_document
---

```{r setup, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)

library(visR)
library(riskmetric)
library(usethis)

riskmetric_score <- "visR" %>%
riskmetric::pkg_ref() %>%
dplyr::as_tibble() %>%
riskmetric::pkg_assess() %>%
riskmetric::pkg_score() %>%
dplyr::pull("pkg_score") %>%
round(2)
```

# visR

[![Lifecycle: questioning](https://img.shields.io/badge/lifecycle-questioning-blue)](https://lifecycle.r-lib.org/articles/stages.html#experimental)
[![Codecov test coverage](https://codecov.io/gh/openpharma/visR/branch/develop/graph/badge.svg)](https://app.codecov.io/gh/openpharma/visR?branch=main)
[![R-CMD-check](https://github.com/openpharma/visR/workflows/R-CMD-check/badge.svg)](https://github.com/openpharma/visR/actions)
[![CRAN status](https://www.r-pkg.org/badges/version/visR)](https://CRAN.R-project.org/package=visR)

**Note**: We aim to keep visR maintained, but cannot commit to any future development. For all your KM plot needs, we would recommend checking out [ggsurvit](https://www.danieldsjoberg.com/ggsurvfit/).

The goal of visR is to enable fit-for-purpose, reusable clinical and medical research focused visualizations and tables with sensible defaults and based on sound [graphical principles](https://graphicsprinciples.github.io/).

[Package documentation](https://openpharma.github.io/visR/)

## Motivation

By using a common package for visualising data analysis results in the clinical development process, we want to have a **positive influence** on

* **choice of visualisation** by making it easy explore different visualisation and to use impactful visualisations fit-for-purpose
* effective visual communication by making it easy to **implement best practices**

We are not judging on what visualisation you chose for your research question, but want to facilitate and support good practice.

You can read more about the philosophy and architecture in the [repo wiki](https://github.com/openpharma/visR/wiki).

## Installation

The easiest way to get `visR` is to install from CRAN:

``` r
install.packages("visR")
```

Install the *development* version from [GitHub](https://github.com/openpharma/visR) with:

``` r
# defaults to main branch
devtools::install_github("openpharma/visR")
```

## Cite visR

```{text, comment="", eval = FALSE}
> citation("visR")
```

## Contributing

Please note that the `visR` project is released with a [Contributor Code of Conduct](CODE_OF_CONDUCT.md). By contributing to this project, you agree to abide by its terms.
Thank you to all contributors:

```{r warning=FALSE, echo=FALSE, message=FALSE}
contr <- usethis::use_tidy_thanks("https://github.com/openpharma/visR", from = "2020-01-01", to = NULL)
```
`r unique(c(paste((paste0("[@",contr,"](https://github.com/", contr, ")")), collapse = ", ")
))`