https://jbengler.github.io/tidyplots/
Tidy Plots for Scientific Papers
https://jbengler.github.io/tidyplots/
Last synced: 8 months ago
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Tidy Plots for Scientific Papers
- Host: GitHub
- URL: https://jbengler.github.io/tidyplots/
- Owner: jbengler
- License: other
- Created: 2023-09-07T20:16:21.000Z (almost 3 years ago)
- Default Branch: master
- Last Pushed: 2025-11-13T23:15:30.000Z (8 months ago)
- Last Synced: 2025-11-13T23:29:09.190Z (8 months ago)
- Language: R
- Homepage: https://jbengler.github.io/tidyplots/
- Size: 372 MB
- Stars: 629
- Watchers: 3
- Forks: 26
- Open Issues: 14
-
Metadata Files:
- Readme: README.Rmd
- Changelog: NEWS.md
- Funding: .github/FUNDING.yml
- License: LICENSE
Awesome Lists containing this project
- awesome-ggplot2 - tidyplots
README
---
output: github_document
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
results = FALSE,
message = FALSE,
warning = FALSE,
fig.align = "center",
dpi = 300,
fig.width = 5,
fig.height = 2.5,
fig.path = "man/figures/README-"
)
```
# tidyplots 
[](https://github.com/jbengler/tidyplots/actions/workflows/R-CMD-check.yaml)
[](https://CRAN.R-project.org/package=tidyplots)
The goal of `tidyplots` is to streamline the creation of publication-ready plots for scientific papers. It allows to gradually add, remove and adjust plot components using a consistent and intuitive syntax.
## Citation
Engler, Jan Broder. 2025. “Tidyplots Empowers Life Scientists With Easy Code-Based Data Visualization.” _iMeta_ e70018. https://doi.org/10.1002/imt2.70018
## Installation
You can install the released version of tidyplots from [CRAN](https://cran.r-project.org/) with:
``` r
install.packages("tidyplots")
```
And the development version from [GitHub](https://github.com/) with:
``` r
# install.packages("pak")
pak::pak("jbengler/tidyplots")
```
## Cheatsheet
This cheatsheet gives a high level overview of available functions.
## Usage
Here are some examples.
Also have a look at the [getting started guide](https://jbengler.github.io/tidyplots/articles/tidyplots.html) and the [full documentation](https://jbengler.github.io/tidyplots/reference/). For more example plots, check out the [tidyplots use cases](https://tidyplots.org/use-cases/) website.
```{r}
library(tidyplots)
study |>
tidyplot(x = treatment, y = score, color = treatment) |>
add_mean_bar(alpha = 0.4) |>
add_sem_errorbar() |>
add_data_points_beeswarm()
```
```{r}
energy |>
tidyplot(x = year, y = energy, color = energy_source) |>
add_barstack_absolute()
```
```{r}
energy |>
dplyr::filter(year %in% c(2005, 2010, 2015, 2020)) |>
tidyplot(y = energy, color = energy_source) |>
add_donut() |>
adjust_size(width = 25, height = 25) |>
split_plot(by = year)
```
```{r}
energy_week |>
tidyplot(x = date, y = power, color = energy_source) |>
add_areastack_absolute()
```
```{r}
energy_week |>
tidyplot(x = date, y = power, color = energy_source) |>
add_areastack_relative()
```
```{r}
study |>
tidyplot(x = group, y = score, color = dose) |>
add_mean_bar(alpha = 0.4) |>
add_mean_dash() |>
add_mean_value()
```
```{r}
time_course |>
tidyplot(x = day, y = score, color = treatment) |>
add_mean_line() |>
add_mean_dot() |>
add_sem_ribbon()
```
```{r}
climate |>
tidyplot(x = month, y = year, color = max_temperature) |>
add_heatmap()
```
```{r, fig.height=3}
study |>
tidyplot(x = treatment, y = score, color = treatment) |>
add_boxplot() |>
add_test_pvalue(ref.group = 1)
```
```{r, fig.height=3.2}
gene_expression |>
dplyr::filter(external_gene_name %in% c("Apol6", "Col5a3", "Vgf", "Bsn")) |>
tidyplot(x = condition, y = expression, color = sample_type) |>
add_mean_dash() |>
add_sem_errorbar() |>
add_data_points_beeswarm() |>
add_test_asterisks(hide_info = TRUE) |>
remove_x_axis_title() |>
adjust_size(width = 25, height = 25) |>
split_plot(by = external_gene_name)
```
```{r}
study |>
tidyplot(x = treatment, y = score, color = treatment) |>
add_mean_bar(alpha = 0.4) |>
add_sem_errorbar() |>
add_data_points_beeswarm() |>
view_plot(title = "Default color scheme: 'friendly'") |>
adjust_colors(colors_discrete_apple) |>
view_plot(title = "Alternative color scheme: 'apple'")
```
## Documentation
- [Package index](https://jbengler.github.io/tidyplots/reference/)
Overview of all tidyplots functions
- [Get started](https://jbengler.github.io/tidyplots/articles/tidyplots.html)
Getting started guide
- [Visualizing data](https://jbengler.github.io/tidyplots/articles/Visualizing-data.html)
Article with examples for common data visualizations
- [Advanced plotting](https://jbengler.github.io/tidyplots/articles/Advanced-plotting.html)
Article about advanced plotting techniques and workflows
- [Color schemes](https://jbengler.github.io/tidyplots/articles/Color-schemes.html)
Article about the use of color schemes
## Acknowledgements
I would like to thank Lars Binkle-Ladisch for our insightful discussions and for consistently challenging my decisions regarding the naming of functions and their arguments.
Many thanks to the R and tidyverse communities. tidyplots is built upon their software and coding paradigms, and it would not have been possible without their contributions.
tidyplots relies on several fantastic packages that handle all the heavy lifting behind the scenes. These include
cli,
dplyr,
forcats,
ggbeeswarm,
ggplot2,
ggpubr,
ggrastr,
ggrepel,
glue,
Hmisc,
htmltools,
lifecycle,
patchwork,
purrr,
rlang,
scales,
stringr,
tidyr, and
tidyselect.