Movatterモバイル変換


[0]ホーム

URL:


Skip to content

Navigation Menu

Sign in
Appearance settings

Search code, repositories, users, issues, pull requests...

Provide feedback

We read every piece of feedback, and take your input very seriously.

Saved searches

Use saved searches to filter your results more quickly

Sign up
Appearance settings

Tidy Plots for Scientific Papers

License

Unknown, MIT licenses found

Licenses found

Unknown
LICENSE
MIT
LICENSE.md
NotificationsYou must be signed in to change notification settings

jbengler/tidyplots

Repository files navigation

R-CMD-checkCRAN status

The goal oftidyplots is to streamline the creation ofpublication-ready plots for scientific papers. It allows to graduallyadd, remove and adjust plot components using a consistent and intuitivesyntax.

Citation

Engler, Jan Broder. 2025. “Tidyplots Empowers Life Scientists With EasyCode-Based Data Visualization.”iMeta e70018.https://doi.org/10.1002/imt2.70018

Installation

You can install the released version of tidyplots fromCRAN with:

install.packages("tidyplots")

And the development version fromGitHub with:

# install.packages("pak")pak::pak("jbengler/tidyplots")

Cheatsheet

This cheatsheet gives a high level overview of available functions.

tidyplots cheatsheet

Usage

Here are some examples.

Also have a look at thegetting startedguide andthefulldocumentation. Formore example plots, check out thetidyplots usecases website.

library(tidyplots)study|>   tidyplot(x=treatment,y=score,color=treatment)|>   add_mean_bar(alpha=0.4)|>   add_sem_errorbar()|>   add_data_points_beeswarm()

energy|>   tidyplot(x=year,y=energy,color=energy_source)|>   add_barstack_absolute()

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)

energy_week|>   tidyplot(x=date,y=power,color=energy_source)|>   add_areastack_absolute()

energy_week|>   tidyplot(x=date,y=power,color=energy_source)|>   add_areastack_relative()

study|>   tidyplot(x=group,y=score,color=dose)|>   add_mean_bar(alpha=0.4)|>   add_mean_dash()|>   add_mean_value()

time_course|>  tidyplot(x=day,y=score,color=treatment)|>  add_mean_line()|>  add_mean_dot()|>  add_sem_ribbon()

climate|>  tidyplot(x=month,y=year,color=max_temperature)|>  add_heatmap()

study|>   tidyplot(x=treatment,y=score,color=treatment)|>   add_boxplot()|>   add_test_pvalue(ref.group=1)

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)

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

Acknowledgements

I would like to thank Lars Binkle-Ladisch for our insightful discussionsand for consistently challenging my decisions regarding the naming offunctions and their arguments.

Many thanks to the R and tidyverse communities. tidyplots is built upontheir software and coding paradigms, and it would not have been possiblewithout their contributions.

tidyplots relies on several fantastic packages that handle all the heavylifting behind the scenes. These include cli, dplyr, forcats,ggbeeswarm, ggplot2, ggpubr, ggrastr, ggrepel, glue, Hmisc, htmltools,lifecycle, purrr, rlang, scales, stringr, tidyr, and tidyselect.

About

Tidy Plots for Scientific Papers

Resources

License

Unknown, MIT licenses found

Licenses found

Unknown
LICENSE
MIT
LICENSE.md

Stars

Watchers

Forks

Sponsor this project

    Packages

    No packages published

    Contributors3

    •  
    •  
    •  

    Languages


    [8]ページ先頭

    ©2009-2025 Movatter.jp