Jan Broder Engler

@jbengler

Scientist and software developer. Creator of tidyplots.org and sepacode.app. Website jbengler.de.

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Jan Broder Engler@jbengler· 28d

Tidyplots offers a variety of continuous color schemes 🌈 Most of the continuous color schemes are adapted from Stéfan van der Walt and Nathaniel Smith (2015) and were designed to maximize accessibility for individuals with color vision deficiencies. #rstats #dataviz

Jan Broder Engler@jbengler· 29d

Tidyplots offers a variety of diverging color schemes 🌈 Diverging color schemes are great to represent data that diverges around a central midpoint, often a meaningful neutral value like zero, an average, or a baseline. #rstats #dataviz

Jan Broder Engler@jbengler· Jul 18

This is how you can add ggplot2 code to your #tidyplots 🔥 #rstats #dataviz #phd

Jan Broder Engler@jbengler· Jul 17

In case you ever wondered about the differences between magrittr pipe and base pipe 🤔 This table is taken from a great stackoverflow answer by @GeorgKindermann https://stackoverflow.com/questions/67633022/what-are-the-differences-between-rs-native-pipe-and-the-magrittr-pipe #rstats #dataviz #phd

Jan Broder Engler@jbengler· Jul 16

This is how you can install a specific version of a package 🤓 In these cases 📦 pak.r-lib.org comes in very handy #rstats #dataviz #phd

library(pak)

# install the latest CRAN release
pak("tidyplots")

# install the development version
pak("jbengler/tidyplots")

# install a specific version
pak("jbengler/tidyplots@v0.0.1")

# install a specific commit
pak("jbengler/tidyplots@9f7294a")

Jan Broder Engler@jbengler· Jul 15

You can easily switch between magrittr pipe `%>%` and base pipe `|>` in the RStudio settings 🧰 #rstats #dataviz #phd

Jan Broder Engler@jbengler· Jul 14

This is how you can highlight a subset of the dataset in #tidyplots 🔥 https://jbengler.github.io/tidyplots/reference/all_rows.html #rstats #dataviz #phd

library(tidyplots)

animals |>
tidyplot(x = weight, y = size) |>
add_data_points() |>
add_data_points(data = max_rows(weight, n = 3),
color = "red", shape = 1, size = 3)

Jan Broder Engler@jbengler· Jul 13

This is how you can plot z-scores in #tidyplots heatmaps 🚀 This is especially useful when you want to focus on the dynamics within rows or columns. #rstats #dataviz #phd

Jan Broder Engler@jbengler· Jul 12

This is how you can use plotmath expressions in #tidyplots 🤓 https://jbengler.github.io/tidyplots/articles/Advanced-plotting.html#special-characters #rstats #dataviz #phd

Jan Broder Engler@jbengler· Jul 11

This is how you can add the mean and standard deviation to summarize the raw data points in your #tidyplots 🤩 Alternatively, you can also display the median, standard error of the mean, 95% confidence interval, and more. #rstats #dataviz #phd

library(tidyplots)

climate |>
tidyplot(x = month, y = max_temperature) |>
add_data_points_beeswarm(alpha = 0.3, color = "grey") |>
add_mean_line(linewidth = 0.5) |>
add_sd_ribbon()

Jan Broder Engler@jbengler· Jul 10

This is how you can remove elements from #tidyplots 🔥 https://jbengler.github.io/tidyplots/reference/index.html#remove #rstats #dataviz #phd

library(tidyplots)

study |>
tidyplot(x = treatment, y = score, color = treatment) |>
add_mean_bar(alpha = 0.4) |>
add_sem_errorbar() |>
add_data_points_beeswarm() |>
remove_legend() |>
remove_x_axis_ticks() |>
remove_y_axis_title()

Jan Broder Engler@jbengler· Jul 9

These are the discrete color schemes in #tidyplots 🌈 The default scheme `colors_discrete_friendly` is inspired by Okabe and Ito (2008) and was designed to be accessible for individuals with color vision deficiencies. #rstats #dataviz #phd

Jan Broder Engler@jbengler· Jul 8

This is the grammar for summary statistics in #tidyplots 🤩 You can mix and match as you like. #rstats #dataviz #phd

Jan Broder Engler@jbengler· Jul 7

This is how you can label selected data points in #tidyplots 🔥 In this case, we label the three animals with the highest weight using `max_rows()`. #rstats #dataviz #phd

library(tidyplots)

animals |>
tidyplot(x = weight, y = size) |>
add_data_points() |>
add_data_labels_repel(data = max_rows(weight, n = 3),
label = animal, color = "black")

Jan Broder Engler@jbengler· Jul 6

This is how you can define a custom style to reuse it across several #tidyplots 🤩 #rstats #dataviz #phd

$library(tidyplots) my_style <- function(x) { x |> adjust_colors(colors_discrete_apple) |> adjust_font(family = "mono", face = "bold") |> remove_x_axis_ticks() |> remove_y_axis_ticks() } energy_week |> tidyplot(date, power, color = energy_source) |> add_areastack_relative() |> my_style()$

Jan Broder Engler@jbengler· Jul 5

Too many vector shapes can slow down PDF performance. This is how you can selectively rasterize data points in #tidyplots 🪩 In this example, I used 100 DPI for demonstration purposes. In practice, you would typically use 300 DPI for better quality 😉 #rstats #dataviz #phd

library(tidyplots)

climate |>
tidyplot(x = month, y = max_temperature) |>
add_data_points_beeswarm(white_border = TRUE, rasterize = TRUE, rasterize_dpi = 100)

Jan Broder Engler@jbengler· Jul 4

When you execute a #tidyplots color scheme like `colors_continuous_viridis` in the Console, you will get a preview in the RStudio Viewer pane 🌈 Pro tip: You can highlight and copy individual hex codes directly from the Viewer pane. #rstats #dataviz #phd

Jan Broder Engler@jbengler· Jul 3

All key features at a glance – with the #tidyplots cheatsheet 🤩 https://tidyplots.org/cheatsheet #rstats #dataviz #phd

Jan Broder Engler@jbengler· Jul 2

This is how you can highlight data in #tidyplots 💡 #rstats #dataviz #phd

Jan Broder Engler@jbengler· Jul 2

This book by Kang Wu is all about #tidyplots 🤩 It’s packed with beautiful example plots and their code. Kang really pushes #tidyplots to its limits—and sometimes even beyond 😂 tidyplots-book.pages.dev @wukang.bsky.social #rstats #dataviz #phd

Jan Broder Engler@jbengler· Jul 1

This is how you can split a plot into multiple subplots using #tidyplots 🚀 #rstats #dataviz #phd

library(tidyplots)

gene_expression |>
head(n = 180) |>
tidyplot(x = group, y = expression, color = group) |>
add_mean_bar(alpha = 0.3) |>
add_sem_errorbar() |>
add_data_points_beeswarm(white_border = TRUE) |>
adjust_size(width = 25, height = 25) |>
split_plot(by = external_gene_name, ncol = 3, nrow = 3)

Jan Broder Engler@jbengler· Jun 30

This is how you can generate multipage PDFs in #tidyplots 🪼 #rstats #dataviz #phd

library(tidyplots)

gene_expression |>
tidyplot(x = group, y = expression, color = group) |>
add_violin() |>
add_data_points_beeswarm(white_border = TRUE) |>
adjust_size(width = 25, height = 25) |>
split_plot(by = external_gene_name, ncol = 3, nrow = 4) |>
save_plot("my_genes.pdf")

Jan Broder Engler@jbengler· Jun 29

This is how you can generate multiple PDF files at once in #tidyplots 🚀 #rstats #dataviz #phd

library(tidyplots)

gene_expression |>
tidyplot(x = group, y = expression, color = group) |>
add_violin() |>
add_data_points_beeswarm(white_border = TRUE) |>
split_plot(by = external_gene_name, ncol = 1, nrow = 1) |>
save_plot("my_genes.pdf", multiple_files = TRUE)

Jan Broder Engler@jbengler· Jun 28

You can save #tidyplots in multiple formats by piping through multiple rounds of `save_plot()` 🤩 #rstats #dataviz #phd

library(tidyplots)

study |>
tidyplot(x = group, y = score, color = dose) |>
add_mean_dash() |>
add_sem_errorbar() |>
add_data_points_beeswarm() |>
save_plot("my_plot.pdf") |>
save_plot("my_plot.png") |>
save_plot("my_plot.svg")

Jan Broder Engler@jbengler· Jun 27

This is how you can assign colors in #tidyplots 🌈 #rstats #dataviz #phd

library(tidyplots)

study |>
tidyplot(x = treatment, y = score, color = treatment) |>
add_violin() |>
add_data_points_beeswarm() |>
adjust_colors(new_colors =
c("A" = "#5B8DFE",
"B" = "#DD227D",
"C" = "#FE5F00",
"D" = "#FFB109"))

Jan Broder Engler@jbengler· Jun 26

Here are some #tidyplots use cases for proportional data 🔥 Complete with data and code 🚀 https://tidyplots.org/use-cases/#proportional-data #rstats #dataviz #phd

Jan Broder Engler@jbengler· Jun 25

This is how you can compare groups in #tidyplots 🦊 #rstats #dataviz #phd

library(tidyplots)

study |>
tidyplot(x = group, y = score, color = dose) |>
add_boxplot() |>
add_mean_dash() |>
add_test_asterisks()

Jan Broder Engler@jbengler· Jun 24

Here are some #tidyplots use cases for bioinformatics 🔥 Complete with data and code 🚀 https://tidyplots.org/use-cases/#bioinformatics #rstats #dataviz #phd

Jan Broder Engler@jbengler· Jun 23

This is how you can add sum values in #tidyplots 🤩 #rstats #dataviz #phd

library(tidyplots)

spendings |>
tidyplot(x = category, y = amount, color = category) |>
add_sum_bar(alpha = 0.2) |>
add_sum_dash() |>
add_sum_value(accuracy = 1, color = "black") |>
adjust_x_axis(rotate_labels = TRUE)

Jan Broder Engler@jbengler· Jun 22

This is how you can sort the x-axis in #tidyplots 🤩 #rstats #dataviz #phd