Hello!
This repo contains my #rstats, data science & stats illustrations shared on my twitter account (@allison_horst).
All of this artwork is 100% available (and encouraged!) for open use by CC-BY license. That means: Hooray! I'm so happy that you want to share this artwork - especially if it helps when teaching R/rstats/stats. You can just cite with "Artwork by @allison_horst". That's it! Click on the images below for the hi-res versions.
This work is licensed under a Creative Commons Attribution 4.0 International License.
Is the artwork useful for your teaching materials? Please consider donating to Data 4 Black Lives!
This artwork is available for free to anyone who wants to use it for your teaching, learning, presentations, and more. If you are a teacher and feel that your course benefits from the artwork, and you can do so without stress or burden, please consider a donation to Data 4 Black Lives.
Recent additions
Workflows that shred...
Openscapes blog with Dr. Julia Lowndes!)
Tidy Data series (a collaboration for thePlease cite the following Tidy Data illustrations as: "Illustrations from the Openscapes blog Tidy Data for reproducibility, efficiency, and collaboration by Julia Lowndes and Allison Horst"
- What is tidy data?
- Like families...
- Comparison of work benches:
- Friends with similar tools:
- Easier for automation & iteration!
- And it makes all other tidy datasets seem more welcoming!
- So make friends with tidy data!
R Knowledge Rollercoaster:
Derivatives thread:
usethis (seriously...):
Faces of debugging:
Monster supporters:
R-related artwork:
beepr let's you pick and play a notification sound when your code/analysis is done running:
broom makes messy model / statistical outputs into tidy tibbles:
dplyr::mutate creates or transforms a variable (column) while keeping the existing ones:
dplyr: get your data wrangling on.
dplyr::across()
makes it easy to apply a function (or functions) across selected columns!
dplyr::case_when()
for friendly if_else statements:
dplyr::filter()
to subset rows based on your conditions:
dplyr::relocate
: a friendly function for moving columns around (in dplyr
1.0.0)!
gganimate: get a little action in(to your graphs)...
ggplot2 for visual data exploration:
...and use ggplot2 for creating beautiful data masterpieces!
here for more peaceful (file) paths:
The janitor package contains multiple user-friendly functions for cleaning messy data, including clean_names() to update all of your column names to a nice case of your choosing (snake_case! lowerCamel! UpperCamel! SCREAMING_SNAKE! ...and more) all at once:
Use lubridate to work more easily & intuitively with dates & times:
Like lubridate_ymd() to easily parse year/month/day data!
Use readr::parse_number() to just keep the numeric parts, & remove characters:
Part of tidymodels, the parsnip package creates standardized syntax across model engines:
Easily arrange and combine ggplots with patchwork!
You can do it!
Use @tylermorganwall's rayshader package to create amazing 3D maps and graphs!
Use recipes to streamline data preprocessing for stats & machine learning models:
Create reproducible examples to get (and give) help more easily with reprex!
Get your code, text & outputs in the same (reproducible) place with Rmarkdown:
Be an Rmarkdown knitting wizard.
Do your data sci like it's going to need an alibi with Rmarkdown:
Use the sf package for simpler spatial data analysis with geometries that stick to attributes:
Soon to be pivot_wider() & pivot_longer()! tidyr::spread() & gather():
stringr::str_squish()
removes whitespace before and after strings, and reduced repeated interior whitespace to a single space (see also: str_trim()
):
Blast off into the...
For #rstats and friends!
Thanks, #rstats community!
If you bring group_by() to the party, don't forget dplyr::ungroup()
purrr bakers from Hadley Wickham's 2019 talk "The Joy of Functional Programming (for Data Science)"
The following illustrations are in Hadley's ACM talk, which you can watch HERE. Please cite the following artwork with "Illustrations from Hadley Wickham's talk "The Joy of Functional Programming (for Data Science)."
Bakers
Others from this set
For looped:
Wrangler:
purrr feels like:
Presenting results:
R gifs (made for ESM 206 Slack channel, Fall 2020)
Make your own sample cartoons!
I'm building this library of samples, faces & arms so that statistics teachers can create their own fun, charismatic samples to include in stats lectures, slides & materials. The files below contain different graphs (dotplots, histograms, more to come) with matching arms doing different things, along with a file of faces you can add on top to give them some personality. I recommend playing with transparency, brightness, cropping & size in whatever program you use to piece these together! Working on making these PNGs & SVGs.
Here are some examples of DIY creations:
The pieces so that you can make your own:
Faces
Choose the expression to add to your sample:
Histogram sticker sheets
Dot plot sticker sheets
Extras & speech bubbles
More coming, feel free to send suggestions.
Other stats artwork:
For loop monster parade
Whale sharks for PCA teaching warm-up
I start with "pretend you are this whale shark..."
Pie charts
For the love of pie charts:
k-means clustering thread:
Hierarchical clustering (single linkage) thread:
Creatures and their distance matrix:
Find the clusters with the minimum distance between elements in them & merge:
Repeat!
Ta-da!
Multiple linear regression dragons thread:
Meet your MLR teaching assistants:
Interpret coefficients for categorical predictor variables:
And for continuous predictor variables:
Or make predictions using the regression model:
Understand residuals:
And check for residuals normality:
in_case_you_forget:
Release the disco data:
Type I errors:
Type II errors:
Normality?
Continuous & discrete data:
Nominal, ordinal & binary data:
Openscapes artwork (@jules32 collaborations)
The expanded version of the classic Grolemund & Wickham R4DS workflow, including environmental data & sci comm bookends! Envisioned by Dr. Julia Lowndes for her useR!2019 keynote.
Really random stuff
Dog & whale training art:
Make a data shark:
Data to make the shark is HERE. Created with drawdata.xyz.
Translated R-artwork:
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Español: rstats-artwork-ES
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Brazilian Portuguese: rstats-artwork-PT
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Please submit translations as an issue!
Thank you
Thank you to all the R developers, maintainers, contributors, teachers and communicators who actually MAKE all of these amazing packages and documentation that have inspired this #rstats artwork. When I create an illustration with your package it's with immense gratitude for how your hard work has allowed me to do mine (using and teaching #rstats) more efficiently, more clearly, more reproducibly....just plain better. THANK YOU!