# 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.
## Black Lives Matter
### 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
Derivatives thread:
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usethis (seriously...):
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Faces of debugging:
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Monster supporters:
## R-related artwork:
beepr let's you pick and play a notification sound when your code/analysis is done running:
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broom makes messy model / statistical outputs into tidy tibbles:
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dplyr::mutate creates or transforms a variable (column) while keeping the existing ones:
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dplyr: get your data wrangling on.
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`dplyr::across()` makes it easy to apply a function (or functions) across selected columns!
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`dplyr::case_when()` for friendly if_else statements:
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`dplyr::filter()` to subset rows based on your conditions:
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`dplyr::relocate`: a friendly function for moving columns around (in `dplyr` 1.0.0)!
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gganimate: get a little action in(to your graphs)...
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ggplot2 for visual data exploration:
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...and use ggplot2 for creating beautiful data masterpieces!
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here for more peaceful (file) paths:
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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:
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Use lubridate to work more easily & intuitively with dates & times:
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Like lubridate_ymd() to easily parse year/month/day data!
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Use readr::parse_number() to just keep the numeric parts, & remove characters:
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Part of tidymodels, the parsnip package creates standardized syntax across model engines:
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Easily arrange and combine ggplots with patchwork!
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You can do it!
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Use @tylermorganwall's rayshader package to create amazing 3D maps and graphs!
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Use recipes to streamline data preprocessing for stats & machine learning models:
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Create reproducible examples to get (and give) help more easily with reprex!
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Get your code, text & outputs in the same (reproducible) place with Rmarkdown:
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Be an Rmarkdown knitting wizard.
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Do your data sci like it's going to need an alibi with Rmarkdown:
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Use the sf package for simpler spatial data analysis with geometries that stick to attributes:
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Soon to be pivot_wider() & pivot_longer()! tidyr::spread() & gather():
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`stringr::str_squish()` removes whitespace before and after strings, and reduced repeated interior whitespace to a single space (see also: `str_trim()`):
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Blast off into the...
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For #rstats and friends!
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Thanks, #rstats community!
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If you bring group_by() to the party, don't forget dplyr::ungroup()
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## 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](https://learning.acm.org/techtalks/functionalprogramming). 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:
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in_case_you_forget:
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Release the disco data:
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Type I errors:
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Type II errors:
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Normality?
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Continuous & discrete data:
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Nominal, ordinal & binary data:
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## 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.
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## Really random stuff
Dog & whale training art:
Make a data shark:
Data to make the shark is HERE. Created with drawdata.xyz.
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## Translated R-artwork:
- Espaol: rstats-artwork-ES
- Brazilian Portuguese: rstats-artwork-PT
- 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!