Twitter bots | Next - Issue #30





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Hi there!
I’ve been reading a little on how to make Twitter bots because I want to make one for this newsletter. Today’s letter includes some of them. Enjoy!

Five Stories
A person’s ability to be random peaks around 25 years old and declines after 60. Dozens of outlets covered this study. Some researchers had some questions and thought to replicate the study. (I’ve written about the replication crisis in the past.)
If some observations are excluded from the study, the results change. Play the interactive game and learn more about it!
Tidy Data Tutor lets you write R and Tidyverse code in your browser and see how your data frame changes at each step of a data analysis pipeline. (If you use Python, check out Pandas Tutor.)
Musk might be against the bots on Twitter, but it looks like they are here to stay. In the tutorial blogpost, the authors created a Twitter bot that…
…posts a satellite image from random coordinates in Greater London (well, from a bounding box roughly within the M25 motorway) on schedule.
The process is not too complicated. There is an R script for getting the tweets and a YAML file instructing Github to automate everything. Check it out!
Oscar Baruffa created a Twitter bot to discover R programming books. In this blog post, Oscar covers how to get a Twitter bot working or automate your tweets. The post is detailed and covers aspects that the previous story by missed: storing credentials privately on Github, applying for elevated access, etc.
You want to create a Twitter bot but don’t want to go through the complicated process. {botmaker} package is here to help.
It reduces the hassles of making bots into one simple function. Just don’t make an evil bot, okay?
Four Packages
botmaker provides an interface to make your Twitter bots based on Github actions. For details, see the vignette. YouTube.
modelsummary creates tables and plots to summarise models in R. The output can be HTML, PDF, Text/Markdown, LaTeX, MS Word, RTF, JPG, and PNG. For details, see the vignette.
foreach provides looping constructs in R — alternative to for loop, apply, map, etc. Why is it better? It allows for parallel processing and is much faster! See vignette.
Rtex is an alternative to R Markdown. Using LaTeX in R Markdown can be complicated as soon as you have multiple libraries and style files. Rtex produces a TeX file with a few executable R code chunks. Check it out!
Three Jargons
A collection of common R terms defined first using Stata jargon (or plain English when possible) and then more formally using R jargon.
Two Tweets
Michael Sumner
#rstats how do I set up one of those twitter bot accounts to post something every day? can it be done from Github actions?
Bindu Reddy 🔥❤️
machine learning is magical until you understand the math...

Once you do, it feels like glorified curve fitting.
One Meme
That's a wrap!
I hope you enjoyed today’s letter. Could you share it with a friend or a colleague? See you next week!
Did you enjoy this issue? Yes No
Harshvardhan @harshbutjust

A short and sweet curated collection of R-related works. Five stories. Four packages. Three jargons. Two tweets. One Meme.

List of all packages covered in past issues:

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