Tootfinder

Tidy Modeling with R: #rstats #machinelearning

Tidy Modeling with R
The tidymodels framework is a collection of R packages for modeling and machine learning using tidyverse principles. This book provides a thorough introduction to how to use tidymodels, and an outline of good methodology and statistical practice for phases of the modeling process.

🚀 𝘀𝗽𝗮𝗻𝗶𝘀𝗵𝗼𝗱𝗱𝗮𝘁𝗮 0.2.0 is here. As before, you are getting nicely formatted Open Mobility Big Data released by the Spanish Ministry of Transport and Sustainable Mobility (MITMS) in a reproducible way. #rstats #opendata

Get Spanish Origin-Destination Data
Gain seamless access to origin-destination (OD) data from the Spanish Ministry of Transport, hosted at . This package simplifies the management of these large datasets by providing tools to download zone boundaries, handle associated origin-destination data, and process it efficiently with the duckdb database interface. Local caching minimizes repeated downloads, streamlining wo…

We're making hand-made buttons/pins for the @… booth at @…
Any ideas for good motifs anyone?
#rstats

Are you interested in how dependency-heavy your (or another) package is and why? #rstats

GitHub - jokergoo/pkgndep: Analyzing Dependency Heaviness of R Packages
Analyzing Dependency Heaviness of R Packages. Contribute to jokergoo/pkgndep development by creating an account on GitHub.

Beside the {report} package (yesterdays note) there are more tools in the easystats collection. #rstats

GitHub - easystats/easystats: :milky_way: The R easystats-project
:milky_way: The R easystats-project. Contribute to easystats/easystats development by creating an account on GitHub.

Add some swag to your ggplots, with fontawesome symbols and colors: #rstats

Adding social media icons to charts with {ggplot2} | Nicola Rennie
Adding social media icons to your data visualisation is a great, concise way to put your name on your work, and make it easy for people to find your profile from your work. This blog post explains how to add social media icons to {ggplot2} charts.

Using fonts in R graphics can be tricky at times. {showtext} aims to make it easier: #rstats

Extract tables from pdfs with {tabulapdf} #rstats #datasciece

Automatically describe data and models as text using the {report} package. #rstats

Sometimes (often) one ends up needing to run older versions of R using older versions of packages. Evercran might be just the tool to help with that: #RStats

GitHub - r-hub/evercran: Any version of R -- with the matching version of CRAN
Any version of R -- with the matching version of CRAN - r-hub/evercran

Get 9-30x speed doing areal-weighted interpolation with my new {𝐝𝐮𝐜𝐤𝐬𝐟} #rstats package compared to {sf}/{areal}. Experimental, but tested against both {areal} and {sf}. https://github.com/e-kotov/ducksf . Despite…

Need some data to test a plot idea or algorithm? On #rstats #synthetic…

If you feel you should be reading more: #rstats #ebooks

Big Book of R

There are frameworks like {golem} and {rhino} to make shiny development more robust, but I like the concept of {shinytest2} in providing a testing framework for pure shiny. https://rstudio.github.io/shinytest2/index.html

{nplyr} has helper functions to work on nested dataframes: #rstats #datascience

Polars is a lightning fast DataFrame library/in-memory query engine with parallel execution and cache efficiency. And now you can use is with the tidyverse syntax: #rstats

Here's an ad that Google Opal created for #rstats #spanishoddata https://ropenspain.github.io/spanishod

{ggdist}: Visualizations of distributions and uncertainty #rstats #ggplot

Im using case_when() quite a lot, case_match() is new to me: #rstats

A general vectorised switch() — case_match
This function allows you to vectorise multiple switch() statements. Each case is evaluated sequentially and the first match for each element determines the corresponding value in the output vector. If no cases match, the .default is used. case_match() is an R equivalent of the SQL "simple" CASE WHEN statement. Connection to case_when() While case_when() uses logical expressions on the left-hand side of the formula, case_match() uses values to match against .x with. The following two statement…

Here's an ad that Google Opal created for #rstats #spanishoddata https://ropenspain.github.io/spanishod

Highlight a certain aspect of your data in ggplot: #rstats

{piggyback} makes it easier to attach large files (e.g. input data) to code in github repos: #rstats

GitHub - ropensci/piggyback: :package: for using large(r) data files on GitHub
:package: for using large(r) data files on GitHub. Contribute to ropensci/piggyback development by creating an account on GitHub.

The cool things you sometimes find in the CRAN submission queue. #rstats

There are many situations were you need access to different R versions: rig is a way to manage them #rstats

GitHub - r-lib/rig: The R Installation Manager
The R Installation Manager. Contribute to r-lib/rig development by creating an account on GitHub.

The cool things you sometimes find in the CRAN submission queue. #rstats

If you use Quarto to make presentations for a professional setting, it is important to choose the right theme, e.g. #rstats

GitHub - EmilHvitfeldt/quarto-nes-theme: A Quarto reveal.js theme based on NES.css
A Quarto reveal.js theme based on NES.css. Contribute to EmilHvitfeldt/quarto-nes-theme development by creating an account on GitHub.

Sometimes you get data in less than optimal format, e.g. as a png of a figure 😭... In that case https://cran.r-project.org/web/packages/metaDigitise/vignettes/metaDigitise.html might be the rescue.

TidyX: screencasts explaining different aspects of the R language and the coding process. #rstats

Not sure any longer which libraries your script actually needs? #rstats

Script for finding loaded but unused packages in R scripts
Script for finding loaded but unused packages in R scripts - analyze_pkg_usage.R

Beautiful palettes based on art for R and python: #rstats #ggplot

GitHub - BlakeRMills/MetBrewer: Color palette package in R inspired by works at the Metropolitan Museum of Art in New York
Color palette package in R inspired by works at the Metropolitan Museum of Art in New York - BlakeRMills/MetBrewer

📝🗃️ 𝗿𝗱𝗼𝗰𝗱𝘂𝗺𝗽: Dump ‘R’ Package Source, Documentation, and Vignettes into One File for use in LLMs #rstats #LLM is on CRAN https://www.ekotov.pro/rdocdum…

rdocdump: Dump R Package Documentation and Vignettes into One File
Dump R Package Documentation and Vignettes into One File

Find the best contrast between one color and a list of options, e.g. for labels in geom_tile: {prismatic::best_contrast()} https://emilhvitfeldt.github.io/prismatic/reference/best_contrast.html

Everything is a linear model: #rstats #stats

{ggbump} creates elegant bump charts in ggplot. #ggplot #rstats

Are you making slides with Quarto or R Markdown and need a timer e.g. for breaks or group work? There is the {countdown} package for you: #rstats

A pictures says more than 1000 words. How much more can an audio representation of your data tell you? #rstats

sonify: Data Sonification - Turning Data into Sound
Sonification (or audification) is the process of representing data by sounds in the audible range. This package provides the R function sonify() that transforms univariate data, sampled at regular or irregular intervals, into a continuous sound with time-varying frequency. The ups and downs in frequency represent the ups and downs in the data. Sonify provides a substitute for R's plot function to simplify data analysis for the visually impaired.

Getting started with Shiny to make interactive web-apps with R: #rstats

Overview | Building Web Apps with R Shiny
This class will teach you the basics of Shiny app programming, giving you skills that will form the basis of almost any app you want to build. By the end of the class, you will have created a custom app that collects and saves data, allows users to dynamically visualize the data, and produces downloadable reports.

The {esquisse} package makes it easy to plot your data in different ways with a drag and drop interface: #rstats

Explore and Visualize Your Data Interactively
A shiny gadget to create ggplot2 figures interactively with drag-and-drop to map your variables to different aesthetics. You can quickly visualize your data accordingly to their type, export in various formats, and retrieve the code to reproduce the plot.

This looks helpful: #rstats #optimization

Keynote from rstudio::conf 2022: The past and future of shiny. #rstats

Posit

Do you need better performance than what the standard #tidyverse functions have? {collapse} might be worth a look: https://sebkrantz.github.io/collapse/

Advanced and Fast Data Transformation in R
A large C/C++-based package for advanced data transformation and statistical computing in R that is extremely fast, class-agnostic, robust, and programmer friendly. Core functionality includes a rich set of S3 generic grouped and weighted statistical functions for vectors, matrices and data frames, which provide efficient low-level vectorizations, OpenMP multithreading, and skip missing values by default. These are integrated with fast grouping and ordering algorithms (also callable from C), an…

Use cookies in shiny apps: #rstats #shiny

The dbcooper package turns a database connection into a collection of functions. #rstats

GitHub - pipeline-tools/dbcooper: Create user-friendly accessor functions from a database connection
Create user-friendly accessor functions from a database connection - pipeline-tools/dbcooper

{slider} helps with aggregation over (sliding) windows, both index and time period based: #rstats

GitHub - r-lib/slider: Sliding Window Functions
Sliding Window Functions. Contribute to r-lib/slider development by creating an account on GitHub.

{lubridate} makes working with dates in R just that little bit easier: #rstats #dates

Make Dealing with Dates a Little Easier
Functions to work with date-times and time-spans: fast and user friendly parsing of date-time data, extraction and updating of components of a date-time (years, months, days, hours, minutes, and seconds), algebraic manipulation on date-time and time-span objects. The lubridate package has a consistent and memorable syntax that makes working with dates easy and fun.

Follow along when @… walks you through how she tackles a new dataset: https://www.youtube.com/c/JuliaSilge

Primer to get you started with Optimization and Mathematical Programming in R #rstats

Keep track of the TODO notes in your code: #rstats #todo

GitHub - dokato/todor: TODOr - RStudio add-in for finding TODO, FIXME, CHANGED etc. comments in your code.
TODOr - RStudio add-in for finding TODO, FIXME, CHANGED etc. comments in your code. - dokato/todor

Use multi level models with {parsnip}: http://multilevelmod.tidymodels.org/ #rstats #ML

paint() your data when you print them to make them easier to grasp: #rstats #console

GitHub - MilesMcBain/paint: paint the data
paint the data. Contribute to MilesMcBain/paint development by creating an account on GitHub.

A curated list of awesome tools to assist 📦 development in R programming language. #rstats #📦

The inner working of parquette/arrow data in R: #rstats

Unpacking Arrow Datasets – Notes from a data witch
A comment on how Datasets work in Apache Arrow. I’m not really sure who the audience for this one. Am I just talking to myself? Probably.

The functions in the {withr} package allow to change your environment temporarily. E.g. create a temp file for a {testthat} test and clean it up afterwards. #rstats

Run Code With Temporarily Modified Global State
A set of functions to run code with safely and temporarily modified global state. Many of these functions were originally a part of the devtools package, this provides a simple package with limited dependencies to provide access to these functions.

{dtrack} makes documentation of data wrangling part of the analysis and creates pretty flow charts: #rstats

The {purrr} package is a powerfull way to replace loops. The {furrr} package takes this approach one step further by parallel execution: #rstats

Apply Mapping Functions in Parallel using Futures
Implementations of the family of map() functions from purrr that can be resolved using any future-supported backend, e.g. parallel on the local machine or distributed on a compute cluster.

GitHub Actions for the R language: Makes automatic testing of your R package much easier and making sure your package works on different OS and R versions is a matter of just a few lines of yaml: #rstats

Make paint-by-number pictures in R: #rstats

{annotater}: Annotate package load calls, so we can have an idea of the overall purpose of the libraries we’re loading: #rstats

Make sure your code follows a consitent style using the {lintr} package. #rstats

A Linter for R Code
Checks adherence to a given style, syntax errors and possible semantic issues. Supports on the fly checking of R code edited with RStudio IDE, Emacs, Vim, Sublime Text, Atom and Visual Studio Code.

{ggrain}: Raincloud plots for ggplot2: #rstats #dataviz

GitHub - njudd/ggrain: {package} Make beautiful Raincloud plots in R!
{package} Make beautiful Raincloud plots in R! Contribute to njudd/ggrain development by creating an account on GitHub.

Handy RStudio addins for reshaping and navigating in code: #rstats #rstudio

{spiralize} can be used to highlight cyclic data, e.g. multi year time series. #rstats

r-charts.com provides example code for a variety of chart types, both in base R and ggplot: #rstats #ggplot…

R CHARTS | A collection of charts and graphs made with the R programming language
Over 1400 graphs with reproducible code divided in 8 big categories and over 50 chart types, in addition of tools to choose and create colors and color palettes

Lets be honest, we spend too much time cleaning data. {janitor} can help with that: #rstats

{testthat} is great for automatic testing. Here are some tricks for the heavy user: #rstats

{ivs} makes it easier to work with intervals: #rstats

Function-oriented Make-like declarative workflows for R #rstats

GitHub - ropensci/targets: Function-oriented Make-like declarative workflows for R
Function-oriented Make-like declarative workflows for R - ropensci/targets

Visualize dependencies between functions: #rstats

Make fancy tables: #rstats #tables

A template for data analysis projects structured as R packages (or not) #rstats #datascience

GitHub - Pakillo/template: A template for data analysis projects structured as R packages (or not)
A template for data analysis projects structured as R packages (or not) - Pakillo/template

Cute comics of R functions by @…: https://allisonhorst.com/r-packages-functions

Allison Horst - R Packages & Functions

Do you (sometimes) use print() or message() for debugging your code? Next time you can use {icecream} instead: #rstats

Ice Cream for R Programmers - Turtletopia: a blog about programming in R
Icecream is a tool which may serve as a more sophisticated replacement of using print while debugging.

I am more fluent in LaTeX than in plotmath expression. If you are the same, latex2exp will make your life easier. https://cran.r-project.org/web/packages/latex2exp/vignettes/using-latex2exp.html

Its good to have many tests in your R package, but it can be a pain to debug some failing tests when it happens. {lazytest} for the rescue: only rerun the failing tests, until they pass: #RStats

Friends Don't Let Friends Make Bad Graphs! Do you agree with the examples of bad graphs and the alternatives Chenxin Li (@chenxinli2.bsky.social) lists at https://github.com/cxli233/FriendsDontLetFriends

GitHub - cxli233/FriendsDontLetFriends: Friends don't let friends make certain types of data visualization - What are they and why are they bad.
Friends don't let friends make certain types of data visualization - What are they and why are they bad. - GitHub - cxli233/FriendsDontLetFriends: Friends don't let friends make certain ty...

Easier debugging of piped analyses in R: https://github.com/MilesMcBain/breakerofchains by @…

If you set limits for a scale (e.g. x-axis) in ggplot, how would you like data outside of that range be handled? There is the oob parameter for that and a set of functions to use with it: https://scales.r-lib.org/reference/oob.html

The {cli} package makes it easy to show pretty and informative messages to the user of your code. #rstats #terminal

GitHub - r-lib/cli: Tools for making beautiful & useful command line interfaces
Tools for making beautiful & useful command line interfaces - r-lib/cli

{constructive} prints code that can be used to recreate R objects. Like dput, but better... #rstats

Display Idiomatic Code to Construct Most R Objects
Prints code that can be used to recreate R objects. In a sense it is similar to base