Tootfinder

What They Forgot to Teach You About R: #rstats

Linear programs help to find optimal solutions based on a set of constrains. I used {ompr} before, but the new package {tidyLP} looks promising and integrates with the tidyverse. #rstats #linearprograms #optimization

GitHub - colin-fraser/tidyLP: Tidy Linear Programs
Tidy Linear Programs. Contribute to colin-fraser/tidyLP development by creating an account on GitHub.

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.

{duckplyr} is a drop-in replacement for dplyr powered by DuckDB. Keep the familiar dplyr syntax while speeding up work with large datasets: #rstats

A DuckDB-Backed Version of dplyr
A drop-in replacement for dplyr, powered by DuckDB for performance. Offers convenient utilities for working with in-memory and larger-than-memory data while retaining full dplyr compatibility.

Base pipe vs magrittr pipe: a thread by TimTeaFan: #rstats

Thread by @TimTeaFan on Thread Reader App
@TimTeaFan: I see still a lot of #RStats tweets about the base pipe vs. the {magrittr} pipe, often in favor of the former. I have to admit: I still stick to the magrittr pipe and here is...

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.

{ggtintshade} adds a tint/shade aesthetic to ggplot2 in addition to hue. This makes it possible to show groups and subgroups using related colours, and works for both nested and crossed designs: https://github.com/wkumler/ggtintshade

GitHub - wkumler/ggtintshade: Tinting and shading aesthetics for ggplot2
Tinting and shading aesthetics for ggplot2. Contribute to wkumler/ggtintshade development by creating an account on GitHub.

r-ts-mode is now available on Melpa. It has the possibility of being used with ESS but it can also be used independently. A big milestone for the #rstats community of #emacs users.

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

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

The fastverse is a suite of complementary high-performance packages for statistical computing and data manipulation in R. #rstats

GitHub - fastverse/fastverse: An Extensible Suite of High-Performance and Low-Dependency Packages for Statistical Computing and Data Manipulation in R
An Extensible Suite of High-Performance and Low-Dependency Packages for Statistical Computing and Data Manipulation in R - fastverse/fastverse

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

Customize what happens when you start R: #rstats #environment

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

Everything is a linear model: #rstats #stats

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.

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.

{ggchicklet}: library for rounded Segmented Column Charts: #ggplot #rstats

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

Do you need inspiration how to present a dataset in a clear figure and what package to use? Check out #rstats #dataviz

From data to Viz | Find the graphic you need
A classification of chart types based on their input data format.

I am proud to announce that r-ts-mode is now available on GNU ELPA and as such, it can be installed directly from any Emacs installation.
The package provides tree sitter functionality for syntax highlighting, indentation, R standard typos, function search and semantic navigation. The major mode has the possibility of being used with ESS but it can also be used independently.
It represents a big milestone for the

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

Use cookies in shiny apps: #rstats #shiny

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

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

quick and easy way to build a website for your r package: #rstats #package

Build websites for R packages
Generate an attractive and useful website from a source package. pkgdown converts your documentation, vignettes, README, and more to HTML making it easy to share information about your package online.

{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.

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

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

The R Graph Gallery – Help and inspiration for R charts
The R graph gallery displays hundreds of charts made with R, always providing the reproducible code.

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.

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

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

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

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

R doesnt need to be a hard and scientific tool 📈. You can use it to make art 🎨: #rstats

GitHub - cutterkom/generativeart: Create Generative Art with R
Create Generative Art with R. Contribute to cutterkom/generativeart development by creating an account on GitHub.

Add highlighting to your quarto presentation using the RoughNotation library: #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

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.

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.

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

Extract Tables from PDF Documents
Bindings for the Tabula Java library, which can extract tables from PDF files. This tool can reduce time and effort in data extraction processes in fields like investigative journalism. It allows for automatic and manual table extraction, the latter facilitated through a Shiny interface, enabling manual areas selection\ with a computer mouse for data retrieval.

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

GitHub - lionel-/codegrip: Reshaping and navigation commands for R code
Reshaping and navigation commands for R code. Contribute to lionel-/codegrip development by creating an account on GitHub.

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

Allison Horst - R Packages & Functions

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

It has happened to the best of us: You forgot the name of a function or the package that function was in but you are sure its there somewhere and does exactly what you need! Introduce {forgot}, it helps you find that function: https://github.com/parmsam/forgot

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

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

A Grammar of Nested Data Manipulation
Provides functions for manipulating nested data frames in a list-column using dplyr syntax. Rather than unnesting, then manipulating a data frame, nplyr allows users to manipulate each nested data frame directly. nplyr is a wrapper for dplyr functions that provide tools for common data manipulation steps: filtering rows, selecting columns, summarising grouped data, among others.

This looks helpful: #rstats #optimization

Visualize dependencies between functions: #rstats

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

A general vectorised switch() — case_match
case_match() is deprecated. Please use recode_values() and replace_values() instead, which are more powerful, have more intuitive names, and have better safety. In addition to the familiar two-sided formula interface, these functions also have from and to arguments which allow you to incorporate a lookup table into the recoding process. This function allows you to vectorise multiple switch() statements. Each case is evaluated sequentially and the first match for each element determines the cor…

Make fancy tables: #rstats #tables

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

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

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

TidyX
TidyX is a screen cast where we discuss how Data Science topics and code work line-by-line, explaining what they did and how the functions they used work. We also break down the visualizations they create and talk about how to apply similar approaches to other data sets. The objective is to help more people learn R and get involved in the TidyTuesday community. The hosts are Ellis Hughes (@ellis_hughes) and Patrick Ward (@OSPpatrick). Ellis has been working with R since 2015 and has a backgr…

{rsonar} combines lintr, styler, covr and goodpractice into an interactive code quality report for R projects, including technical debt and quality gates: #rstats

R learning for applied statistics by Chenxin Li: #rstats

Rapp turns ordinary R scripts into command-line tools and generates arguments and help from the structure of the script: #rstats

GitHub - r-lib/Rapp: Build CLI applications in R
Build CLI applications in R. Contribute to r-lib/Rapp development by creating an account on GitHub.

{purrr} has some lesser known functions that make handling of failing function calls easier: safely, quietly, possibly: #rstats

Interactive resizing of picture and table content in Rmd and Quarto: #rstats

{tabpfn} brings a pretrained deep-learning model for tabular data to R, with familiar formula, recipe and predict() interfaces: #rstats

GitHub - tidymodels/tabpfn: Foundation Model for Tabular Data via reticulate
Foundation Model for Tabular Data via reticulate. Contribute to tidymodels/tabpfn development by creating an account on GitHub.

The {conflicted} package makes sure that namespace conflicts are solved explicitly and prevents unpleasent surprises: #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

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 #RStats

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. - cxli233/FriendsDontLetFriends

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

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.

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

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

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

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

GitHub - r-lib/actions: GitHub Actions for the R community
GitHub Actions for the R community. Contribute to r-lib/actions development by creating an account on GitHub.