Tootfinder

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

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

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.

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

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

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

GitHub - hrbrmstr/ggchicklet: 🀫 Create Chicklet (Rounded Segmented Column) Charts
🀫 Create Chicklet (Rounded Segmented Column) Charts - hrbrmstr/ggchicklet

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

I have often been unhappy that the line type in a #ggplot2 legend is not clearly visible. Today, I found a simple solution: simply use
theme(legend.key.width = unit(1, "cm"))
Replace 1 with any other value that you like (not too small, of course!).
#rstats

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.

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

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.

Dear #rstats users of #emacs I am developing an Emacs Major Mode to use treesitter with R and #ESS I've been using it for over 2 weeks now and it is looking good, but it would greatly benefit from…

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

Hey #rstats folks! I'm curious to know if you use {renv} when developing packages? Or are there any downsides to it?

Use cookies in shiny apps: #rstats #shiny

#rstats #spanishoddata will be presented next week at the MNO-MINDS ESSnet Project Final Conference https://cros.ec.eur…

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.

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.

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.

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

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

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…

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

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.

🚀 #rJavaEnv #rstats (helper for 100 Java-dependent R packages) is about to get its biggest update yet. Just in time for ~10k downloads, Java 25 release, and its CRAN bday!
👉 Dev version:

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

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

Allison Horst - R Packages & Functions

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.

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

New #rstats https://github.com/e-kotov/gridmaker Creates Eurostat GISCO compatible and INSPIRE-compliant grids with IDs that look like ‘CRS3035RES1000mN3497000E4448000’ or ‘1kmN3497E4447’. Input can be sf, or …

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

GitHub - cj-holmes/paintr: Create paint by numbers images
Create paint by numbers images. Contribute to cj-holmes/paintr development by creating an account on GitHub.

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

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

#Accessibility modelers using #r5r #rstats, check this GUI for playing around with R5 network. If many people find it useful, I would get signal if I should invest any more free time into it.

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.

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.

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.

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

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

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

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

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

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...

Visualize dependencies between functions: #rstats

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

Make fancy tables: #rstats #tables

This looks helpful: #rstats #optimization

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

{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.

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.

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

R learning for applied statistics by Chenxin Li: #rstats

GitHub - cxli233/Online_R_learning: Online R learning for applied statistics
Online R learning for applied statistics . Contribute to cxli233/Online_R_learning development by creating an account on GitHub.

{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

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

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

Wrap a function to capture errors — safely
Creates a modified version of .f that always succeeds. It returns a list with components result and error. If the function succeeds, result contains the returned value and error is NULL. If an error occurred, error is an error object and result is either NULL or otherwise.

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

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

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. - GitHub - cxli233/FriendsDontLetFriends: Friends don't let friends make certain ty...

I have a habbit of making (too) many (small) packages for functionality that might be reused in different context. {box} might be an alternative by making scripts into modlues that can be loaded: #RStats

‘box’: Write Reusable, Composable and Modular R Code
A modern module system for R. Organise code into hierarchical, composable, reusable modules, and use it effortlessly across projects via a flexible, declarative dependency loading syntax.

{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

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.

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

Posit

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

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

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

{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.

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

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

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

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

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

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

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

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