Tootfinder

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

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

GitHub - MilesMcBain/breakerofchains: Break your chain at the cursor line. Run the first bit. See the output. Be free.
Break your chain at the cursor line. Run the first bit. See the output. Be free. - MilesMcBain/breakerofchains

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

A very detailed walk-through of adding a property to #Wikidata, while contributing some data cleanup using #Rstats
https://

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.

Try this in #Rstats :
x <- -42
x^2.3
==> NaN ("not a number")
Now try this:
-42^2.3
==> -5413.441
🤯
(adapted from the wonderful 'R Inferno' by Patrick Burns #precedence

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.

This looks helpful: #rstats #optimization

Visualize dependencies between functions: #rstats

GitHub - lewinfox/foodwebr: Function dependency graphs in R
Function dependency graphs in R. Contribute to lewinfox/foodwebr development by creating an account on GitHub.

I could not not share my favorite image of the week... Month... Maybe year, with the #rstats folks over here!

Make fancy tables: #rstats #tables

RE: #rstats

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.

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

I'm working on something big: A new package for async communication between R and Emacs. The output should be a terminal run in Emacs, at the level of Arf and Radian.
If you use #rstats on #emacs stay tunned

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

RE: #rstats

#TIL that #RStudio supports multiple levels of code sections. The level depends on the number of # signs at the beginning of the line.
# First Level -----
## Second level ------
This is also reflected in the document outline you get with Cmd Shift O (on a Mac, I guess it's Ctrl Shift O anywhere else).
Why did no-one tell me that earlier?!?
#rstats

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…

R learning for applied statistics by Chenxin Li: #rstats

{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.

RE: #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.

I wrote a short post with my thoughts on #emacs #ESS and why I created ESR, my tree sitter mode for R. After 10 years doing #rstats programming in ESS, I finally managed to move away from it.
P…

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...

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

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

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

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

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

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.

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.

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

Everything is a linear model: #rstats #stats

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

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.

{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.

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.

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

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.

Use cookies in shiny apps: #rstats #shiny

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

{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

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.

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.

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

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.

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

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

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.

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

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.

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.

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

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.

{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

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

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.

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

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

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

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

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

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

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

Allison Horst - R Packages & Functions

A template for data analysis projects structured as R packages (or not) https://github.com/Pakillo/template by @…

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

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

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

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

GitHub - MilesMcBain/breakerofchains: Break your chain at the cursor line. Run the first bit. See the output. Be free.
Break your chain at the cursor line. Run the first bit. See the output. Be free. - MilesMcBain/breakerofchains