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2024-04-20 10:00:01

{slider} helps with aggregation over (sliding) windows, both index and time period based: #rstats
2024-04-19 10:00:01

{lubridate} makes working with dates in R just that little bit easier: #rstats #dates
2024-04-21 10:00:01

Do you (sometimes) use print() or message() for debugging your code? Next time you can use {icecream} instead:
2024-05-14 16:18:26

Simple #Rstats problem: Suppose you have a vector like this:
vec <- c('A/B', 'C/D', 'E/F')
For each element, you want the value after the '/', i.e. B, D, and F. How would you do it?
After years and years of using R, I just learned that you can do this:
sapply(strsplit(vec, '/'), '[', 2)
Did you KNOW this? The extraction operator '[' is given as a function to sapply() here and the 2 as an argument. 🤯
If you knew this: WHY DIDN’T YOU TELL ME?!?
2024-04-13 15:51:19

just a couple years of language and package updates, what could go wrong? #Rstats

renv doing its thing
2024-03-21 11:00:01

I am more fluent in LaTeX than in plotmath expression. If you are the same, latex2exp will make your life easier.
2024-04-11 11:29:05

Any #rstats people know how to capture / react to a hover event in #shiny (using a #quarto doc)? The examples I'm finding are old / don't work..
2024-04-18 10:00:02

Keep track of the TODO notes in your code: #rstats #todo
2024-05-18 10:00:01

Do you need inspiration how to present a dataset in a clear figure and what package to use? Check out #rstats
2024-06-18 10:00:00

A pictures says more than 1000 words. How much more can an audio representation of your data tell you? #rstats <…
2024-04-22 14:16:59

This new blog by Nick Clark providing tips for ecological modeling with a focus on time-series/forecasting and #rstats is excellent. I highly recommend checking it out.
2024-05-31 14:12:09

🚀 Introducing rJavaEnv: A new R package to manage multiple Java JDKs for your R projects! 🎉
2024-06-17 10:00:01

The {esquisse} package makes it easy to plot your data in different ways with a drag and drop interface: #rstats
2024-04-17 10:00:01

A curated list of awesome tools to assist 📦 development in R programming language. #rstats #📦
2024-05-19 10:00:00

{ggchicklet}: library for rounded Segmented Column Charts: #ggplot #rstats
2024-04-16 10:00:01

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 <…
2024-06-15 10:00:01

Use cookies in shiny apps: #rstats #shiny
2024-05-26 10:33:18

Cannot find any ready-to-use open source software (or even a combination of software) that would solve the travelling salesperson problem using public transit. Am I missing something? Any suggestions? #rstats #gtfs #urbanmobility
2024-05-15 10:00:01

quick and easy way to build a website for your r package: #rstats #package
2024-04-15 10:00:01

The {purrr} package is a powerfull way to replace loops. The {furrr} package takes this approach one step further by parallel execution: #rstats <…
2024-06-14 10:00:01

Cute comics of R functions: #rstats
2024-04-14 10:00:01

Make sure your code follows a consitent style using the {lintr} package. #rstats
2024-04-12 09:52:44

I have programmed a small #rstats script combining the web-based #API of our SolarEdge #photovoltaic system with the local API of our go-e #wallbox.
If the car charges, the script looks up the production of the PV system and increases/decreases the charging current for the car accordingly. This makes the most of the collected #solar power. What now runs on an old #Raspberry Pi would’ve easily cost us 500 EUR installation costs – and I have full control over everything! 🤓🤩
2024-05-14 10:00:01 provides example code for a variety of chart types, both in base R and ggplot: #rstats
2024-04-13 10:00:01

The {cli} package makes it easy to show pretty and informative messages to the user of your code. #rstats
2024-04-12 10:00:01 provides example code for a variety of chart types, both in base R and ggplot: #rstats #ggplot
2024-03-23 11:00:01

What They Forgot to Teach You About R: #rstats
2024-06-10 10:00:01

Use multi level models with {parsnip}: #rstats #ML
2024-04-10 10:00:01

{constructive} prints code that can be used to recreate R objects. Like dput, but better... #rstats
2024-05-10 10:00:01

R doesnt need to be a hard and scientific tool 📈. You can use it to make art 🎨: #rstats
2024-04-09 10:00:01

Function-oriented Make-like declarative workflows for R #rstats
2024-06-09 10:00:02

The inner working of parquette/arrow data in R: #rstats
2024-05-09 10:00:01

Add highlighting to your quarto presentation using the RoughNotation library: #rstats
2024-05-08 10:00:01

Yet another package to speed up different calculations in R: #rstats
2024-04-08 10:00:01

A template for data analysis projects structured as R packages (or not) #rstats #datascience
2024-06-08 10:00:02

{dtrack} makes documentation of data wrangling part of the analysis and creates pretty flow charts: #rstats
2024-06-07 10:00:00

Make paint-by-number pictures in R: #rstats
2024-05-07 10:00:01

Are you interested in how dependency-heavy your (or another) package is and why? #rstats
2024-06-05 10:00:01

Handy RStudio addins for reshaping and navigating in code: #rstats #rstudio
2024-04-05 10:00:01

Automatically describe data and models as text using the {report} package. #rstats
2024-05-04 10:00:01

Need some data to test a plot idea or algorithm? On #rstats #synthetic
2024-06-04 10:00:01

Lets be honest, we spend too much time cleaning data. {janitor} can help with that: #rstats
2024-04-03 10:00:01

If you feel you should be reading more: #rstats #ebooks
2024-05-24 10:00:01

Base pipe vs magrittr pipe: a thread by TimTeaFan: #rstats
2024-06-12 10:00:01

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
2024-06-02 10:00:01

Visualize dependencies between functions: #rstats
2024-06-01 10:00:01

Make fancy tables: #rstats #tables
2024-05-01 10:00:01

This looks helpful: #rstats #optimization
2024-04-01 10:00:01

{ggdist}: Visualizations of distributions and uncertainty #rstats #ggplot<…
2024-03-31 10:00:01

{piggyback} makes it easier to attach large files (e.g. input data) to code in github repos: #rstats
2024-05-31 10:00:01

Add some swag to your ggplots, with fontawesome symbols and colors: #rstats
2024-05-31 10:00:01

Add some swag to your ggplots, with fontawesome symbols and colors: #rstats
2024-03-30 11:00:01

Primer to get you started with Optimization and Mathematical Programming in R #rstats
2024-04-29 10:00:01

If you use Quarto to make presentations for a professional setting, it is important to choose the right theme, e.g. #rstats
2024-05-30 10:00:01

R learning for applied statistics by Chenxin Li: #rstats
2024-04-28 10:00:01

TidyX: screencasts explaining different aspects of the R language and the coding process. #rstats
2024-05-29 10:00:01

{purrr} has some lesser known functions that make handling of failing function calls easier: safely, quietly, possibly: #rstats
2024-05-28 10:00:01

Interactive resizing of picture and table content in Rmd and Quarto: #rstats
2024-03-27 11:00:01

{spiralize} can be used to highlight cyclic data, e.g. multi year time series. #rstats
2024-05-27 10:00:01

The {conflicted} package makes sure that namespace conflicts are solved explicitly and prevents unpleasent surprises: #rstats
2024-05-25 10:00:01

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
2024-03-26 11:00:01

{ggbump} creates elegant bump charts in ggplot. #ggplot #rstats
2024-04-25 10:00:01

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
2024-03-25 11:00:01

Getting started with Shiny to make interactive web-apps with R: #rstats
2024-04-23 10:00:01

Keynote from rstudio::conf 2022: The past and future of shiny. #rstats
2024-04-07 10:00:01

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.
2024-05-23 10:00:01

The fastverse is a suite of complementary high-performance packages for statistical computing and data manipulation in R. #rstats
2024-05-22 10:00:01

Customize what happens when you start R: #rstats #environment
2024-03-22 11:00:01

The dbcooper package turns a database connection into a collection of functions. #rstats
2024-05-06 10:00:01

Using fonts in R graphics can be tricky at times. {showtext} aims to make it easier: #rstats
2024-06-06 10:00:01

Friends Don't Let Friends Make Bad Graphs! Do you agree with the examples of bad graphs and the alternatives Chenxin Li ( lists at
2024-06-03 10:00:01

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:
2024-05-03 10:00:01

Sometimes you get data in less than optimal format, e.g. as a png of a figure 😭... In that case might be the rescue.
2024-05-02 10:00:01

Find the best contrast between one color and a list of options, e.g. for labels in geom_tile: {prismatic::best_contrast()}
2024-03-29 11:00:01

Follow along when @… walks you through how she tackles a new dataset:
2024-04-26 10:00:01

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:
2024-05-26 10:00:01

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