Bruno Rodrigues
@brodriguesco
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Sworn in Data Janitor blog: https://t.co/id384GeKXV youtube: https://t.co/zKHU0YfLcA mastodon: https://t.co/Dooa7319vP bsky: https://t.co/LKIAD3RUnw "nix solves this"
Joined November 2014
My book is done. I need to write a conclusion to the last chapter and will likely rewrite some paragraphs, but I won't make major changes anymore. So if you're interested in building reproducible analytical pipelines with #RStats, take a look it's free:
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me: I need to compute some summary statistics and t-test.R: yes.me: also linear regression.R: sure.me: pretty graphs.R: gotcha.me: I'd also like to build an interactive game like a clone of wordle.R: you're not gonna believe this
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why use a general purpose programming language when you have a clear purpose and could use a language tailored to the problem instead?
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if you're a data 'anything' and wonder "why is R still a thing?" maybe this answer I wrote on Reddit will help #RStats #pydata #datascience
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And another chapter done! Learn about build automation using {targets}. If you’re interested in upping your data science game and build reproducible analytical pipelines, give my book a read, it’s free:. Comments more than welcome! #RStats #DataScience
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Python data scientists trying out the tidyverse for the first time, 2038.
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if your language of choice doesn’t allow me to write like this, I don’t want it
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#RStats is used by 69 billion people each day. But no one uses it effectively. Here are 420 tips and tricks you should know TODAY to extract value from your data:.
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I've just read that that Yihui Xie @xieyihui left @posit_pbc . he will continue to work on his packages as a contractor . that's really surprising (not in a good way) news to start 2024. .
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The final PDF of the book, ready for print, is 520 pages long.
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I don't think I've ever read the paper that introduced the R programming language. here it is #RStats
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#RStats anecdote: When I started learning econometrics at Uni in France, I asked the professor which software was the standard. He said "Air". That evening at home I Google "Air econometrics software" but didn't find anything. I asked him the next day to clarify. .
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Little #RStats function I use when I quickly need to open the result of various %>% operations in Excel. as in : mtcars %>% filter(am == 1) %>% show_in_excel()
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amazing read by @nntaleb and providing a cheap black and white version of the book as print on demand is a great idea
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how data scientist got psyoped into using notebooks and python I’ll never understand.
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If you use #rstats and are interested in reproducibility but confused by all of the ecosystem around it, I'm currently working on an ebook that should. Called "Building reproducible analytical pipelines with R" you can start reading it here
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Let me take this opportunity to shill the infer #RStats package. read the vignette which explains why charts like the one below can be ignored nowadays (we have very good computers these days).
How I pick the right statistical test for my experimental variables
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New domain name for my e-book, Modern R with the tidyverse. modern-rstats dot eu.
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for those of you that might not understand why the claim in this tweet is so ridiculous, here’s the @duckdb benchmark showing how many popular data analysis packages perform on data with 1000000000 rows.
@JuddLegum @elonmusk In my initial run, which processed the first 60,000 rows, I did not find these awards—my hard drive overheated long before I could complete a full pass through the database. In a later run, which I referenced in another post, I did identify two such awards. That discrepancy is a.
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My new book project, "Building reproducible analytical pipelines with #rstats", will teach you how to make projects reproducible. Manifest your interest here: . just want to read the WIP version? 👇. if you prefer physical 1/2.
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I really love this . The {targets} #RStats package is probably one of the most underrated packages out there! Give it a try! You won't regret it!
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Are you struggling to see how #Docker can make your #datascience pipelines reproducible? Want to learn how to make projects reproducible?Take a look at the latest chapter of my free book:. Comments more than welcome! #RStats #DataScience
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a very cool illustration showing why you shouldn’t use loops in #RStats : remember, many operations in R are vectorized and will be very quick if you take advantage of this!.
More languages, more insights!. A few interesting takeaways:. * Java and Kotlin are quick! Possible explanation: Google is heavily invested in performance here. * Js is really fast as far as interpreted / jit languages go. * Python is quite slow without things like PyPy.
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Btw I'll be teaching this year's course on reproductibility with R, Docker and Nix starting next Monday . it's up: mostly unchanged from last year.
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It is with great joy that I announce today that our (together with @PhilippBauman15 ) package rix is now on CRAN:. #RStats.
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Really happy with how it looks! I keep looking at it!
The proof is in, and it's looking niiiiiice!. Building reproducible analytical pipelines with #rstats will be available on Amazon on June 20th!
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Just finished the chapter on testing in my book. If you’re interested in upping your data science game and build reproducible analytical pipelines, give my book a read, it’s free:. Comments more than welcome! #RStats #DataScience
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you're excited for GTA 6, I'm excited for R 4.4.3, where not the same.
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Today is my birthday, so I thought I'd make a coupon code so you can get a DRM-free Epub and Pdf of Building reproducible analytical pipelines with #rstats for 14.99 . Physical books are coming next week to Amazon !
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The proof is in, and it's looking niiiiiice!. Building reproducible analytical pipelines with #rstats will be available on Amazon on June 20th!
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New blog post: Machine learning with {tidymodels} (by @topepos ). Learn how to tune several models in parallel using list of models, list of grids and furrrr::future_map() (by @dvaughan32 )! #rstats #datascience
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Python is the best language for statistical analysis and data science hands down. I'm currently porting all my reproducible pipelines (R in Nix shells) over to Jupyter notebooks (pip is all you need) running inside docker containers.long live Pandas!.this now a #pydata account.
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You can now get physical copies of my book, "Building reproducible analytical pipelines with #RStats" on (USA only for now):. other marketplaces (FR, DE, ES, and more) will follow in the coming days!.
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Please, if you have an idea for a package, just write it and publish it on CRAN. The availability of high quality packages are one of #RStats greatest strengths, just package stuff please
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I love the {withr} #RStats package. Need to create a single plot? Just use withr::with_package("ggplot2", . )
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You can get the Docker image with all the code and slides here: the slides are also online here:
𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗿𝗲𝗽𝗿𝗼𝗱𝘂𝗰𝗶𝗯𝗹𝗲 𝗮𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝗮𝗹 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀 𝘄𝗶𝘁𝗵 𝗥 . Join #ReproT 𝟭𝟵 𝗝𝘂𝗹𝘆, where Dr Rodrigues @brodriguesco will show how to make research more reproducible: @jessiebaldwin.@SwissRN.@ukrepro.@ReproducibiliT
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Imagine unironically doing geospatial analysis with Python instead of R.
Laptop was a bit low on memory so I uninstalled a few useless programs. Starting with R.
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"Air, like ze letter R!". Yes the letter R in French is pronounced like the English word for "Air". This was the first time I heard of R, that was in 2009. little did I know that "Air" would become my main work tool!.
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@Cor3ntin I ask myself following question: has there ever been any vaccine, any at all ever, where several decades after a vaccination campaign people developed any disease due to said vaccine?.
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QT with a meme you made
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My new (invited) blog post for @rdata_lu : Skip errors in R loops by not writing loops #rstats #purrr #DataScience @k_rosamont
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ALT-F4 and then double clicking on RStudio.
what’s your favorite excel shortcut?.
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#RStats 4.4.3, released 40 minutes ago, is already available through rix by using today’s date!
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I'm very happy to announce that {chronicler}, an #RStats 📦 I've been working on for 3+ months is now available on CRAN! The following blog post introduces it very quickly:. but continue scrolling down if you want an even TL;DR summary!
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Building reproducible analytical pipelines with #rstats will be available on Amazon on June 20th. 34.99$, 29.99£, 29.99€, 44.99CAD. You can buy a DRM free epub and pdf at for 19.99 (min. price). You can read it for free forever at
The final PDF of the book, ready for print, is 520 pages long.
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hey, if you want to give me a christmas present, why not give my book a review if you bought it? but only if you got nice things to say, if not screw you (no refunds).
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just got a 500€ donation for my open source work wow biggest donation I’ve ever received! I’m really so happy my work is helpful!
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new blog post: teaching the #tidyverse to beginners: . This blog post details what I covered and how the participants to the courses reacted to it! #rstats. @drob @strengejacke @hadleywickham.
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#Python users, which R packages do you use, if any? Does it annoy you to have to use them? Why/why not? please RT.
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It is now possible to easily pass data from and to Python and #RStats by serializing to json (but you can still convert more complex objects using rxp_py2r() and rxp_r2py() which uses {reticulate} under the hood for conversin)
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New blog post: Reproducible #DataScience with #Nix, part 6 -- CI/CD has never been easier. or how to run an #RStats {targets} pipeline on Github Actions using #Nix
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Need a last minute gift for the fan of reproducibility and #RStats fan in your life?. Get my ebook, "Building reproducible analytical pipelines with R" for $9.99. Merry Christmas!
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PSA: If you're an R user and rely on MRAN for reproducibility, you should know MRAN is getting shutdown. You might want to start migrating to the @posit_pbc package manager which also allows you to use packages as of a specific date like MRAN.
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Just changed like 100 grepl calls to stringi::stri_detect and my pipeline now runs 4 times faster #RStats.
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Started writing the preface to the python edition of "Building reproducible analytical pipelines with. "
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Even though I think #RStats is the superior choice when it comes to data *anything*, I think I might work on a python edition of the book. Those notebooks hosted on Github without any requirements.txt or Dockerfiles need to stop!.
Need a last minute gift for the fan of reproducibility and #RStats fan in your life?. Get my ebook, "Building reproducible analytical pipelines with R" for $9.99. Merry Christmas!
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The year is 2029. Data Scientists fresh out of school now clean data by opening CSV files in Excel and directly writing the needed Python code in the Workbook. They still do mean imputation.
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New blog post: Reproducible data science with Nix, part 13 -- {rix} is on CRAN!. #RStats #DataScience #nix
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Looking for a nice introduction to #reproducibility using #Docker and #RStats? @_ColinFay has you covered with this great blog post!
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rix v0.14.3 is on CRAN with many new features and improvements!. Thanks to the many contributors for this release (credited in the DESCRIPTION file). Here is a sneak peak of what awaits you: . 1/4.
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New release of rix on CRAN!.rix generates Nix expressions which are then used by the Nix package manager to build.reproducible #RStats development environments. Many new features in this release:. 1/3
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R's native pipe is almost 4 years old, I think I'll start using it inside my packages (thus requiring at least #RStats 4.1.0 to be installed)
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R devs: "🤔 my package depends on this other well-maintained package for just 3 functions, guess I'll refractor everything to get rid of that dependency and lower risk for my users". JS devs:.
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it's really fucking hard to find competent engineers. i've interviewed about 20 cs majors who claim to be experts at R, and none of them have been able to explain what subseting an object of type closure means.
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New #RStats x #Nix blog post: Reproducible data science with Nix, part 9 -- rix is looking for testers!. Check out the latest feature implemented by @PhilippBauman15 , with_nix(), it'll blow your mind!
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Almost one year ago, I’ve ran all example scripts shipped in versions of R from 0.6.0 up to 4.2.2 on R version 4.2.2 . as you can see, #RStats 4.2.2 is still able to run more than three quarters of the examples of the oldest release of R!
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