Data Science with R @DataSciwithR

Have fun with data.😄 Bengaluru, India Joined September 2018

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Data Science with R @DataSciwithR

2 years ago

Error in `data_color()` at .../tabsplots.R:1300:2: ! `method` must be one of "auto", "numeric", "bin", "quantile", or "factor", not "bins". ℹ Did you mean "bin"? Insane error reporting in gt package of R. Thumbs up to @riannone #rstats must retweet

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Data Science with R @DataSciwithR

2 years ago

Error in `+.gg`: ! Cannot use `+` with a single argument ℹ Did you accidentally put `+` on a new line? This is insane level of error catching. Kudos @hadleywickham ...you are closing in on chatgpt from the human side. #rstats

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michelle huang @michellehuang42

2 years ago

some brilliant UX / design examples i've stumbled upon in japan:

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Data Science with R @DataSciwithR

3 years ago

#rstats the biggest pain of R is this: Figuring out the arguments of a function with pass through parameters often shown as . . . Why can't package authors include those arguments explicitly in the documentation of their package?

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peter davenport @peterdavenport8

3 years ago

r-bloggers.com/2023/02/using-… chat GPT certainly makes quick explanation alt easier #rstats #datascience #statistics #chatgpt #coding

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Data Science with R @DataSciwithR

3 years ago

#rstat users: Has anyone tried chatgpt to improve R code like this (example given is python). Surely we will get interesting examples. Please share yours.

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Mark Tenenholtz @marktenenholtz

3 years ago

What beginners think ML pipelines are: • Data comes in • Model makes predictions • Done What they actually are: • Raw data comes in • Goes through multiple transformation layers • Quality checks, anomaly detection, etc • Feature engineering (continued)

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Data Science with R @DataSciwithR

3 years ago

Can we include links to GitHub issues mentioned here.. this being an important change document ?shiny.rstudio.com/reference/shin… @jcheng

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Data Science with R @DataSciwithR

3 years ago

app.sli.do/event/pBGqEjGP…

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Mark Tenenholtz @marktenenholtz

3 years ago

If you're a data scientist that wants to grow as a builder, here's how. Pick a project that makes you: 1. Scrape data 2. Clean data 3. Organize data 4. Explore data 5. Try many models 6. Deploy models 7. Monitor models If you want to be a builder, master those skills.

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Data Science with R @DataSciwithR

3 years ago

Just discovered the R package "daff". It helps to visualise the changes (adds, deletes, edits) to a data frame. Uses a fantastic color coded tabular HTML visualization of differences. Try it out and provide your feedback. #rstats A big shout out to Edwin de Jonge

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Jack Forge @TheJackForge

3 years ago

If you write code to relieve stress, you're probably meant to be a developer.

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Data Science with R @DataSciwithR

3 years ago

I just completed "Some Assembly Required" - Day 7 - Advent of Code 2015 adventofcode.com/2015/day/7 #AdventOfCode This was the toughest one till now. Good one to practice parsing in R.

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Data Science with R @DataSciwithR

3 years ago

"Probably a Fire Hazard" - Day 6 - Advent of Code 2015 is an ideal problem for R. Try to solve it in minimum lines of code. #rstat adventofcode.com/2015/day/6 #AdventOfCode

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Data Science with R @DataSciwithR

3 years ago

I just completed "I Was Told There Would Be No Math" - Day 2 - Advent of Code 2015 adventofcode.com/2015/day/2 #AdventOfCode

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Data Science with R @DataSciwithR

3 years ago

I just completed "Not Quite Lisp" - Day 1 - Advent of Code 2015 adventofcode.com/2015/day/1 #AdventOfCode Ideal place to start seeing the power of R in a fun way.