Yes, definitely like project profiles for task this as well!
I used if statements because in the more complex version I have, there are parameters that create a unique solution sheet for each student. I wanted to use apply to render 30 different versions, and I couldn't figure out a nice way of doing that with project profiles.
The TidyDensity package now includes new functions to calculate the Akaike Information Criterion (AIC) for various distributions, streamlining model quality assessment. Use functions like util_negative_binomial_aic() to automate AIC calculations, ensuring precise model evaluation.
#rstats Do you know what the difference is between nested and packed data? And what does this difference look like in a JSON format? If you're curious about that, please check my last blog post out: https://rdiscovery.netlify.app/posts/2024-05-30_pack-nest/. Cheers😉
@Lluis_Revilla@Mehrad This is exactly the same use cases as @Lluis_Revilla for me. I often use a nested data frame to compute/collect an element based on each row of the initial tibble. For example
@layal
Nice. Thanks for the tangible example. I now see what you both mean 😅
May I suggest adding this example and use-case to your article?
I would also like to express my gratitude for using basepipe (when Magrittr is not needed) and more importantly for defining the packages for each of the functions you have used. This makes it extra clear for the reader especially if they are like me and don't do blind library(tidyverse). 🤓 @Lluis_Revilla
In the development version of {collapse} [v2.0.15, available via install.packages("collapse", repos = "https://fastverse.r-universe.dev")], the pivot() function has received a FUN argument to support aggregation, including a number or hard-coded internal functions that do this "on the fly". Initial benchmarks show that this significantly outperforms other pivot table options in R. More at https://sebkrantz.github.io/collapse/reference/pivot.html (feel free to test and give feedback). #rcollapse#rstats#DataScience
I find it WILDLY FRUSTRATING implementing contrast coding in Julia.
If I use ContrastCoding(), I can specify my own contrast matrices (yay!) but I can't label them. So the regression output just reuses my actual factor levels to label an actual model term that means something like, say, 'mean of levels A and B vs. mean of levels C and D'. Or whatever. To interpret my model, I must make physical notes on a piece of paper about what each term means.
Judging from Dave Kleinschmidt's very useful tour of it, I think possibly it was simply built for someone who learned to specify contrast matrices differently from me.
I infer this from the bit where Dave remarks that the hypothesis matrix is transformed into a contrast matrix in a way that he wouldn't be able to derive off the top of his head. To me, the contrast matrix is great! It's the hypothesis matrix that I have to puzzle over.
@ergative Ah so... yeah a bit of API opacity is common in julia. People are working on that quite hard though, julia community is great at that. If the use-case makes sense (it does!) and there isn't an issue, please do open one.
🐘✨ Great news from Marcela Victoria Soto at R4HR in Buenos Aires! She recently shared updates about their dynamic activities: "Data analysis is crucial for agile decision-making in companies." Join them on June 1, 2024, for the "Data Visualization in HR" event. Perfect for Spanish-speaking R users interested in HR analytics. 📅👥 Read more: https://www.r-consortium.org/blog/2024/05/30/r4hr-in-buenos-aires-leveraging-r-for-dynamic-hr-solutions
How do I find people (especially women and POC and LGBTQ+) who started as scientists and somehow found their way to programming and love it so much but were never formally trained and so they just figure it out as they go but they make it work anyway?? Too specific?? (I’m a half #filipino woman and ally, let’s be pals?) #python#rstats#diversityintech