Video

very important event. Thank you very much❤

Thanks so much, clear and concise

I have a file from the Collegeboard (scorecard) that is 566 MB as a csv on my hard drive. However, the parquet file of the same data only takes up 54 MB. Seems incredible.

now my shiny app works ..great tutorial. even picked up some css

I heard that there is an attempt to develop arrow for shape files to generate maps. How is that coming along?

Great presentation and package, thank you!

I am running a M1 Mac and getting errors even though the arrow package is installed. The message is: Error: This build of the arrow package does not support Datasets

I love these presentations. They are so informative. My only beef is that the code is so tiny and hard to see.

I prefer using glue() (from the glue package) rather than paste.

I use the conflicted package. It is as vital as the here pacakge.

Niiiice!! I missed the live event, I am so glad I'll be able to watch the recording! Thanks so much!

In R there is always a function. The useful package has a function called lower.case(string).

wish you'd also talk about geom_text_path ;)

Very informative and engaging s3ssion, thank you

Thanks a lot 🙏

This is RHE video anyone should watch in order to enhance their ggplot skills! It is definitely not for beginners nor intermediate R users, it's very advanced and elaborative!

Excellent as always from Cara

Thank you for these informative sessions.

I think this is great. The tidyverse packages are may favorite things in R. However, I am having a hard time reading the code here (I know I can go to github) due to the low resolution of the video. Anyway to post up a higher res video?

Yes! I feel good about this r package stuff!

Fantastic. You made this very easy to follow. All set up today without a hitch.

Thanks, girls❤

amazing demo....thanks again Cara

@41:06 There is no difference in output, other than the warning msg for summarise. its excatly the same: tab <- letters[1:4] x <- tibble(g=rep(1:2,each=4), y=c("e","a","b","y","d","c","a","r")) tab x x |> reframe(intersect(y,tab),.by = g) x |> summarise(intersect(y,tab),.by = g) |> suppressWarnings()

@33:17 There is a mistake here. The question was can you use the `.by` on a grouped data. the answer is no. the error is very clear: ! Can't supply `.by` when `.data` is a grouped data frame. What the presenter did is just creating a column called 'by' with the value 'company'. in order to group by within a summarise function, you would need the `.by` (with the dot), otherwise it just create a new column.

Mine is giving an error: Unknown host. Can you help?

Nice talk

good

by any chance, do you have an example of mixed models in bayes factor? I am not sure that I am understanding the examples in the manual.

Why Cant I save this video?

Thank you it was very interesting.

Thanks for the tutorials

😘 *promo sm*

The code for finding the number of lines for each character can be condensed from using group_by, summarize and arrange with a single line of code: count(character, name = "lines", sort = TRUE).

🎉🎉🎉

Hi Divya and Julia, Thank you so much for this great introduction lecture! I was wondering if there is any way I could get my hands on the simulated datasets? I would like to try to explore and analyze eye-tracking data :) Let me know, Sophia

Very helpful

This was the perfect introduction to the BayesFactor package, much clearer than the official manual. Thank you!

Please continue with the content on R packages for data science. I attended some of the channel's workshops. I've already learned a lot.

This is awesome.

Dark background is more difficult to read

The best video I found on this subject, thank you very much

Excellent tutorial Cosima

Absolutely brilliant! Thanks!

Btw... this is incredible work and an amazing talk. Thank you so much Isabella!!!

As much as I love the tidyverse and I greatly appreciate the hard work the team has put into this, I have to say, some of these changes are a bit odd. Even for newcomers, learning so many functions to achieve such similar tasks will be very confusing. Also, although most of the time the tidyverse is quite streamlined, there are cases when it has become too verbose. One example is the summarise(n_x = ncol(pick(starts_with("x")))) ... jeez just look at how much parentheses you have to use to perform a simple operation. If anything, you should be able to get rid of pick() inside that summarise() statement. Also, superseeding map_dfr or map_dfc for an additional list_rbind() or list_cbind() seems super clumsy, too. First of all, map_dfr() and map_dfc() are waaaay easier to remember rbind and cbind. Secondly, why the need to "complicate" things requiring an additional step? Just very bad changes, IMHO, all over the place.

That's a fantastic introduction to the quarto, hats off to Julia Müller.

What an amazing meetup we had!

Greate work juli thanks for sharing. For me the `scale_x_reordered` not work please help to solve error. Reagards

very nice!