@edyhsgr Potentially controversial, but I agree!

I was annoyed when the code demos for a particular uni course relied on #tidyR, because I felt that I hadn't learned enough #baseR yet.

So I stuck to base for my big assignment, only bringing in other packages where needed. It's not that I dislike tidy; it's just that I want to be in control of the packages - I don't want the packages to be in control of me.

📊 Simplify data manipulation with pivot_longer() in R's tidyr library! Reshape wide data to long format effortlessly. Analyze and visualize with ease! 🚀 #DataAnalysis #R #tidyr

Post: https://www.spsanderson.com/steveondata/posts/2023-06-06/

Any #rstats users here that use #tidyr et al. for clustering and ordination?

I'm trying to wrap my head around how I should manage a workflow like:

data -> distance matrix -> clustering or ordination

*without* the benefit of row names to link the original data to the resulting cluster leaf or ordination point.

RT @vbfelix
fill() allows us to impute data with other values from the same variable, considering the direction

#tidyr #tidyverse #rstats

RT @vbfelix
fill() allows us to impute data with other values from the same variable, considering the direction

#tidyr #tidyverse #rstats

I also want to acknowledge that gcplyr is built on foundations laid by the #tidyr package for data tidying and the #dplyr package for data manipulation, the latter of which is the inspiration for its name: a grammar of data manipulation for growth curve data
11/12

One of the outcomes of my work over the last four years is the #tabshiftr R-package.

We all love #tidyr but downloading data from all over the internet reveals that "rectangular messy" is not the same as "disorganised messy" (check out also these pretty cool visuals by Julia Lowndes and @allison_horst on tidy data!). With tabshiftr, I am able to reorganise almost all types of tables with reproducible code, even if they are not rectangular yet.

https://luckinet.github.io/tabshiftr/

One of the outcomes of my work over the last four years is the #tabshiftr R-package.

We all love #tidyr but downloading data from all over the internet reveals that "rectangular messy" is not the same as "disorganised messy" (check out also these pretty cool visuals by Julia Lowndes and @allison_horst on tidy data!). With tabshiftr, I am able to reorganise almost all types of tables with reproducible code, even if they are not rectangular yet.

https://luckinet.github.io/tabshiftr/

Great new features in #tidyr 1.2.0

https://www.tidyverse.org/blog/2022/02/tidyr-1-2-0/

#RStats @rstats

@rstats@gup.pe

@jorge posted a quite interesting #webinar #shortcourse on how to handle data efficiently with #rstats

• data management plans
• version control
• R for reproducible data manipulation
• working on clusters
• data publication

#shateEGU20 #FAIRprinciples #tidyverse #dplyr #broom #tidyr #purrr #readr #ggplot2 #markdown #git #spatialdata