Mastodawn

#Día 2 | Comparaciones – Pictograma | #30DayChartChallenge. Centroamérica suma más de 51 millones de habitantes. El gráfico fue creada usando R con #ggplot2, #dplyr, #tidyr#, #scales, #ggflags, #sf, #rnaturalearth, #rnaturalearthdata, #patchwork.

Ell 🏳️‍⚧️Jan 2

Finally sat down to try to get my head around `reshape()` after being told somewhere that `melt`/`cast` are old hat, `reshape` is the new hotness...the result?

Friendship ended with `reshape`, now me and #tidyr are besties, `pivot_longer`/`pivot_wider` ilu #rlang #dataviz

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kernpanik 🐾 🕊️ ☮ 🖖Dec 11

BTW, so far I have not encountered any scenario in which #tidyR offers solutions superior to #baseR.

I can't speak for anyone else, but in my line of work, I achieve everything I want to do in base R with fewer lines of code than with what tidyR, dplyr and the like have to offer.

confusion matrix

Jun 19, 2024

It's a 72nd day of my #100DaysOfCoding with #R and #RStats. I met #tidyr and #purrr.

Lulu Powerful Jul 18, 2023

@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.

Tyler Smith Apr 28, 2023

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.

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Mike Blazanin Nov 16, 2022

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
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