I'm choice 2, using group_nest and map as it retains the original column types and there is no need to rename, although if I put some effort into it I'm sure I could remove the need to enframe and rename. I just don't feel like doing that this morning.

#tidyr #tidyverse #purrr #dplyr #imap #map #RandomWalker

Here is a simple script to show what different distribution densities look like. You can easily achieve this using my TidyDensity package.

#dplyr #ggplot2 #TidyDensity #R #RStats

Na #PythonCerrado2025, tivemos ontem um excelente tutorial do Lucas Marcondes Pavelski https://github.com/lucasmpavelski.

Aprendemos sobre #R, #tidyverse, #reticulate, várias ferramentas essenciais como #ggplot2 e #dplyr, vendo na prática como aplicá-las. Foco na ponte #Python <-> R.

Tudo novidade pra mim, vieram várias ideias interessantes de análises e plots.

#PythonCerrado

I recently saw a kind of stacked donut/pie chart that visualized nested count data (e.g. a sample description with two relevant categories, like favorite ice cream and gender) and wondered how I'd do that in #rstats.

So, if you ever want to make a plot like this, here's the #ggplot2 and #dplyr code: https://gist.github.com/Kudusch/577b6f07c686a64a3aace685fd9f3bee

This wouldn't work well with too many categories and pie charts in general aren't optimal, but for this specific kind/shape of data, I think it works well enough.

Last one for today, I just added random_hypergeometric_walk() to the #dev version of my #R #package #RandomWalker

this package relies on #dplyr #ggplot2 #stats #purrr

#R #RStats #tech #Coding

Hey #RStats hivemind, can someone sanity check me?

for some reason filtering with a value assigned to 'x' isn't working here (I was trying to make a dummy dataset for an lapply + ggplot problem I'm having, and instrad have bumped into this weird inconcistency).

df <- data.frame(name = c("delta^13*C", "delta^13*C", "delta^18*O", "delta^18*O"),
x = c(1,1, 2, 2),
y = c(1,3, 5, 4))

x <- "delta^13*C"

df %>%
filter(name == x)

# [1] name x y
# <0 rows> (or 0-length row.names)

df %>%
filter(name == "delta^13*C")

# name x y
# delta^13*C 1 1
# delta^13*C 1 3

#dplyr

I've talked about creating data.frames and tibbles before, but it is an important topic so I have covered it again. This time specifically from the perspective of creating them from vectors.

Post: https://www.spsanderson.com/steveondata/posts/2025-06-09/

#R #RStats #tibble #dplyr #tidyverse #dataframe #baseR #blog #Technology

I've talked about creating data.frames and tibbles before, but it is an important topic so I have covered it again. This time specifically from the perspective of creating them from vectors.

Post: https://www.spsanderson.com/steveondata/posts/2025-06-09/

#R #RStats #tibble #dplyr #tidyverse #dataframe #baseR #blog #Technology