Makes me curious what state R was at the time, or whatever else could've been useful for deep learning, and the benefits of a new language vs adapting something that exists. Seems like it was a big investment
replies(2):
penguins <- read_csv("penguins.csv") |>
na.omit() |>
select(species, island, bill_length_mm, body_mass_g) |>
group_by(species, island) |>
summarize(
mean_bill_length = mean(bill_length_mm),
mean_mass = mean(body_mass_g),
n = n()
) |>
arrange(species, desc(mean_bill_length))
penguins |>
ggplot(aes(x = species, y = mean_bill_length, fill = island)) +
geom_col(position = "dodge") +
labs(
title = "Mean Bill Length by Species and Island",
y = "Mean Bill Length (mm)"
) +
theme_minimal()