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122 points todsacerdoti | 1 comments | | HN request time: 0.214s | source
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ngriffiths ◴[] No.42193839[source]
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): >>42193979 #>>42194909 #
_Wintermute ◴[] No.42194909[source]
In my opinion R should thought of as an unbeatable graphical calculator, but an awful programming language.
replies(2): >>42197177 #>>42198754 #
williamcotton ◴[] No.42197177[source]
The tinyverse collection of packages makes things a lot more sane, IMO:

  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()
replies(1): >>42202384 #
1. _Wintermute ◴[] No.42202384[source]
True, but trying to wrap any of that into a function rather than simple scripts makes you delve into the ever-deprecated API for non-standard evaluation.