Technique example: data loader, R to ZIP

examples/loader-r-to-zip/.gitignore

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+.DS_Store
+/dist/
+node_modules/
+yarn-error.log
+.Rhistory
+.RData

examples/loader-r-to-zip/README.md

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+[Framework examples →](../)
+
+# R data loader to generate a ZIP archive
+
+View live: <https://observablehq.observablehq.cloud/framework-example-loader-r-to-zip/>
+
+This Observable Framework example demonstrates how to write an R data loader that accesses penguin body size measurements, performs multiple linear regression, then outputs model estimates and predictions as two separate CSV files in a ZIP archive.
+
+The data loader lives in [`src/data/penguin-mlr.zip.R`](./src/data/penguin-mlr.zip.R).

examples/loader-r-to-zip/observablehq.config.js

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+export default {
+  root: "src"
+};

examples/loader-r-to-zip/package.json

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+{
+  "type": "module",
+  "private": true,
+  "scripts": {
+    "clean": "rimraf src/.observablehq/cache",
+    "build": "rimraf dist && observable build",
+    "dev": "observable preview",
+    "deploy": "observable deploy",
+    "observable": "observable"
+  },
+  "dependencies": {
+    "@observablehq/framework": "^1.7.0"
+  },
+  "devDependencies": {
+    "rimraf": "^5.0.5"
+  },
+  "engines": {
+    "node": ">=18"
+  }
+}

examples/loader-r-to-zip/src/.gitignore

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+/.observablehq/cache/

examples/loader-r-to-zip/src/data/penguin-mlr.zip.R

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+# Attach required packages (must be installed)
+library(readr)
+library(tidyr)
+library(dplyr)
+library(broom)
+
+# Data access, wrangling and analysis
+penguins <- read_csv("src/data/penguins.csv") |>
+    drop_na(body_mass_g, species, sex, flipper_length_mm, culmen_depth_mm)
+
+penguins_mlr <- lm(body_mass_g ~ species + sex + flipper_length_mm + culmen_depth_mm, data = penguins)
+
+mlr_est <- tidy(penguins_mlr)
+
+mlr_fit <- penguins |>
+    mutate(
+        predicted_mass = penguins_mlr$fitted.values,
+        residual = penguins_mlr$residuals
+    )
+
+# Write the data frames as CSVs to a temporary directory
+setwd(tempdir())
+write_csv(mlr_est, "estimates.csv")
+write_csv(mlr_fit, "predictions.csv")
+
+# Zip the contents of the temporary directory
+system("zip - -r .")