An OJS Primer

Okay, I need the primer on OJS; I liked the flexibility of setting up the input values but I am not feeling the syntax of the plots.

This Repo helped me figure out setting up the input values using a data frame including correcting converting the data. The quarto page helped me figure out how to filter the data.

Claude provided a conversion steps from ggplot2 to Observable JS plot.

Yes, you can convert a ggplot2 script to an Observable JS plot. Here’s an approach to translate ggplot2 concepts to Observable JS using the Plot library:

import * as Plot from "@observablehq/plot";

// Assuming similar data structure to R/ggplot2
const data = [
  {category: "A", value: 10},
  {category: "B", value: 15},
  {category: "C", value: 12}
];

// Equivalent to ggplot(data, aes(x=category, y=value)) + geom_bar(stat="identity")
const barPlot = Plot.plot({
  marks: [
    Plot.barY(data, {
      x: "category", 
      y: "value",
      fill: "category"
    })
  ],
  x: {label: "Category"},
  y: {label: "Value"},
  color: {legend: true},
  title: "Bar Plot Conversion"
});

// Scatter plot equivalent
// ggplot(data, aes(x=x, y=y, color=category)) + geom_point()
const scatterPlot = Plot.plot({
  marks: [
    Plot.dot(data, {
      x: "x", 
      y: "y",
      fill: "category"
    })
  ],
  color: {legend: true}
});

// Line plot equivalent
// ggplot(data, aes(x=x, y=y, group=category)) + geom_line()
const linePlot = Plot.plot({
  marks: [
    Plot.line(data, {
      x: "x",
      y: "y",
      stroke: "category"
    })
  ]
});

// Render the plot
document.body.append(barPlot);

Key conversion tips: - ggplot() → Plot.plot() - geom_bar() → Plot.barY() - geom_point() → Plot.dot() - geom_line() → Plot.line() - Aesthetic mappings (aes) become configuration objects - Styling and legends are handled similarly but with different syntax

The main differences are in the configuration approach and method names. Observable JS Plot is more functional and uses method chaining differently from ggplot2’s layered approach.