Bin Transform

Bin Transform

The bin transform aggregates quantitative or temporal data into discrete bins for histograms and heatmaps.

Constructors

Plot.binX(outputs, options)   // Bin on x-axis
Plot.binY(outputs, options)   // Bin on y-axis
Plot.bin(outputs, options)    // Bin on both axes

Basic Usage

// Histogram
Plot.rectY(data, Plot.binX({y: "count"}, {x: "value"}))

// 2D Heatmap
Plot.rect(data, Plot.bin({fill: "count"}, {x: "weight", y: "height"}))

Output Channels

The first argument specifies output channels:

{y: "count"}           // Count items per bin
{y: "sum"}             // Sum values
{fill: "mean"}         // Mean for color
{r: "count"}           // Count for size

Examples

Basic Histogram

Plot.rectY(data, Plot.binX({y: "count"}, {x: "value"})).plot()

Stacked Histogram

Plot.rectY(data, Plot.binX({y: "count"}, {
  x: "value",
  fill: "category"
})).plot()

2D Heatmap

Plot.rect(data, Plot.bin({fill: "count"}, {
  x: "weight",
  y: "height"
})).plot({color: {scheme: "YlGnBu"}})

Custom Thresholds

Plot.rectY(data, Plot.binX({y: "count"}, {
  x: "value",
  thresholds: 20  // ~20 bins
})).plot()

Specific Bin Edges

Plot.rectY(data, Plot.binX({y: "count"}, {
  x: "value",
  thresholds: [0, 10, 20, 50, 100]
})).plot()

Cumulative Distribution

Plot.rectY(data, Plot.binX({y: "count"}, {
  x: "value",
  cumulative: 1
})).plot()

Time-Based Bins

Plot.rectY(data, Plot.binX({y: "count"}, {
  x: "date",
  thresholds: d3.utcMonth
})).plot()

Reducers

Options

Threshold Methods

• "auto" - Scott's rule (default)
• "freedman-diaconis" - Freedman-Diaconis rule
• "scott" - Scott's rule
• "sturges" - Sturges' formula
• Number - Approximate bin count
• Array - Explicit bin edges
• Interval - Time or numeric interval

Notes

• Outputs channels like x1, x2, y1, y2 for bin boundaries
• Use domain to exclude outliers
• Subdivide bins using z, fill, or stroke channels
• Works with faceting for small multiples