Update README

Author: mbostock

README.md

@@ -940,9 +940,7 @@ Plot’s option transforms, listed below, do more than populate the **transform*
 
 [<img src="./img/bin.png" width="320" height="198" alt="a histogram of athletes by weight">](https://observablehq.com/@data-workflows/plot-bin)
 
-[Source](./src/transforms/bin.js) · [Examples](https://observablehq.com/@data-workflows/plot-bin) · Aggregates continuous data — quantitative or temporal values such as temperatures or times — into discrete bins, and then computes summary statistics for each bin such as a count or sum. The bin transform is like a continuous [group transform](#group) and is often used to make histograms.
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-There are several variants of the bin transform depending on which dimensions need binning: [Plot.binX](#plotbinxoutputs-options) for *x*; [Plot.binY](#plotbinyoutputs-options) for *y*; and [Plot.bin](#plotbinoutputs-options) for both.
+[Source](./src/transforms/bin.js) · [Examples](https://observablehq.com/@data-workflows/plot-bin) · Aggregates continuous data — quantitative or temporal values such as temperatures or times — into discrete bins, and then computes summary statistics for each bin such as a count or sum. The bin transform is like a continuous [group transform](#group) and is often used to make histograms. There are separate transforms depending on which dimensions need binning: [Plot.binX](#plotbinxoutputs-options) for *x*; [Plot.binY](#plotbinyoutputs-options) for *y*; and [Plot.bin](#plotbinoutputs-options) for both.
 
 Given input *data* = [*d₀*, *d₁*, *d₂*, …], by default the resulting binned data is an array of arrays where each inner array is a subset of the input data [[*d₀₀*, *d₀₁*, …], [*d₁₀*, *d₁₁*, …], [*d₂₀*, *d₂₁*, …], …]. Each inner array is in input order, while the outer array is in natural order according to the associated dimension (*x* then *y*). Empty bins are skipped. By specifying a different aggregation method for the *data* output, as described next, you can change how the binned data is computed.