From c7b56de5f8461115fc72b718293ec5bf7b437870 Mon Sep 17 00:00:00 2001 From: Mike Bostock Date: Sat, 16 Nov 2019 10:38:49 -0800 Subject: [PATCH] Update README. --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index d0ed59cc..07ce2b10 100644 --- a/README.md +++ b/README.md @@ -14,7 +14,7 @@ A good hierarchical visualization facilitates rapid multiscale inference: micro- ## Installing -If you use NPM, `npm install d3-hierarchy`. Otherwise, download the [latest release](https://github.com/d3/d3-hierarchy/releases/latest). You can also load directly from [d3js.org](https://d3js.org), either as a [standalone library](https://d3js.org/d3-hierarchy.v1.min.js) or as part of [D3 4.0](https://github.com/d3/d3). AMD, CommonJS, and vanilla environments are supported. In vanilla, a `d3` global is exported: +If you use NPM, `npm install d3-hierarchy`. Otherwise, download the [latest release](https://github.com/d3/d3-hierarchy/releases/latest). You can also load directly from [d3js.org](https://d3js.org), either as a [standalone library](https://d3js.org/d3-hierarchy.v1.min.js) or as part of [D3](https://github.com/d3/d3). AMD, CommonJS, and vanilla environments are supported. In vanilla, a `d3` global is exported: ```html @@ -39,7 +39,7 @@ var treemap = d3.treemap(); Before you can compute a hierarchical layout, you need a root node. If your data is already in a hierarchical format, such as JSON, you can pass it directly to [d3.hierarchy](#hierarchy); otherwise, you can rearrange tabular data, such as comma-separated values (CSV), into a hierarchy using [d3.stratify](#stratify). # d3.hierarchy(data[, children]) ยท [Source](https://github.com/d3/d3-hierarchy/blob/master/src/hierarchy/index.js), [Examples](https://observablehq.com/@d3/d3-hierarchy) - + Constructs a root node from the specified hierarchical *data*. The specified *data* must be an object representing the root node. For example: ```json