Update README.

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
 <script src="https://d3js.org/d3-hierarchy.v1.min.js"></script>
@@ -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).
 
 <a name="hierarchy" href="#hierarchy">#</a> d3.<b>hierarchy</b>(<i>data</i>[, <i>children</i>]) · [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