javascript - 在 D3 中绑定(bind)大数组

Question

我正在使用 D3 可视化绑定(bind)到 map 的数据，但我不知道应该处理多大的列表。

如果我使用行业数据，大约有 20 个左右的 NAICS，这很容易。

例如，我使用以下代码绑定(bind)来自 geojson 的数据:

 var values = feature.properties;              
 var data = [
    {key: "Agric.,forestry., fishing.,hunting.", name:"N11",value:values["N11"]},
    {key: "Mining.,quar., oil,gas", name:"N21",value:values["N21"]},
    {key: "Utilities", name:"N22",value:values["N22"]},
    {key: "Constr.", name:"N23OL",value:values["N23"]},
    {key: "Manuf.", name:"N31_33OL",value:values["N31-33"]},
    {key: "Wholesale trade", name:"N41OL",value:values["N41"]},
    {key: "Retail trade", name:"N44-45",value:values["N44-45"]},
    {key: "Transportation, warehousing", name:"N48-49",value:values["N48-49"]},
    {key: "Information, cultur.industries", name:"N51",value:values["N51"]},
    {key: "Finance, insurance", name:"N52",value:values["N52"]},
    {key: "Real estate, rental,leasing", name:"N53",value:values["N53"]},
    {key: "Prof.scientific, techn.services", name:"N54",value:values["N54"]},
    {key: "Management companies,enterprises", name:"N55",value:values["N55"]},
    {key: "Admin.support, waste.manag., remed.services", name:"N56",value:values["N56"]},
    {key: "Educational services", name:"N61",value:values["N61"]},
    {key: "Health.care, social.assistance", name:"N62",value:values["N62"]},
    {key: "Arts,entertainment, recreation", name:"N71",value:values["N71"]},
    {key: "Accommodation, food.services", name:"N72",value:values["N72"]},
    {key: "Other.services (except.pub. admin.)", name:"N81",value:values["N81"]},
    {key: "Public administration", name:"N91",value:values["N91"]}
];   

现在，如果我想使用职业数据，它会变得很棘手，因为它们大约有 800 个。显然，像这样手动输入它们是不切实际的。这将如何处理？使用 d3.csv 导入 CSV 并加入 geojson 数据对象？我不知道从哪里开始。

这是我对较小集合所做的一个例子:https://jsfiddle.net/Monduiz/tr5pxv1s/

Answer 1

听起来您很清楚自己在做什么，只是错过了最好的学习示例:

Example visualisation mapping reasonably large data-set loaded from tab-separated-values .

该示例中容易忽略的是它如何使用 d3.queue()、defer() 和 await() 来确保数据以正确的顺序加载和处理。

另见 documentation for other CSV-related functions .