数据可视化：在 React 项目中使用 Vega 图表 (二)
上一篇讲了如何在 React 项目中用 Vega-Lite 绘制基本的 area chart 图表。
本篇将介绍如何绘制多层图表，如何添加图例。
多层图表
通过上一篇文章，我们知道了可以通过 mark, encoding 等来描述我们想要的图表。要实现多层图表，只需要把多个包含上述属性的图表对象放进 layer 数组中就可以。就像栈一样， 从栈顶压入，后压入的（index 大的）图层在上层。
我们在之前的数据中加入用户评论数量 “user_comments”:
"data": {
"values": [
{ "user_comments": 0, "active_users": 0, "date": "2019-10-01" },
{ "user_comments": 3, "active_users": 2, "date": "2019-10-02" },
{ "user_comments": 1, "active_users": 0, "date": "2019-10-03" },
{ "user_comments": 1, "active_users": 1, "date": "2019-10-04" },
{ "user_comments": 2, "active_users": 0, "date": "2019-10-05" },
{ "user_comments": 1, "active_users": 0, "date": "2019-10-06" },
{ "user_comments": 2, "active_users": 1, "date": "2019-10-07" }
]
},
按照与上篇文章案例相同的 Vega-Lite 语法，写一个描述 user_comments 的单层图表。
其实只需要替换部分 y 轴的信息即可。
{
"mark": {"type": "area", "color": "#e0e0e0", "interpolate": "monotone"},
"encoding": {
"x":{
"field": "date",
"type": "ordinal",
"timeUnit": "yearmonthdate",
"axis": {"title": "Date", "labelAngle": -45}
},
"y": {
"field": "user_comments",
"type": "quantitative",
"axis": {
"title": "User Comments",
"format": "d",
"values": [1,2,3]
}
}
}
}
接下来，创建 layer 数组。把上述对象放入数组中，图表没有任何变化，此时仍然是单层图表。
...
"layer":[
{
"mark": {"type": "area", "color": "#e0e0e0", "interpolate": "monotone"},
"encoding": {
"x":{
"field": "date",
"type": "ordinal",
"timeUnit": "yearmonthdate",
"axis": {"title": "Date", "labelAngle": -45}
},
"y": {
"field": "user_comments",
"type": "quantitative",
"axis": {
"title": "User Comments",
"format": "d",
"values": [1,2,3]
}
}
}
}
],
...
把上一篇中 Active Users 的对象加入数组，列在 User Comments 之后：
"layer":[
{
"mark": {"type": "area", "color": "#e0e0e0", "interpolate": "monotone"},
"encoding": {
"x":{
"field": "date",
"type": "ordinal",
"timeUnit": "yearmonthdate",
"axis": {"title": "Date", "labelAngle": -45}
},
"y": {
"field": "user_comments",
"type": "quantitative",
"axis": {
"title": "User Comments",
"format": "d",
"values": [1,2,3]
}
}
}
},
{
"mark": {"type": "area", "color": "#0084FF", "interpolate": "monotone"},
"encoding": {
"x": {
"field": "date",
"type": "ordinal",
"timeUnit": "yearmonthdate",
"axis": {"title": "Date", "labelAngle": -45}
},
"y": {
"field": "active_users",
"type": "quantitative",
"axis": {
"title": "Active Users",
"format": "d",
"values": [1,2]
}
}
}
}
],
当当~ 多层图表出现了。
增加图例
与之前的图表相比，横轴没什么变化，竖轴的位置显示了两层图表的 title。但这样表意不够清晰，用户不能一眼看明白哪个颜色代表哪个数据。所以我们需要引进图例（legend）。
创建图例的方式并不唯一，我通过 stroke 创建图例，用 legend 来优化它的样式。
在任一图层中加入 stroke：
...
{
"mark": {"type": "area", "color": "#e0e0e0", "interpolate": "monotone"},
"encoding": {
"x":{
"field": "date",
"type": "ordinal",
"timeUnit": "yearmonthdate",
"axis": {"title": "Date", "labelAngle": -45}
},
"y": {
"field": "user_comments",
"type": "quantitative",
"axis": {
"title": "User Comments",
"format": "d",
"values": [1,2,3]
}
},
"stroke": {
"field": "symbol",
"type": "ordinal",
"scale": {
"domain": ["User Comments", "Active Users"],
"range": ["#e0e0e0", "#0084FF"]
}
}
}
},
...
图中出现了丑丑的图例：
化妆师 legend 登场，赶紧打扮一下。在顶层的 config 中添加 legend 对象：
...
"legend": {
"offset": -106, // 调节图例整体水平移动距离
"title": null,
"padding": 5,
"strokeColor": "#9e9e9e",
"strokeWidth": 2,
"symbolType": "stroke",
"symbolOffset": 0,
"symbolStrokeWidth": 10,
"labelOffset": 0,
"cornerRadius": 10,
"symbolSize": 100,
"clipHeight": 20
}
现在顺眼多啦！
其实现在不要竖轴的 title 都可以，将 y.axis 对象的 title 删除或置空即可，效果如文章首图。
当图层多的时候，也可以搭配使用 area chart 和 line chart，效果也不错，只需要把该图层的 mark.type 改为 line 即可。
示意图：
在 React 项目中使用
import React from 'react';
import { Vega } from 'react-vega';
// chart config
const jobpalBlue = '#e0e0e0';
const jobpalLightGrey = '#0084FF';
const jobpalDarkGrey = '#9e9e9e';
const areaMark = {
type: 'area',
color: jobpalBlue,
interpolate: 'monotone',
};
const getDateXObj = rangeLen => ({
field: 'date',
type: `${rangeLen > 30 ? 'temporal' : 'ordinal'}`,
timeUnit: 'yearmonthdate',
axis: {
title: 'Date',
labelAngle: -45,
},
});
const getQuantitativeYObj = (field, title, values) => ({
field,
type: 'quantitative',
axis: {
title,
format: 'd',
values,
},
});
const legendConfig = {
title: null,
offset: -106,
padding: 5,
strokeColor: jobpalDarkGrey,
strokeWidth: 2,
symbolType: 'stroke',
symbolOffset: 0,
symbolStrokeWidth: 10,
labelOffset: 0,
cornerRadius: 10,
symbolSize: 100,
clipHeight: 20,
};
const getSpec = (yAxisValues = [], rangeLen = 0) => ({
$schema: 'https://vega.github.io/schema/vega-lite/v4.json',
title: 'Demo Chart',
layer: [
{
mark: {
...areaMark,
color: jobpalLightGrey,
},
encoding: {
x: getDateXObj(rangeLen),
y: getQuantitativeYObj('user_comments', '', yAxisValues),
stroke: {
field: 'symbol',
type: 'ordinal',
scale: {
domain: ['User Comments', 'Active Users'],
range: [jobpalLightGrey, jobpalBlue],
},
},
},
}, {
mark: areaMark,
encoding: {
x: getDateXObj(rangeLen),
y: getQuantitativeYObj('active_users', '', yAxisValues),
},
},
],
config: {
legend: legendConfig,
},
})
const data = [
{ "user_comments": 0, "active_users": 0, "date": "2019-10-01" },
{ "user_comments": 3, "active_users": 2, "date": "2019-10-02" },
{ "user_comments": 1, "active_users": 0, "date": "2019-10-03" },
{ "user_comments": 1, "active_users": 1, "date": "2019-10-04" },
{ "user_comments": 2, "active_users": 0, "date": "2019-10-05" },
{ "user_comments": 1, "active_users": 0, "date": "2019-10-06" },
{ "user_comments": 2, "active_users": 1, "date": "2019-10-07" }
]
const App = () => {
// get max value from data arary
const yAxisMaxValueFor = (...keys) => {
const maxList = keys.map(key => data.reduce(
// find the item containing the max value
(acc, cur) => (cur[key] > acc[key] ? cur : acc)
)[key]
);
return Math.max(...maxList);
};
const yAxisValues = Array.from(
{ length: yAxisMaxValueFor('active_users', 'user_comments') },
).map((v, i) => (i + 1));
const spec = getSpec(yAxisValues, data.length);
return (
resize
在实际项目中，我们必须保证图表大小能跟随窗口大小变化。接下来，我们来实现这个功能。
图表在绘制完成后不会重新绘制，但我们可以通过 React 组件接管宽高值来实现重新绘制。
即:
- 在
state中管理width和height - 通过
setState刷新来实现图表的重绘 - 在生命周期方法中设置事件监听函数来监听
resize事件 - 结合 css 和
ref, 通过图表外的 warper 层得到此时图表正确的宽高值
示例代码如下：
import React from 'react';
import { Vega } from 'react-vega';
// chart config
const jobpalBlue = '#e0e0e0';
const jobpalLightGrey = '#0084FF';
const jobpalDarkGrey = '#9e9e9e';
const areaMark = {
type: 'area',
color: jobpalBlue,
interpolate: 'monotone',
};
const getDateXObj = rangeLen => ({
field: 'date',
type: `${rangeLen > 30 ? 'temporal' : 'ordinal'}`,
timeUnit: 'yearmonthdate',
axis: {
title: 'Date',
labelAngle: -45,
},
});
const getQuantitativeYObj = (field, title, values) => ({
field,
type: 'quantitative',
axis: {
title,
format: 'd',
values,
},
});
const legendConfig = {
title: null,
offset: -106,
padding: 5,
strokeColor: jobpalDarkGrey,
strokeWidth: 2,
symbolType: 'stroke',
symbolOffset: 0,
symbolStrokeWidth: 10,
labelOffset: 0,
cornerRadius: 10,
symbolSize: 100,
clipHeight: 20,
};
const getSpec = (yAxisValues = [], rangeLen = 0) => ({
$schema: 'https://vega.github.io/schema/vega-lite/v4.json',
title: 'Demo Chart',
layer: [
{
mark: {
...areaMark,
color: jobpalLightGrey,
},
encoding: {
x: getDateXObj(rangeLen),
y: getQuantitativeYObj('user_comments', '', yAxisValues),
stroke: {
field: 'symbol',
type: 'ordinal',
scale: {
domain: ['User Comments', 'Active Users'],
range: [jobpalLightGrey, jobpalBlue],
},
},
},
}, {
mark: areaMark,
encoding: {
x: getDateXObj(rangeLen),
y: getQuantitativeYObj('active_users', '', yAxisValues),
},
},
],
config: {
legend: legendConfig,
},
})
const data = [
{ "user_comments": 0, "active_users": 0, "date": "2019-10-01" },
{ "user_comments": 3, "active_users": 2, "date": "2019-10-02" },
{ "user_comments": 1, "active_users": 0, "date": "2019-10-03" },
{ "user_comments": 1, "active_users": 1, "date": "2019-10-04" },
{ "user_comments": 2, "active_users": 0, "date": "2019-10-05" },
{ "user_comments": 1, "active_users": 0, "date": "2019-10-06" },
{ "user_comments": 2, "active_users": 1, "date": "2019-10-07" }
];
// get max value from data arary
const yAxisMaxValueFor = (...keys) => {
const maxList = keys.map(key => data.reduce(
// find the item containing the max value
(acc, cur) => (cur[key] > acc[key] ? cur : acc)
)[key]
);
return Math.max(...maxList);
};
const { addEventListener, removeEventListener } = window;
class App extends React.Component {
state = {
width: 400,
height: 300,
}
componentDidMount() {
addEventListener('resize', this.resizeListener, { passive: true, capture: false });
}
componentWillUnmount() {
removeEventListener('resize', this.resizeListener, { passive: true, capture: false });
}
resizeListener = () => {
if (!this.chartWrapper) return;
const child = this.chartWrapper.querySelector('div');
child.style.display = 'none';
const {
clientWidth,
clientHeight: height,
} = this.chartWrapper;
const width = clientWidth - 40; // as padding: "0 20px"
this.setState({ width, height });
child.style.display = 'block';
}
refChartWrapper = el => {
this.chartWrapper = el
if (el) this.resizeListener();
}
yAxisValues = Array.from(
{ length: yAxisMaxValueFor('active_users', 'user_comments') },
).map((v, i) => (i + 1));
render() {
const {width, height, yAxisValues} = this.state;
const spec = getSpec(yAxisValues, data.length);
return (
动图演示：
至此，图表已经基本完善。