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土豆我是马铃薯 数据达人Lv4
发表于2020-5-26 10:15
楼主
本帖最后由 土豆我是马铃薯 于 2020-5-26 10:18 编辑
在ABI通用统计图组件中暂时没有象形柱状图，则需要我们自己在自定义组件中引入echarts。效果如下：
实现方法：
一、在ABI资源管理器中上传echarts资源包echarts.min.js，如下路径(其他路径也行)
二、拖入echarts自定义组件
三、双击自定义组件，填写编译好得代码
代码如下：复制代码
echarts.min.zip
(239.78 KB, 下载次数: )
在ABI通用统计图组件中暂时没有象形柱状图，则需要我们自己在自定义组件中引入echarts。效果如下：
实现方法：
一、在ABI资源管理器中上传echarts资源包echarts.min.js，如下路径(其他路径也行)
二、拖入echarts自定义组件
三、双击自定义组件，填写编译好得代码
代码如下：
- EUI.include("vfs/root/products/ebi/echarts.min.js");
- //------------------------------------引用请注明出处
- var spirit = 'image://data:image/png;base64,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';
- var maxData =eval('<#=grid1.b3#>');
- var maxData1 =eval('<#=grid1.c3#>');
- var myData =eval('<#=grid1.a2$#>');
- var databeast =eval('<#=grid1.b2$.select(true,@.txt)#>');
- var databeast1 =eval('<#=grid1.c2$.select(true,@.txt)#>')
- //var databeauty = [280, 128, 255, 254, 313, 143, 360, 343, 338, 163, 333, 317, 263, 302, 372, 163]
- option = {
- // tooltip: {
- // trigger: 'axis',
- // axisPointer: {
- // type: 'cross',
- // crossStyle: {
- // color: '#999'
- // }
- // }
- // },
- tooltip : {
- trigger: 'axis',
- formatter(params) {
- console.log(JSON.stringify(params))
- return `
- 频繁停电数：${params[0].data}
- 频繁停电次数：${params[2].data}
- `;
- }
- },
- xAxis: {
- type: 'category',
- inverse: true,
- axisLine: {
- show: false
- },
- axisTick: {
- show: false
- },
- axisLabel: {
- interval: 0, //横轴信息全部显示
- show: true,
- margin: 8,
- textStyle: {
- color: '#868686',
- fontSize: 14,
- },
- },
- data: myData,
- },
- yAxis: [{
- name:'单位：万元',
- nameTextStyle:{
- color:'#868686',
- },
- color:'#868686',
- type: 'value',
- axisLine: {
- show: false,
- },
- //y轴分割线
- axisTick: {
- show: false,
- },
- position: 'center',
- //y轴标签
- axisLabel: {
- show: true,
- textStyle:{
- color:'#868686',
- fontsize:14,
- },
- formatter: function (value, index) {
- return value.toFixed(0);
- }
- },
- splitLine: {
- show: false,
- lineStyle: {
- color: '#3E3E3E',
- width: 1,
- type: 'dashed',
- },
- },
- splitNumber: 6,
- max:maxData,
- interval: maxData/6
- },{
- name:'单位：万元',
- nameTextStyle:{
- color:'#868686',
- },
- type: 'value',
- axisLine: {
- show: false,
- },
- //y轴分割线
- axisTick: {
- show: false,
- },
- position: 'center',
- //y轴标签
- axisLabel: {
- show: true,
- textStyle:{
- color:'#868686',
- fontsize:14,
- },
- formatter: function (value, index) {
- return value.toFixed(0);
- }
- },
- splitLine: {
- show: true,
- lineStyle: {
- color: '#3E3E3E',
- width: 1,
- type: 'dashed',
- },
- },
- max:maxData1,
- splitNumber: 6,
- interval: maxData1/6
- }
- ],
- series: [{
- type: 'pictorialBar',
- symbol: 'rect',
- label: {
- emphasis: {
- show: true,
- position: 'center',
- offset: [0, 0],
- textStyle: {
- color: '#000',
- fontSize: 14,
- },
- },
- },
- itemStyle: {
- normal: {
- color: '#61FFD8',
- backgroundColor: 'rgba(2,191,138,1)',
- },
- emphasis: {
- color: '#08C7AE',
- },
- },
- symbolRepeat: 'fixed',
- symbolClip: true,
- symbolSize: [20, 5],
- symbolBoundingData: maxData,
- animationEasing: 'elasticOut',
- data: databeast,
- animationDelay: function(dataIndex, params) {
- return params.index * 30;
- }
- },
- {
- // full data
- type: 'pictorialBar',
- yAxisIndex: 0,
- itemStyle: {
- normal: {
- color: 'rgba(82,110,63,0.2)'
- }
- },
- name: '模拟数据1',
- label: {
- normal: {
- show: true,
- formatter: function(params) {
- return (params.value);
- },
- position: ['20%', '0%'],
- offset: [10, -20],
- textStyle: {
- color: '#fff',
- fontSize: 0
- }
- }
- },
- animationDuration: 0,
- symbolRepeat: 'fixed',
- symbolMargin: '5%',
- symbol: 'rect',
- symbolSize: [20, 5],
- symbolBoundingData: maxData,
- data: databeast,
- z: 99999,
- animationEasing: 'elasticOut',
- animationDelay: function(dataIndex, params) {
- return params.index * 30;
- }
- },
- {
- name: '模拟数据',
- type: 'line',
- yAxisIndex: 1,
- smooth: true,
- symbol: 'circle',
- symbolSize: 5,
- sampling: 'average',
- symbolBoundingData: maxData1,
- itemStyle: {
- color: '#FFC002'
- },
- stack: 'a',
- areaStyle: {
- color: new echarts.graphic.LinearGradient(0, 0, 0, 1, [{
- offset: 0,
- color: 'rgba(255,192,2,0.32)'
- }, {
- offset: 1,
- color: 'rgba(3,16,23,-0.01)'
- }])
- },
- data: databeast1
- }
- ],
- };
- return option;
echarts.min.zip
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