一、需求问题

在开发项目中，我们可能会遇到这样的需求。在vue中使用Echarts绘制K线图，进行数据分析。下面是一个简单的K线图绘制，数据是伪造的，虽然不多，但是能够实现大致的K线图效果。

二、需求分析

对于使用Echarts绘制K线图，首先我们需要下载Echarts，可以通过 npm install echarts --save命令下载。在这个文件中引入echarts，创建echarts的挂载实例，在mounted中初始化echarts实例，进行相关的K线图绘制就可以了。

三、需求实现

完整的代码实例如下所示：

<template><div><h1>Echarts绘制k线图</h1><div id="echartContainer" ref="echartContainer" style="width:100%; height:400px"></div></div>
</template><script>
var echarts = require("echarts");
export default {data() {return {//数据模型 time0 open1 close2 min3 max4 vol5 tag6 macd7 dif8 dea9//['2019-10-18',18.56,18.25,18.19,18.56,55.00,0,-0.00,0.08,0.09]data: [["2019-3-16", 18.4, 18.58, 18.33, 18.79, 67.0, 1, 0.04, 0.11, 0.09],["2019-3-19", 18.56, 18.25, 18.19, 18.56, 55.0, 0, -0.0, 0.08, 0.09],["2019-3-20", 18.3, 18.22, 18.05, 18.41, 37.0, 0, 0.01, 0.09, 0.09],["2019-3-21", 18.18, 18.69, 18.02, 18.98, 89.0, 0, 0.03, 0.1, 0.08],["2019-3-22", 18.42, 18.29, 18.22, 18.48, 43.0, 0, -0.06, 0.05, 0.08],["2019-3-23", 18.26, 18.19, 18.08, 18.36, 46.0, 0, -0.1, 0.03, 0.09],["2019-3-26", 18.33, 18.07, 17.98, 18.35, 65.0, 0, -0.15, 0.03, 0.1],["2019-3-27", 18.08, 18.04, 17.88, 18.13, 37.0, 0, -0.19, 0.03, 0.12],["2019-3-28", 17.96, 17.86, 17.82, 17.99, 35.0, 0, -0.24, 0.03, 0.15],["2019-3-29", 17.85, 17.81, 17.8, 17.93, 27.0, 0, -0.24, 0.06, 0.18],["2019-3-30", 17.79, 17.93, 17.78, 18.08, 43.0, 0, -0.22, 0.11, 0.22],["2019-4-02", 17.78, 17.83, 17.78, 18.04, 27.0, 0, -0.2, 0.15, 0.25],["2019-4-03", 17.84, 17.9, 17.84, 18.06, 34.0, 0, -0.12, 0.22, 0.28],["2019-4-04", 17.97, 18.36, 17.85, 18.39, 62.0, 0, -0.0, 0.3, 0.3],["2019-4-05", 18.3, 18.57, 18.18, 19.08, 177.0, 0, 0.07, 0.33, 0.3],["2019-4-06", 18.53, 18.68, 18.3, 18.71, 95.0, 0, 0.12, 0.35, 0.29],["2019-4-09", 18.75, 19.08, 18.75, 19.98, 202.0, 1, 0.16, 0.35, 0.27],["2019-4-10", 18.85, 18.64, 18.56, 18.99, 85.0, 0, 0.09, 0.29, 0.25],["2019-4-11", 18.64, 18.44, 18.31, 18.64, 50.0, 0, 0.06, 0.27, 0.23],["2019-4-12", 18.55, 18.27, 18.17, 18.57, 43.0, 0, 0.05, 0.25, 0.23],["2019-4-13", 18.13, 18.14, 18.09, 18.34, 35.0, 0, 0.05, 0.24, 0.22],["2019-4-16", 18.01, 18.1, 17.93, 18.17, 34.0, 0, 0.07, 0.25, 0.21],["2019-4-17", 18.2, 18.14, 18.08, 18.45, 58.0, 0, 0.11, 0.25, 0.2],["2019-4-18", 18.23, 18.16, 18.0, 18.45, 47.0, 0, 0.13, 0.25, 0.19],["2019-4-19", 18.08, 18.2, 18.05, 18.25, 32.0, 0, 0.15, 0.24, 0.17],["2019-4-20", 18.15, 18.15, 18.11, 18.29, 36.0, 0, 0.13, 0.21, 0.15],["2019-4-23", 18.16, 18.19, 18.12, 18.34, 47.0, 0, 0.11, 0.18, 0.13],["2019-4-24", 18.23, 17.88, 17.7, 18.23, 62.0, 0, 0.03, 0.13, 0.11],["2019-4-25", 17.85, 17.73, 17.56, 17.85, 66.0, 0, -0.03, 0.09, 0.11],["2019-4-26", 17.79, 17.53, 17.5, 17.92, 63.0, 0, -0.1, 0.06, 0.11],["2019-4-27", 17.51, 17.04, 16.9, 17.51, 67.0, 0, -0.16, 0.05, 0.13],["2019-4-30", 17.07, 17.2, 16.98, 17.32, 55.0, 0, -0.12, 0.09, 0.15],["2019-5-01", 17.28, 17.11, 16.91, 17.28, 39.0, 0, -0.09, 0.12, 0.16],["2019-5-02", 17.13, 17.91, 17.05, 17.99, 102.0, 0, -0.01, 0.17, 0.18],["2019-5-03", 17.8, 17.78, 17.61, 17.98, 71.0, 0, -0.09, 0.14, 0.18],["2019-5-04", 17.6, 17.25, 17.13, 17.69, 51.0, 0, -0.18, 0.1, 0.19],["2019-5-07", 17.2, 17.39, 17.15, 17.45, 43.0, 0, -0.19, 0.12, 0.22],["2019-5-08", 17.3, 17.42, 17.18, 17.62, 45.0, 0, -0.23, 0.13, 0.24],["2019-5-09", 17.33, 17.39, 17.32, 17.59, 44.0, 0, -0.29, 0.13, 0.28],["2019-5-10", 17.39, 17.26, 17.21, 17.65, 44.0, 0, -0.37, 0.13, 0.32],["2019-5-11", 17.23, 16.92, 16.66, 17.26, 114.0, 1, -0.44, 0.15, 0.37],["2019-5-14", 16.75, 17.06, 16.5, 17.09, 94.0, 0, -0.44, 0.21, 0.44],["2019-5-15", 17.03, 17.03, 16.9, 17.06, 46.0, 0, -0.44, 0.28, 0.5],["2019-5-16", 17.08, 16.96, 16.87, 17.09, 30.0, 0, -0.4, 0.36, 0.56],["2019-5-17", 17.0, 17.1, 16.95, 17.12, 50.0, 0, -0.3, 0.47, 0.62],["2019-5-18", 17.09, 17.52, 17.04, 18.06, 156.0, 0, -0.14, 0.59, 0.66],["2019-5-21", 17.43, 18.23, 17.35, 18.45, 152.0, 1, 0.02, 0.69, 0.68],["2019-5-22", 18.14, 18.27, 18.06, 18.32, 94.0, 0, 0.08, 0.72, 0.68],["2019-5-23", 18.28, 18.19, 18.17, 18.71, 108.0, 0, 0.13, 0.73, 0.67],["2019-5-24", 18.18, 18.14, 18.01, 18.31, 37.0, 0, 0.19, 0.74, 0.65],["2019-5-25", 18.22, 18.33, 18.2, 18.36, 48.0, 0, 0.26, 0.75, 0.62],["2019-5-28", 18.35, 17.84, 17.8, 18.39, 48.0, 0, 0.27, 0.72, 0.59],["2019-5-29", 17.83, 17.94, 17.71, 17.97, 36.0, 0, 0.36, 0.73, 0.55],["2019-5-30", 17.9, 18.26, 17.55, 18.3, 71.0, 1, 0.43, 0.71, 0.5],["2019-5-31", 18.12, 17.99, 17.91, 18.33, 72.0, 0, 0.4, 0.63, 0.43],["2019-6-04", 17.91, 17.28, 17.16, 17.95, 37.0, 1, 0.34, 0.55, 0.38],["2019-6-05", 17.17, 17.23, 17.0, 17.55, 51.0, 0, 0.37, 0.51, 0.33],["2019-6-06", 17.2, 17.31, 17.06, 17.33, 31.0, 0, 0.37, 0.46, 0.28],["2019-6-07", 17.15, 16.67, 16.51, 17.15, 19.0, 0, 0.3, 0.37, 0.22],["2019-6-08", 16.8, 16.81, 16.61, 17.06, 60.0, 0, 0.29, 0.32, 0.18],["2019-6-11", 16.68, 16.04, 16.0, 16.68, 65.0, 0, 0.2, 0.24, 0.14],["2019-6-12", 16.03, 15.98, 15.88, 16.25, 46.0, 0, 0.2, 0.21, 0.11],["2019-6-13", 16.21, 15.87, 15.78, 16.21, 57.0, 0, 0.2, 0.18, 0.08],["2019-6-14", 15.55, 15.89, 15.52, 15.96, 42.0, 0, 0.2, 0.16, 0.05],["2019-6-15", 15.87, 15.48, 15.45, 15.92, 34.0, 1, 0.17, 0.11, 0.02],["2019-6-18", 15.39, 15.42, 15.36, 15.7, 26.0, 0, 0.21, 0.1, -0.0],["2019-6-19", 15.58, 15.71, 15.35, 15.77, 38.0, 0, 0.25, 0.09, -0.03],["2019-6-20", 15.56, 15.52, 15.24, 15.68, 38.0, 0, 0.23, 0.05, -0.07],["2019-6-21", 15.41, 15.3, 15.28, 15.68, 35.0, 0, 0.21, 0.0, -0.1],["2019-6-22", 15.48, 15.28, 15.13, 15.49, 30.0, 0, 0.21, -0.02, -0.13],["2019-6-25", 15.29, 15.48, 15.2, 15.49, 21.0, 0, 0.2, -0.06, -0.16],["2019-6-26", 15.33, 14.86, 14.78, 15.39, 30.0, 0, 0.12, -0.13, -0.19],["2019-6-27", 14.96, 15.0, 14.84, 15.22, 51.0, 0, 0.13, -0.14, -0.2],["2019-6-28", 14.96, 14.72, 14.62, 15.06, 25.0, 0, 0.1, -0.17, -0.22],["2019-6-29", 14.75, 14.99, 14.62, 15.08, 36.0, 0, 0.13, -0.17, -0.24],["2019-7-01", 14.98, 14.72, 14.48, 15.18, 27.0, 0, 0.1, -0.21, -0.26],["2019-7-02", 14.65, 14.85, 14.65, 14.95, 18.0, 0, 0.11, -0.21, -0.27],["2019-7-03", 14.72, 14.67, 14.55, 14.8, 23.0, 0, 0.1, -0.24, -0.29],["2019-7-04", 14.79, 14.88, 14.69, 14.93, 22.0, 0, 0.13, -0.24, -0.3],["2019-7-05", 14.9, 14.86, 14.78, 14.93, 16.0, 0, 0.12, -0.26, -0.32],["2019-7-15", 14.5, 14.66, 14.47, 14.82, 19.0, 0, 0.11, -0.28, -0.34],["2019-7-16", 14.77, 14.94, 14.72, 15.05, 26.0, 0, 0.14, -0.28, -0.35],["2019-7-17", 14.95, 15.03, 14.88, 15.07, 38.0, 0, 0.12, -0.31, -0.37],["2019-7-18", 14.95, 14.9, 14.87, 15.06, 28.0, 0, 0.07, -0.35, -0.39],["2019-7-19", 14.9, 14.75, 14.68, 14.94, 22.0, 0, 0.03, -0.38, -0.4],["2019-7-22", 14.88, 15.01, 14.79, 15.11, 38.0, 1, 0.01, -0.4, -0.4],["2019-7-23", 15.01, 14.83, 14.72, 15.01, 24.0, 0, -0.09, -0.45, -0.4]]};},mounted() {// 这里实现的是一个比较简单的，可以按照需求将函数移动到methods函数中var data0 = splitData(this.data);// macd计算function splitData(rawData) {var categoryData = [];var values = [];var macds = [];var difs = [];var deas = [];for (var i = 0; i < rawData.length; i++) {categoryData.push(rawData[i].splice(0, 1)[0]);values.push(rawData[i]);macds.push(rawData[i][6]);difs.push(rawData[i][7]);deas.push(rawData[i][8]);}return {categoryData: categoryData,values: values,macds: macds,difs: difs,deas: deas};}// ma均线函数function calculateMA(dayCount) {var result = [];for (var i = 0, len = data0.values.length; i < len; i++) {if (i < dayCount) {result.push("-");continue;}var sum = 0;for (var j = 0; j < dayCount; j++) {sum += data0.values[i - j][1];}result.push(sum / dayCount);}return result;}// k线配置项var option = {tooltip: {trigger: "axis",axisPointer: {type: "cross"}},grid: [{left: "3%",top: "0",height: "75%"},{left: "3%",right: "10%",top: "80%",height: "10%"}],xAxis: [{type: "category",data: data0.categoryData,scale: true,boundaryGap: false,axisLine: {onZero: false,lineStyle: {color: "red"}},splitLine: {show: false},splitNumber: 20},{type: "category",gridIndex: 1,data: data0.categoryData,axisLabel: { show: false }}],yAxis: [{scale: true,splitArea: {show: true},axisLine: {lineStyle: {color: "red"}},position: "right"},{gridIndex: 1,splitNumber: 3,axisLine: { onZero: false },axisTick: { show: false },splitLine: { show: false },axisLabel: { show: true },axisLine: {lineStyle: {color: "red"}},position: "right"}],dataZoom: [{type: "inside",start: 100,end: 80},{show: true,type: "slider",y: "90%",start: 50,end: 100},{show: false,xAxisIndex: [0, 1],type: "slider",start: 20,end: 100}],series: [{name: "555",type: "candlestick",data: data0.values,markPoint: {data: [{name: "XX标点"}]},markLine: {silent: true,data: [{yAxis: 2222}]}},{name: "MA5",type: "line",data: calculateMA(5),smooth: true,lineStyle: {normal: {opacity: 0.5}}},{name: "MA10",type: "line",data: calculateMA(10),smooth: true,lineStyle: {normal: {opacity: 0.5}}},{name: "MA20",type: "line",data: calculateMA(20),smooth: true,lineStyle: {normal: {opacity: 0.5}}},{name: "MA30",type: "line",data: calculateMA(30),smooth: true,lineStyle: {normal: {opacity: 0.5}}},{name: "MACD",type: "bar",xAxisIndex: 1,yAxisIndex: 1,data: data0.macds,itemStyle: {normal: {color: function(params) {var colorList;if (params.data >= 0) {colorList = "#ef232a";} else {colorList = "#14b143";}return colorList;}}}},{name: "DIF",type: "line",xAxisIndex: 1,yAxisIndex: 1,data: data0.difs},{name: "DEA",type: "line",xAxisIndex: 1,yAxisIndex: 1,data: data0.deas}]};// 进行初始化var charts = echarts.init(this.$refs.echartContainer);charts.setOption(option);}
};
</script><style scoped>
</style>