echarts word cloud is an extension of echarts https://echarts.apache.org/zh/download-extension.html 1. Install dependencies npm install echarts npm install echarts-wordcloud 2. Import main.js import echarts from 'echarts'; Vue.prototype.$echarts = echarts 3. Introduce extensions in the components used <script> import "echarts-wordcloud/dist/echarts-wordcloud"; import "echarts-wordcloud/dist/echarts-wordcloud.min"; </script> 4. Configuration <template> <div class="result"> <el-tabs type="border-card" v-model="name"> <el-tab-pane label="Accumulated confirmed cases in each province" name="0"> <div ref="chart1" style="width: 800px;height:600px;"></div> </el-tab-pane> <el-tab-pane label="Confirmed cases in each province" name="1"> <div ref="chart2" style="width: 800px;height:600px;" class="charts-two"></div> </el-tab-pane> <el-tab-pane label="Accumulated confirmed cases in each city" name="2"> <div ref="chart3" style="width: 800px;height:600px;"></div> </el-tab-pane> <el-tab-pane label="Current confirmed cases in each city" name="3"> <div ref="chart4" style="width: 800px;height:600px;"></div> </el-tab-pane> </el-tabs> </div> </template> // Word cloud chart <script> import * as echarts from "echarts"; import "echarts-wordcloud/dist/echarts-wordcloud"; import "echarts-wordcloud/dist/echarts-wordcloud.min"; export default { name: "VisitShow", data() { return { userVisitNum: [], date: [], goodVisitNum: [], goodsName: [], name: "0", }; }, mounted() { this.showEeharts(); }, methods: { showEeharts() { var chart1 = echarts.init(this.$refs.chart1); var chart2 = echarts.init(this.$refs.chart2); var chart3 = echarts.init(this.$refs.chart3); var chart4 = echarts.init(this.$refs.chart4); var data1 = [ {'name': 'Hong Kong', 'value': 11801}, {'name': 'Taiwan', 'value': 1178}, {'name': 'Shanghai', 'value': 2006}, {'name': 'Guangdong', 'value': 2365}, {'name': 'Yunnan', 'value': 347}, {'name': 'Sichuan', 'value': 992}, {'name': 'Fujian', 'value': 595}, {'name': 'Zhejiang', 'value': 1345}, {'name': 'Hainan', 'value': 188}, {'name': 'Jiangsu', 'value': 720}, {'name': 'Tianjin', 'value': 387}, {'name': 'Shanxi', 'value': 251}, {'name': 'Guangxi', 'value': 275}, {'name': 'Shaanxi', 'value': 592}, {'name': 'Hubei', 'value': 38158}, {'name': 'Chongqing', 'value': 597}, {'name': 'Inner Mongolia', 'value': 382}, {'name': 'Hunan', 'value': 1045}, {'name': 'Shandong', 'value': 879}, {'name': 'Beijing', 'value': 1057}, {'name': 'Henan', 'value': 1312}, {'name': 'Gansu', 'value': 193}, {'name': 'Tibet', 'value': 1}, {'name': 'Jilin', 'value': 573}, {'name': 'Hebei', 'value': 1317}, {'name': 'Qinghai', 'value': 18}, {'name': 'Macao', 'value': 49}, {'name': 'Xinjiang', 'value': 980}, {'name': 'Liaoning', 'value': 408}, {'name': 'Anhui', 'value': 994}, {'name': 'Heilongjiang', 'value': 1610}, {'name': 'Guizhou', 'value': 147}, {'name': 'Jiangxi', 'value': 937}, {'name': 'Ningxia', 'value': 75} ] var data2 = [ {'name': 'Hong Kong', 'value': 118}, {'name': 'Taiwan', 'value': 89}, {'name': 'Shanghai', 'value': 56}, {'name': 'Guangdong', 'value': 51}, {'name': 'Yunnan', 'value': 46}, {'name': 'Sichuan', 'value': 30}, {'name': 'Fujian', 'value': 25}, {'name': 'Zhejiang', 'value': 22}, {'name': 'Hainan', 'value': 17}, {'name': 'Jiangsu', 'value': 8}, {'name': 'Tianjin', 'value': 7}, {'name': 'Shanxi', 'value': 7}, {'name': 'Guangxi', 'value': 7}, {'name': 'Shaanxi', 'value': 6}, {'name': 'Hubei', 'value': 6}, {'name': 'Chongqing', 'value': 6}, {'name': 'Inner Mongolia', 'value': 4}, {'name': 'Hunan', 'value': 4}, {'name': 'Shandong', 'value': 3}, {'name': 'Beijing', 'value': 2}, {'name': 'Henan', 'value': 1}, {'name': 'Gansu', 'value': 1}, {'name': 'Tibet', 'value': 0}, {'name': 'Jilin', 'value': 0}, {'name': 'Hebei', 'value': 0}, {'name': 'Qinghai', 'value': 0}, {'name': 'Macao', 'value': 0}, {'name': 'Xinjiang', 'value': 10}, {'name': 'Liaoning', 'value': 0}, {'name': 'Anhui', 'value': 0}, {'name': 'Heilongjiang', 'value': 0}, {'name': 'Guizhou', 'value': 0}, {'name': 'Jiangxi', 'value': 0}, {'name': 'Ningxia', 'value': 0} ] var data3 = [ {'name': 'Hong Kong', 'value': 11801}, {'name': 'Taiwan', 'value': 1178}, {'name': 'Shanghai', 'value': 2006}, {'name': 'Guangdong', 'value': 2365}, {'name': 'Yunnan', 'value': 347}, {'name': 'Sichuan', 'value': 992}, {'name': 'Fujian', 'value': 595}, {'name': 'Zhejiang', 'value': 1345}, {'name': 'Hainan', 'value': 188}, {'name': 'Jiangsu', 'value': 720}, {'name': 'Tianjin', 'value': 387}, {'name': 'Shanxi', 'value': 251}, {'name': 'Guangxi', 'value': 275}, {'name': 'Shaanxi', 'value': 592}, {'name': 'Hubei', 'value': 38158}, {'name': 'Chongqing', 'value': 597}, {'name': 'Inner Mongolia', 'value': 382}, {'name': 'Hunan', 'value': 1045}, {'name': 'Shandong', 'value': 879}, {'name': 'Beijing', 'value': 1057}, {'name': 'Henan', 'value': 1312}, {'name': 'Gansu', 'value': 193}, {'name': 'Tibet', 'value': 1}, {'name': 'Jilin', 'value': 573}, {'name': 'Hebei', 'value': 1317}, {'name': 'Qinghai', 'value': 18}, {'name': 'Macao', 'value': 49}, {'name': 'Xinjiang', 'value': 980}, {'name': 'Liaoning', 'value': 408}, {'name': 'Anhui', 'value': 994}, {'name': 'Heilongjiang', 'value': 1610}, {'name': 'Guizhou', 'value': 147}, {'name': 'Jiangxi', 'value': 937}, {'name': 'Ningxia', 'value': 75} ] var data4 = [ {'name': 'Hong Kong', 'value': 118}, {'name': 'Taiwan', 'value': 89}, {'name': 'Shanghai', 'value': 56}, {'name': 'Guangdong', 'value': 51}, {'name': 'Yunnan', 'value': 46}, {'name': 'Sichuan', 'value': 30}, {'name': 'Fujian', 'value': 25}, {'name': 'Zhejiang', 'value': 22}, {'name': 'Hainan', 'value': 17}, {'name': 'Jiangsu', 'value': 8}, {'name': 'Tianjin', 'value': 7}, {'name': 'Shanxi', 'value': 7}, {'name': 'Guangxi', 'value': 7}, {'name': 'Shaanxi', 'value': 6}, {'name': 'Hubei', 'value': 6}, {'name': 'Chongqing', 'value': 6}, {'name': 'Inner Mongolia', 'value': 4}, {'name': 'Hunan', 'value': 4}, {'name': 'Shandong', 'value': 3}, {'name': 'Beijing', 'value': 2}, {'name': 'Henan', 'value': 1}, {'name': 'Gansu', 'value': 1}, {'name': 'Tibet', 'value': 0}, {'name': 'Jilin', 'value': 0}, {'name': 'Hebei', 'value': 0}, {'name': 'Qinghai', 'value': 0}, {'name': 'Macao', 'value': 0}, {'name': 'Xinjiang', 'value': 10}, {'name': 'Liaoning', 'value': 0}, {'name': 'Anhui', 'value': 0}, {'name': 'Heilongjiang', 'value': 0}, {'name': 'Guizhou', 'value': 0}, {'name': 'Jiangxi', 'value': 0}, {'name': 'Ningxia', 'value': 0} ] var chart1Option = { title: text: 'Accumulated confirmed cases in each province - word cloud', //Title x: 'center', textStyle: { fontSize: 23 } }, backgroundColor: '#fff', //F7F7F7 tooltip: { show: true }, series: [{ name: 'Accumulated confirmed cases in each province', //Data prompt window title type: 'wordCloud', sizeRange: [12, 64], //Canvas range. If the setting is too large, there will be fewer words (overflowing the screen) rotationRange: [-45, 90], //Data flip range //shape: 'circle', textPadding: 0, autoSize: { enable: true, minSize: 6 }, textStyle: { normal: { color: function() { return 'rgb(' + [ Math.round(Math.random() * 160), Math.round(Math.random() * 160), Math.round(Math.random() * 160) ].join(',') + ')'; } }, emphasis: shadowBlur: 10, shadowColor: '#333' } }, data: data1, }] }; var chart2Option = { title: text: 'Confirmed cases in each province - word cloud', //Title x: 'center', textStyle: { fontSize: 23 } }, backgroundColor: '#fff', tooltip: { show: true }, series: [{ name: 'Confirmed cases in each province', //Data prompt window title type: 'wordCloud', sizeRange: [12, 64], //Canvas range. If the setting is too large, there will be fewer words (overflowing the screen) rotationRange: [-45, 90], //Data flip range //shape: 'circle', textPadding: 0, autoSize: { enable: true, minSize: 6 }, textStyle: { normal: { color: function() { return 'rgb(' + [ Math.round(Math.random() * 160), Math.round(Math.random() * 160), Math.round(Math.random() * 160) ].join(',') + ')'; } }, emphasis: shadowBlur: 10, shadowColor: '#333' } }, data: data2, }] }; var chart3Option = { title: text: 'Accumulated confirmed cases in each city - word cloud', //Title x: 'center', textStyle: { fontSize: 23 } }, backgroundColor: '#fff', tooltip: { show: true }, series: [{ name: 'Accumulated confirmed cases in each city', //Data prompt window title type: 'wordCloud', sizeRange: [12, 64], //Canvas range. If the setting is too large, there will be fewer words (overflowing the screen) rotationRange: [-45, 90], //Data flip range //shape: 'circle', textPadding: 0, autoSize: { enable: true, minSize: 6 }, textStyle: { normal: { color: function() { console.log('rgb(' + [ Math.round(Math.random() * 160), Math.round(Math.random() * 160), Math.round(Math.random() * 160) ].join(',') + ')') return 'rgb(' + [ Math.round(Math.random() * 160), Math.round(Math.random() * 160), Math.round(Math.random() * 160) ].join(',') + ')'; } }, emphasis: shadowBlur: 10, shadowColor: '#333' } }, data: data3, }] }; var chart4Option = { title: text: 'Current confirmed cases in each city - word cloud', //Title x: 'center', textStyle: { fontSize: 23 } }, backgroundColor: '#fff', tooltip: { show: true }, series: [{ name: 'Confirmed cases in each city', //Data prompt window title type: 'wordCloud', sizeRange: [12, 64], //Canvas range. If the setting is too large, there will be fewer words (overflowing the screen) rotationRange: [-45, 90], //Data flip range //shape: 'circle', textPadding: 0, autoSize: { enable: true, minSize: 6 }, textStyle: { normal: { color: function() { console.log('rgb(' + [ Math.round(Math.random() * 160), Math.round(Math.random() * 160), Math.round(Math.random() * 160) ].join(',') + ')') return 'rgb(' + [ Math.round(Math.random() * 160), Math.round(Math.random() * 160), Math.round(Math.random() * 160) ].join(',') + ')'; } }, emphasis: shadowBlur: 10, shadowColor: '#333' } }, data: data4, }] }; chart1.setOption(chart1Option); chart2.setOption(chart2Option); chart3.setOption(chart3Option); chart4.setOption(chart4Option); }, }, }; </script> <style lang="less"> </style> 5. Finished drawing Summarize This is the end of this article about vue using echarts word cloud chart. 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