ECharts scatter plot (multidimensional): how to display data relationships and distribution

ECharts Scatter Chart (Multi-dimensional): How to display data relationships and distribution, specific code examples are required

Introduction:
In the field of data visualization, scatter plot A graph is a commonly used chart type that can show the relationship between different dimensions and the distribution of data. As a powerful and flexible visualization library, ECharts provides a wealth of functions and configuration options that can be used to create various types of scatter plots. This article will introduce how to use ECharts to create scatter plots and give specific code examples.

1. Prepare data:
   First, we need to prepare a set of data. This set of data contains multiple dimensions, such as x coordinates, y coordinates, color, size, etc. Suppose we have the following data:

var data = [
   {x: 10, y: 20, color: 'red', size: 5},
   {x: 15, y: 25, color: 'blue', size: 8},
   {x: 20, y: 30, color: 'green', size: 3},
   ...
];

2. Create a chart container:
   In the HTML page, you need to create a div element as a container for the chart:

<div id="chart" style="width: 600px; height: 400px;"></div>

3. Initialize the ECharts instance:
   In the JavaScript code, we need to introduce the ECharts library and create a chart instance:

var chart = echarts.init(document.getElementById('chart'));

4. Configure chart options:
   Next , we need to configure some options of the chart, such as the chart's title, axis, legend, tooltip, etc.:

var option = {
   title: {
       text: '散点图示例'
   },
   xAxis: {},
   yAxis: {},
   series: [{
       type: 'scatter',
       data: data,
       symbolSize: function (data) {
           return data.size; // 设置散点的大小
       },
       itemStyle: {
           color: function (data) {
               return data.color; // 设置散点的颜色
           }
       }
   }]
};

Among them, series is an array, representing a series in the chart, here we use ' scatter' means scatter plot. The data attribute is used to set the data source, the symbolSize attribute is used to set the size of the scatter points, and the itemStyle attribute is used to set the color of the scatter points.

5. Render the chart:
   Finally, we need to pass the configured chart options to the ECharts instance and call the draw method to render the chart:

chart.setOption(option);

Complete The code example is as follows:

var data = [
   {x: 10, y: 20, color: 'red', size: 5},
   {x: 15, y: 25, color: 'blue', size: 8},
   {x: 20, y: 30, color: 'green', size: 3},
   ...
];

var chart = echarts.init(document.getElementById('chart'));

var option = {
   title: {
       text: '散点图示例'
   },
   xAxis: {},
   yAxis: {},
   series: [{
       type: 'scatter',
       data: data,
       symbolSize: function (data) {
           return data.size;
       },
       itemStyle: {
           color: function (data) {
               return data.color;
           }
       }
   }]
};

chart.setOption(option);

With the above code example, we can easily create a simple scatter plot and show the relationship and distribution of data according to the dimensions of the data. At the same time, ECharts also provides richer configuration options and interactive functions for customized chart display effects. I hope this article can help readers better use ECharts to create scatter plots, and bring convenience and benefits to data visualization work.

Conclusion:
This article introduces how to use ECharts to create a scatter chart and gives specific code examples. By using ECharts' rich functionality and configuration options, we can easily demonstrate relationships and data distribution across multiple dimensions. I hope that readers can better use ECharts to realize their data visualization needs through the introduction of this article.

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