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How to use ECharts and Java interfaces to implement timeline-based statistical analysis
Abstract: With the popularity of data analysis, timeline-based statistical analysis has become a Powerful tool. This article introduces how to use ECharts and Java interfaces to implement timeline-based statistical analysis, and provides specific code examples.
Keywords: ECharts, Java interface, timeline, statistical analysis
Introduction: With the rapid development of the Internet, a large amount of data is generated and stored in the database. How to obtain valuable information from these data has become an important task. Timeline-based statistical analysis is a powerful data analysis tool. This article will introduce how to use ECharts and Java interfaces to implement timeline-based statistical analysis, and provide specific code examples.
1. Background introduction
ECharts is an open source visualization library based on JavaScript. It provides powerful visual chart functions, allowing developers to easily create various statistical charts, and supports Dynamically update data. The Java interface is a technology used to interact with the database. It can easily obtain data from the database and pass the data to the front-end ECharts library for visual processing.
2. Implementation steps
First you need to create a database and create corresponding tables in the database to store the required statistics The data. The table needs to include time fields and statistical data fields.
In Java code, we need to write an interface to get data from the database and pass the data to the front-end ECharts library for processing . The specific code is as follows:
import java.sql.*; import com.alibaba.fastjson.JSONObject; public class DataAPI { public static String getData() { Connection conn = null; Statement stmt = null; ResultSet rs = null; JSONObject data = new JSONObject(); try { Class.forName("com.mysql.jdbc.Driver"); conn = DriverManager.getConnection("jdbc:mysql://localhost/database", "username", "password"); stmt = conn.createStatement(); rs = stmt.executeQuery("SELECT time, count FROM table"); while (rs.next()) { String time = rs.getString("time"); int count = rs.getInt("count"); data.put(time, count); } } catch (Exception e) { e.printStackTrace(); } finally { try { if (rs != null) { rs.close(); } if (stmt != null) { stmt.close(); } if (conn != null) { conn.close(); } } catch (Exception e) { e.printStackTrace(); } } return data.toJSONString(); } }
In the HTML file, we need to introduce the ECharts library file and request the Java interface to obtain data through Ajax , and then use the ECharts library to generate a timeline statistical chart. The specific code is as follows:
<html> <head> <title>基于时间轴的统计分析</title> <script src="https://cdn.jsdelivr.net/npm/echarts@5.2.2/dist/echarts.min.js"></script> <script src="https://cdn.jsdelivr.net/npm/axios/dist/axios.min.js"></script> </head> <body> <div id="chart" style="width: 600px; height: 400px"></div> <script> axios.get('/getData').then(function(response) { var data = response.data; var chart = echarts.init(document.getElementById('chart')); var option = { xAxis: { type: 'category', data: Object.keys(data) }, yAxis: { type: 'value' }, series: [{ data: Object.values(data), type: 'line' }] }; chart.setOption(option); }); </script> </body> </html>
In order for the front-end page to access the Java interface normally, we need to configure a route to forward the request to Methods of Java interfaces. The specific configuration file is as follows:
<servlet> <servlet-name>DataServlet</servlet-name> <servlet-class>com.example.DataServlet</servlet-class> </servlet> <servlet-mapping> <servlet-name>DataServlet</servlet-name> <url-pattern>/getData</url-pattern> </servlet-mapping>
3. Summary
Through the introduction of this article, we have learned how to use ECharts and Java interfaces to implement timeline-based statistical analysis, and provided specific code example. This method can easily obtain data from the database and generate timeline statistical charts through the ECharts library to facilitate data analysis and display. I hope this article is helpful to you, thank you for reading!
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