This article surveys five notable open‑source 3D globe projects—echarts‑gl, Gio.js, three‑globe, Oclock, and starlink‑viz—detailing their core capabilities, technical stacks, usage examples, and ideal scenarios for data‑driven geographic visualizations.
This article presents a concise overview of ten popular open‑source data visualization tools—including Echarts, D3.js, Grafana, Plotly, Redash, Metabase, Superset, Kibana, AntV, and Pyecharts—highlighting their main features, typical use cases, and visual examples to help readers choose the right solution for their needs.
This article explains the recurring pain points of Java web report development and presents a self‑service visual reporting solution that uses metadata discovery, dynamic SQL generation, and drag‑and‑drop UI to let business users build charts instantly, dramatically reducing development effort.
This article details how JD Finance re‑engineered its complex chart rendering pipeline on the mobile app by integrating Apache ECharts via a custom WebView, introducing a reusable cache, automatic retries, and performance measurements that cut first‑screen rendering time by 200 ms and raised success rates to near 100 %.
This article details JD Finance's iOS app chart rendering challenges, the integration of Apache ECharts via a custom ROMA WebView, cache design, data communication between Native and WebView, and performance gains achieved through automated retries and WebView pooling.
This comprehensive guide walks you through the fundamentals of Apache ECharts, showing how to set up the library, understand core concepts like option, series, axes, and datasets, and apply them in real‑world scenarios such as class performance analysis, subject distribution, correlation studies, and top‑student radar charts, while also covering interactivity, responsiveness, visual mapping, and animation techniques.
This article explains why the ECharts library must be imported with the namespace syntax (import * as echarts) by examining ES Module and CommonJS differences, compatibility strategies, historical reasons, and practical guidelines for choosing the correct import style in frontend development.
This article walks through setting up an ECharts combo chart, then compares html2canvas and snapdom for one‑click screenshot and download, covering installation, core code, common pitfalls, performance benchmarks, and scenario‑based selection advice to help developers choose the right tool for reliable chart export.
Version 6.0 of the open‑source ECharts library introduces a sweeping visual redesign, dynamic theme switching, intelligent scatter jitter, new chord diagrams, axis breakpoints, matrix coordinate systems, label overflow protection, upgraded mark layers, and stronger custom series, making both new and existing projects more powerful and easier to develop.
This article walks through building a single‑page tourism dashboard using Vue 3 and ECharts, covering project setup, technology stack, map rendering with geojson, layered map effects, custom numeric fonts, carousel implementation, and future plans for a Node‑based backend management system.
Explore the latest frontend breakthroughs, from Deno 2.4’s revived bundle command and Apache ECharts 6.0’s visual upgrades to the JS1024 code‑golf challenge, PNG spec overhaul, a comprehensive monorepo guide, practical Web Components tips, tree‑shaking pitfalls, and an in‑depth look at TypeScript declaration merging.
This article demonstrates how to integrate the open‑source ECharts library with a PHP backend to dynamically generate a labeled, legend‑enabled statistical chart, covering resource inclusion, data preparation in JSON, HTML container setup, and JavaScript configuration with init() and setOption() calls.
The Tianji team built a no‑code, component‑based visualization platform using Vue3 and Echarts, where a DSL defines reusable chart cards, tables and other widgets that users drag‑and‑drop onto a 24‑column grid, enabling real‑time, permission‑controlled, personalized dashboards that have already produced over 300 dashboards and 6,000 components for growth operations.
This tutorial explains how to set up and use the open‑source Figma MCP service with the Cursor AI IDE, covering API key creation, server configuration, command‑line startup, JSON setup, and a React ECharts example, plus troubleshooting tips for successful integration.
This tutorial explains how to use a PHP interface together with the ECharts JavaScript library and a MySQL database to fetch data, process it on the server, and render dynamic, interactive bar charts in a web page for effective data visualization.
This tutorial consolidates the fragmented knowledge about using Echarts in UniApp mini‑programs, detailing library choices, installation steps, complete code examples for both Vue2 and Vue3 projects, and common pitfalls with practical solutions.
This tutorial demonstrates how to integrate the ECharts JavaScript library with a PHP backend to generate interactive statistical charts featuring labels and legends, covering resource inclusion, data preparation, HTML container setup, and JavaScript configuration with code examples.
This article demonstrates how to use a PHP interface to retrieve data from a MySQL database and employ the ECharts library to create dynamic visual statistical charts, guiding developers through preparation, data extraction, and chart generation steps, including code examples for a bar chart.
This article describes a personal project that automates the calculation of commuting distances and times between multiple residential areas and two workplace locations by leveraging the AMap API within a Vue‑based frontend, generating Excel reports and visual charts for easy comparison.
This tutorial explains how to integrate the open‑source ECharts library with a PHP backend to produce interactive statistical charts that include custom labels and legends, providing step‑by‑step code examples for data preparation, HTML markup, and JavaScript configuration.
This tutorial explains how to encrypt sensitive data with PHP's OpenSSL functions, decrypt it, and then safely feed the decrypted results to ECharts to render interactive statistical charts, providing complete code examples for each step.
This article describes a Python Flask‑based system that crawls tourism site reviews, processes the data with pandas, stores it in MySQL, and visualizes sentiment analysis, keyword frequencies, and rating trends through interactive ECharts charts on a responsive web dashboard.
This article introduces an AI‑driven Smart Report Assistant Bot that automatically converts uploaded Excel files into recommended charts, allows users to customize reports, and details the underlying workflow—including Excel parsing, LLM‑generated SQL, dynamic table creation, chart rendering with ECharts, and image‑merging plugins.
This guide walks you through creating a dynamic, real‑time data visualization dashboard—covering design mockups, requirement planning, architecture using Echarts for the front‑end and Java for the back‑end, JSON data handling, deployment without installation, configuration steps, code structure, and source acquisition.
This article demonstrates how to integrate ECharts into a Vue3 + TypeScript project, create a reusable useEcharts hook for rendering charts, implement one‑click theme switching, and generate custom chart themes from user‑selected colors using the tvision‑color library and Pinia store management.
This tutorial walks through creating a 3D map in a Vue project using ECharts, covering JSON map import, 2D to 3D conversion, region labeling, default and interactive highlighting, background gradients, realistic materials, 3D bar charts, and lighting effects with complete code examples.
This article explains how to quickly build a data‑driven dashboard featuring a pseudo‑3D map, radar and line charts using layered flat maps, ECharts configuration, interaction handling, and visual enhancements such as click‑highlight and ripple effects.
This article demonstrates how to set up and use ECharts in a Vue 3 project with TypeScript, providing a reusable library, type definitions, a composable hook, and example components to render various chart types efficiently.
This guide walks through creating a dynamic, theme‑switchable big‑screen dashboard using Echarts on the front end and a lightweight Java backend, covering requirements, architecture, configuration, code structure, and how to obtain the source code.
Apache ECharts 5.4.3, the open‑source JavaScript visualization library, introduces new features such as axisPointer triggerEmphasis, Sankey trajectory for emphasis, and numerous bug fixes across components like Sankey, Sunburst, Graph, Label, Axis, Pie, Custom, Legend, Util, API, i18n, and Type handling.
This article presents a complete guide to building a data‑visualization big‑screen dashboard, covering effect screenshots, requirement specifications, overall architecture, development environment setup, JSON library configuration, code structure, startup commands, browser access, and source‑code acquisition.
This tutorial details how to create a dynamic, real-time updating data visualization dashboard using Echarts for the frontend and a Java Web backend, covering requirement analysis, architecture design, environment setup, code structure, deployment commands, and source code acquisition.
This article demonstrates how to create a dynamic, real‑time data visualization dashboard using the Echarts library on the front end and a Java‑based backend, covering requirements analysis, architecture design, environment setup, code structure, deployment, and source‑code acquisition.
This article presents a step‑by‑step technical guide for creating a real‑time, dynamic data‑visualization dashboard using Echarts on the front end and a Java‑based backend, covering design screenshots, requirement analysis, architecture, configuration, code structure, deployment commands, and source‑code acquisition.
This article presents a step‑by‑step guide to building a real‑time data‑visualization dashboard using Echarts on the front end and Java on the back end, covering design mockups, requirement analysis, system architecture, development environment setup, code structure, and deployment instructions.
This guide walks you through creating a dynamic, real‑time data visualization big‑screen dashboard using Echarts on the front end and a Java‑based backend, covering requirements, architecture, configuration, code structure, and deployment steps.
This article provides a step‑by‑step tutorial on creating a dynamic, real‑time data visualization dashboard using the Echarts front‑end library and a Java Web backend, covering requirements, architecture, configuration, code structure, deployment, and source‑code acquisition.
This interview chronicles Wang Zhiwei’s journey from a university student experimenting with GitHub to the CTO of AntV, highlighting how his 100‑line Echarts‑for‑React component launched a thriving open‑source career, shaped Ant Group’s culture, and offers practical advice for developers eager to contribute to open source.
This article provides an in-depth exploration of ZRender, a lightweight 2D graphics rendering engine, and its relationship with ECharts, covering installation, basic usage, drawing shapes, interactive effects, and practical applications.
This article demonstrates how to create a dynamic, real‑time data visualization dashboard using Echarts on the front‑end and a Java Web backend, covering requirements, architecture, configuration, code structure, deployment, and source‑code acquisition, with screenshots and a Maven dependency example.
This article demonstrates how to create a dynamic, real‑time data visualization dashboard using Echarts on the front end and a Java‑based backend, covering requirements, architecture, configuration, code structure, deployment, and source‑code acquisition.
This article introduces the wrn-echarts project, detailing its background, feasibility analysis, architecture, implementation of SVG and Skia rendering modes, touch‑event handling, solved issues, usage steps, performance comparison with react-native-echarts-pro, conclusions, and future plans.
This article explains the motivation, architecture, technology stack, adaptive layout techniques, component development workflow, drag‑and‑drop enhancements, and real‑time state management used to build a low‑code, front‑end‑focused big‑screen data visualization platform.
This article explains why ECharts is a popular choice for large‑screen dashboards, introduces the configuration‑driven mindset, demonstrates graphic and animation techniques, and walks through building a reusable Vue 3 base component with dynamic resizing, theming, and empty‑state handling.
This article presents a step‑by‑step tutorial for creating a dynamic, real‑time data visualization dashboard using Echarts on the front end and a Java Web backend, covering design, deployment, architecture, configuration, code structure, and source acquisition.
This article explains why a data‑analysis platform needs a plugin architecture for custom charts, compares iframe‑based and Web Components approaches, shows how to implement a lightweight ECharts‑based chart plugin, and provides step‑by‑step code samples and technical selection criteria for frontend developers.
This article presents a step‑by‑step tutorial for creating a dynamic, real‑time data visualization dashboard using Echarts on the front end and a Java‑based backend, covering design mockups, requirement analysis, architecture, environment setup, code structure, deployment commands, and source code acquisition.
This guide demonstrates how to create a dynamic, real‑time data visualization dashboard using Echarts for the frontend and a Java‑based backend, covering requirement analysis, architecture design, environment setup, code structure, and deployment instructions.
This article presents a step‑by‑step guide to creating a real‑time data‑visualization dashboard using Echarts on the front end and a Java Web backend, covering requirement analysis, architecture design, environment setup, code structure, deployment, and how to obtain the source code.
This article explains how massive online game user data can be turned into insightful visualizations by distinguishing in‑game and out‑of‑game contexts, focusing on core metrics such as activity, retention, and payment, and recommending suitable chart types and web‑based visualization tools.
This tutorial demonstrates step‑by‑step how to wrap popular H5 chart libraries like AntV/F2 and ECharts inside a Uni‑App component, enabling seamless chart rendering in WeChat mini‑programs using Vue syntax and handling canvas context compatibility.
Apache ECharts 5.3.3 has been released, introducing new stacking strategies for bar charts, tree focus support, boolean selectedMode for visualMap, and a series of bug fixes across line, tree, graph, radar, geo, tooltip, dataZoom, markLine, markArea, axis, graphic, decal, radialGradient, and type definitions.
This article presents a step-by-step guide to building a full-screen dashboard for LED displays, detailing requirement analysis, deployment options, overall architecture, key front‑end HTML/CSS layout, Echarts visualizations, back‑end Java REST API, JSON data handling, and configuration instructions.
This tutorial explains how to build a responsive, theme‑switchable real‑time data visualization dashboard using a Python Flask back‑end and ECharts front‑end, covering requirements, architecture, HTML/CSS grid layout, JavaScript chart logic, JSON data handling, and deployment steps.
The Apache Software Foundation announced new members, highlighting Xianzhe—an Apache ECharts PMC member who helped guide ECharts from Baidu donation through incubation to top‑level status and now serves on the Incubator PMC, supporting other projects and the Beijing local community while embracing her honor and responsibility.
This tutorial walks through setting up a modern Vue 3 development environment using Vite, TypeScript, ESLint, Stylelint, Pinia, Vue‑Router, Naive UI, ECharts, and Axios, covering Node.js installation, project scaffolding, configuration files, code standards, git hooks, and integration steps for each library.
This tutorial introduces pyecharts, a Python wrapper for Echarts, covering installation (including Tsinghua mirror), Python 2 compatibility, and step‑by‑step code examples for creating Bar, Pie, Boxplot, Line, Radar, Scatter, Grid, and Overlap charts with rendering to HTML.
This tutorial introduces pyecharts, the Python wrapper for Baidu's Echarts library, explains how it generates a render.html file, and provides complete code examples for drawing various map visualizations—including basic maps, maps without labels, visual‑mapped maps, world maps, and regional maps—while also showing how to replace the dummy data with your own dataset.
This tutorial explains how to use the pyecharts library—a Python wrapper for Baidu's ECharts—to generate a wide range of interactive visualizations, including bar, line, pie, map, heatmap, scatter, 3D, and combined charts, with complete code examples and rendering instructions for Jupyter notebooks.
This article introduces relationship graph visualization, compares common front‑end chart libraries such as ECharts, D3, and G6, explains why D3 and G6 were chosen for a real‑world case, and discusses performance‑related optimizations and layout improvements for large‑scale graph data.
After integrating Kubernetes into Probius, this guide shows how to pull pod metrics from Prometheus using the query_range API, process them with a Python client, and visualize CPU, memory, bandwidth, and IOPS data in Probius via ECharts, completing a seamless container‑monitoring feature.
This article demonstrates how to use Python's data‑analysis ecosystem (NumPy, pandas, statsmodels, etc.) together with Flask, MySQL, and ECharts to create a web‑based sales forecasting tool that automates data extraction, modeling, prediction, and visualisation.
This article presents a cinema ticketing system built with the SSM framework, MySQL, Redis, Alipay sandbox, LayUI, and Baidu ECharts, highlighting its architecture, features such as payment and seat selection, and providing source code link and screenshots.
This article explores the design and implementation of JD's 11.11 data‑center visualization screen, detailing its storytelling approach, 3D integration, step‑by‑step creation process, and the use of tools like ECharts to turn massive traffic data into an engaging, real‑time dashboard.
Apache ECharts 4.9.0, an open‑source JavaScript charting library incubated by Apache, introduces new features such as polygon graph connections and horizontal funnel orientation, adds tooltip text shadow and brush style options, and resolves numerous bugs across components like toolbox, tooltip, and bar charts.
This tutorial demonstrates how to generate simulated web access logs in Python, schedule them with Crontab, collect them in real time using Flume, forward them to Kafka, process the streams with Spark Streaming, store results in HBase, and visualize the data via a Spring Boot application with ECharts.
This article introduces the Python library pyecharts, explains its background from ECharts, shows how to install it, and provides step‑by‑step examples—including creating bar and pie charts from Chengdu statistical data—while detailing the underlying code and rendering process for effective data visualization.
This tutorial demonstrates how to add Baidu's ECharts JavaScript visualization library to a Spring Boot backend, covering project setup, Maven dependencies, controller creation, Thymeleaf template configuration, and rendering a line chart in the browser.
This comprehensive guide walks you through installing pyecharts, creating basic charts such as bar, line, scatter, boxplot, word cloud, and geographic maps, customizing themes, axes, data zoom, and styles, and mastering chart combinations like Grid, Overlap, Page, and Timeline to build sophisticated visualizations.
This guide walks you through installing ECharts, creating a basic chart in a web page, and using the Python ECharts API, providing step‑by‑step instructions, code snippets, and visual examples for effective data visualization.
This tutorial walks through using the Zabbix API with the pyzabbix Python library to retrieve monitoring data, then visualizes it with ECharts, showing step‑by‑step how to create personalized monitoring pages for better operational insight.
This guide walks you through using Python to crawl Qunar’s tourist spot pages, retrieve location and sales data, enrich it with Baidu Map’s geocoding API, and then create interactive heatmaps and ranking charts with ECharts, while storing results in JSON and Excel files for further analysis.
This article introduces Baidu's open‑source ECharts library, walks through installing the JavaScript package, embedding it in a web page, and demonstrates using the Python ECharts API to create interactive charts, while highlighting key setup notes and resources.
