This tutorial explains how to use PHP together with the Baidu Map API to prepare data, create a HeatMap instance, add weighted points, generate the heatmap image, and display it on a web page, providing complete code examples for each step.
This technical article details JD Retail’s 2023 data platform advancements, covering data‑asset certification and governance, a metric middle‑platform for unified indicator management, sophisticated visualization components, low‑code orchestration, and large‑model AI applications that together improve data retrieval efficiency, reduce storage‑compute costs, and support rapid business decision‑making.
This article introduces Python decorators, explains their syntax, and provides ten practical examples—including timing, caching, input validation, logging, error suppression, output validation, retry logic, visualization, debugging, and deprecation—complete with code snippets and usage guidance for data‑science and general development tasks.
iQIYI's Magic Mirror platform, evolving from 1.0 to 3.0, addresses the growing data analysis demands of the internet industry by empowering self‑service analytics, introducing multi‑stage architectures, advanced computation engines, customizable SQL, and visual dashboards, thereby improving efficiency, scalability, and data security for business users.
Gaode solved the WebGL‑context limit in AMap by rendering all visual layers on a single canvas with a shared context, disabling autoClear, preserving depth ordering, and using per‑layer EffectComposers merged via a final composer, enabling multiple scenes and post‑processing without exceeding browser limits.
This article explains how to monitor, interpret, and optimize Java Garbage Collection by using JDK flags, IDE configurations, and the gceasy.io visualizer, providing step‑by‑step guidance, sample logs, and performance metrics for effective JVM tuning.
This tutorial demonstrates how to use Python libraries such as itchat, jieba, matplotlib, snownlp, and Tencent Youtu SDK to collect WeChat friend information and perform data analysis on gender distribution, avatar characteristics, signature sentiment, and geographic location, presenting the results with charts and word clouds.
This article walks through a common Matplotlib title garbling issue caused by encoding settings, explains why the 'encoding' argument triggers an AttributeError, and provides a concise code fix using font configuration to display Chinese characters correctly.
This article introduces ten practical Python decorators—including @timer, @memoize, @validate_input, @log_results, @suppress_errors, @validate_output, @retry, @visualize_results, @debug, and @deprecated—explaining their purpose, showing full code implementations, and demonstrating how they can improve performance, reliability, and maintainability of data‑science and general Python projects.
This tutorial demonstrates how to preprocess a Chinese lyrics JSON dataset, extract Jay Chou's songs using Python, perform word segmentation with Jieba, compute word frequencies, and create visualizations such as word clouds both programmatically and with online tools.
This article introduces four Python packages—Pivottablejs, PyGWalker, Qgrid, and Itables—that transform Pandas DataFrames into interactive tables within Jupyter notebooks, providing code examples, visual demonstrations, and guidance on when to choose each tool for data analysis and visualization.
This article details the evolution of Ctrip's flight IVR system from a simple Chinese‑only version to a multilingual, fully visualized low‑code platform, describing its architecture, core components such as data definition, rule and script engines, version management, and the underlying Node.js and React technologies.
This guide introduces VTable, an open‑source high‑performance table component built on VRender, covering installation via npm or CDN, basic usage, table types, cell rendering options, interaction features, theming, and performance characteristics for modern web applications.
This article presents a detailed, end‑to‑end case study of how Yanhuang Data leveraged the Honghu data‑analysis platform to build a complete Nginx operations‑management solution, covering data ingestion, parsing, modeling, visualization, alerting, third‑party integration, and best‑practice recommendations.
Explore how various mathematical equations—from parametric and polar forms to implicit and animated functions—can be used to generate beautiful heart-shaped graphics, illustrating the romantic symbolism of love through visualized curves and dynamic patterns.
This article introduces six free online diagramming tools—Excalidraw, Zen Flowchart, Visual Paradigm Online, draw.io, Liuchengtu, and ProcessOn—detailing their key features, collaboration capabilities, and how they help engineers quickly create flowcharts, mind maps, UML, and other visual documents.
This article details how JDV, JD.com’s internal visual dashboard platform, tackled the massive data‑intensive 618 promotion by implementing real‑time updates, cross‑midnight count stops, request‑state control, heartbeat monitoring, proxy data sources, and a suite of developer tools to ensure stability, performance, and rapid feature delivery.
This guide introduces six free, web‑based diagramming tools—including Excalidraw, Zen Flowchart, Visual Paradigm Online, draw.io, Liuchengtu, and ProcessOn—highlighting their key features, collaboration capabilities, and URLs so engineers can quickly choose the right visual solution for their projects.
This article explains VisActor's animation system, detailing animation definition, trigger mechanisms, basic units like timeline and timeslice, effect configuration, global morphing via Bezier curves, and demonstrates one-to-one, one-to-many, and many-to-one shape transformations with code examples and demos.
This article explains the importance of architecture visualization for clear communication, compares wireframe, UML, and sketch approaches, and details how the C4 model’s layered abstractions—system, container, component, and code—provide a low‑cognitive‑load, consistent way to document software systems.
This article outlines a clear framework for writing data analysis reports—including hierarchical structure, concise conclusions, business‑oriented recommendations, reliable data sourcing, and best‑practice chart design—while highlighting common statistical pitfalls and tips for improving readability and impact.
This article summarizes the most commonly used architecture diagram types, provides template examples, and outlines their characteristics, typical use cases, visual appeal, and complexity to help developers quickly create diagrams that match business requirements.
This guide compiles the most commonly used architecture diagram types, explains their key characteristics, ideal use cases, visual appeal, and complexity, and offers ready‑to‑use templates so developers can swiftly produce clear, business‑aligned diagrams.
This article curates a series of frontend engineering insights, covering request‑optimization strategies, an introduction to micro‑frontends with qiankun, building a custom animated chart as an alternative to ECharts, quick Pixi.js basics, the new JavaScript Import Maps feature, and a brief overview of the Cloud Academy frontend team.
This article explains the four primary browser rendering approaches—DOM (HTML+CSS), SVG, Canvas, and WebGL/WebGPU—detailing their principles, advantages, limitations, and practical examples to help developers understand the underlying mechanics of web‑based visualizations.
This article introduces several common probability distributions—including uniform, normal, lognormal, Poisson, exponential, binomial, Student's t, and chi‑squared—explains their properties, and provides Python code using NumPy, SciPy, and Matplotlib to visualize each distribution.
This article describes a practical approach to automatically extract and visualize business system knowledge from code by abstracting workflow control logic into a generalized design pattern using the FSM‑X state‑machine framework, discussing its background, methodology, implementation details, and current limitations.
This tutorial demonstrates how to perform A/B testing on two marketing campaigns using Python, covering data loading, cleaning, merging, and visual analysis of key metrics such as impressions, spend, clicks, searches, content views, add‑to‑cart actions, and purchases to identify the most effective strategy.
This article introduces the Python Statsmodels library, explains its key features such as linear regression, GLM, time‑series and robust methods, shows how to install it, load data with pandas, perform descriptive statistics, visualizations, hypothesis testing, and simple and multiple linear regression examples.
This article introduces several free, easy‑to‑use diagramming tools—including Excalidraw, Zen Flowchart, Visual Paradigm Online, draw.io, Liuchengtu, and ProcessOn—highlighting their key features, collaboration capabilities, and where to access them.
This article explains the distinction between code coverage and test coverage, outlines testing strategies across functional, code, and architectural layers, offers practical steps and visualisation techniques, and highlights how AI can enhance both kinds of coverage in modern software testing.
This article analyzes how 33% of data‑center defects stem from big‑data scheduling errors and proposes an automated testing system that monitors data metric integrity, accuracy, and timeliness through interface automation, visual dashboards, alert bots, and a custom ORM framework to dramatically improve ROI.
This guide introduces the open‑source Nexttrace tool, explains how to install it on Linux and macOS, and demonstrates its core commands for ICMP, TCP, and UDP traceroutes, as well as advanced options like fast‑trace, interface selection, and map visualisation.
Discover seven powerful, lightweight online diagramming tools—including Zen Flowchart, Excalidraw, draw.io, xGraph, ProcessOn, Liuchengtu, and Nutstore Drawing—that require no installation, support real‑time collaboration, and cover flowcharts, mind maps, network topologies, and more.
This guide introduces NextTrace, a lightweight open‑source Go traceroute utility, explains how to install it on Linux, macOS and via GHPROXY, details its extensive command‑line options, and demonstrates advanced features such as TCP/UDP tracing, TTL control, parallel requests, map and table outputs.
This article details the user‑driven requirements, problem analysis, design choices, and technical implementation of a high‑performance, scalable data lineage visualization built with a React‑Canvas hybrid architecture to support tens of thousands of tables in a big‑data environment.
This article demonstrates how to compare the distribution of a variable across control and treatment groups using Python, covering data generation, visual techniques such as boxplots, histograms, KDE, CDF, QQ and ridgeline plots, and a suite of statistical tests including t‑test, SMD, Mann‑Whitney, permutation, chi‑square, Kolmogorov‑Smirnov and ANOVA for both two‑group and multi‑group scenarios.
This tutorial demonstrates how to use Python libraries such as itchat, jieba, matplotlib, SnowNLP, and Tencent Youtu SDK to collect WeChat friend information and perform data analysis on gender distribution, avatar characteristics, signature text (including word‑cloud and sentiment analysis), and geographic location, presenting the results with visual charts and maps.
A business capability heatmap is a visual two‑dimensional chart that maps capabilities against evaluation parameters such as strategic importance, maturity, and resource adequacy, helping architects and managers assess, compare, and communicate capability status for purposes like vendor selection, merger analysis, and impact prioritization.
This article chronicles Yǐngyǐng’s evolution from a curious student choosing computer science to a key contributor of AntV S2, highlighting her perseverance, open‑source breakthroughs, work‑life balance strategies, and the lessons she learned while shaping cross‑tab visualizations at Ant Group.
The article reviews essential Python data‑preprocessing and statistical‑analysis tools—including missing‑value imputation, outlier trimming, scaling, binning, knee‑point detection, correlation, chi‑square testing, linear regression, Wilson scoring, PCA weighting, text tokenization and sentiment analysis, plus visualization with matplotlib/seaborn and big‑data access via pyodps.
This article walks through a Python visualization issue raised in a community chat, shows the problematic code and error screenshots, explains the root cause identified by an expert, and provides the corrected implementation so readers can resolve similar problems themselves.
This comprehensive overview introduces Apache Superset 2.0, covering its history, core features such as SQLLab, extensive visualizations, data‑exploration capabilities, dashboard creation, native filters, custom plugins, feature flags, and practical demos, while also providing tips, Q&A, and community resources for developers and data engineers.
This tutorial explains how to prepare advertising click data, train a decision‑tree classifier, and generate clear visualizations using scikit‑learn and dtreeviz, while also showing how to inspect individual prediction paths and feature importance.
An enterprise architecture framework diagram visualizes the various architecture layers—governance, business, information, technology, security, and more—showing which parts are identified, managed, and owned, while illustrating current, future, and envisioned states to support reporting and decision‑making.
This article introduces AJ-Report, an open‑source drag‑and‑drop visual design tool built with Spring Boot and Vue, walks through its technology stack, shows how to clone the repository, set up backend and frontend environments, and demonstrates creating dashboards with multiple data sources.
This article explains how the Wukong low‑code visual platform implements component drag‑and‑drop, covering material‑to‑canvas dragging, intra‑canvas movement, resizing via eight handles, alignment guide generation, performance optimizations using CSS transforms, and component encapsulation with Vue 3.
This guide explains why diagrams are essential for technical articles, introduces draw.io as a free, GitHub‑backed tool, walks through its interface, basic shapes, advanced combinations, and also recommends complementary tools like XMind and carbon.now.sh for mind‑maps and code screenshots.
This article details the four‑year development of SpriteJS, a high‑performance, cross‑platform graphics system that supports WebGL and Canvas2D rendering, DOM‑like APIs, responsive design, WebWorker integration, and extensive performance optimizations for visualisation and game applications.
This article introduces a highly recommended open‑source Nginx visualization project, outlines its core features such as configuration management and performance monitoring, provides step‑by‑step installation and deployment instructions for Linux, and shares the source code location along with remaining challenges.
This article examines the evolution of a monitoring platform, identifies issues such as alert overload and business‑monitoring separation, and presents a Grafana‑based solution that combines Diagram or FlowCharting plugins to visualize metrics alongside business workflows for faster fault isolation.
This article introduces the open‑source Nginx‑GUI tool, explains its configuration‑management and performance‑monitoring features, and provides a step‑by‑step tutorial—including download, file edits, Linux‑specific renaming, and server deployment—complete with code snippets and screenshots for users.
This article details Xiaomi's multi‑year journey in building a group‑wide Business Intelligence platform, covering its historical evolution, technical challenges in performance, modeling, visualization and permissions, the current four‑layer architecture, and future plans to make the platform more business‑centric and simpler.
This article explains how QA engineers can identify inefficiencies in their daily workflows, turn those observations into concrete tool requirements, and apply visualisation, automation, and process‑optimisation techniques—illustrated with game‑testing examples—to dramatically improve efficiency and reduce errors.
This article examines the evolution of a monitoring platform, identifies key challenges such as alarm overload and fragmented data, and presents a solution that combines Grafana with Diagram and FlowCharting plugins to create business‑process‑oriented, data‑driven visualizations for faster issue resolution.
This article introduces the GoPUP Python library, explains how to install it, demonstrates retrieving Weibo index data with code examples, shows how to visualize the results using Pandas, Jupyter and Matplotlib, and lists the wide range of public data APIs the library supports.
This article compares a range of Redis visualization solutions—including desktop clients, a web‑based platform, and an IDE plugin—detailing their features, licensing, platform support, and command‑line integration to help developers choose the most efficient tool for their workflow.
This article analyzes eight practical UI/UX case studies—from empathetic map navigation and smarter text input to privacy‑focused designs, motion‑enhanced feedback, IP interaction, and streamlined flows—showing how thoughtful design can dramatically improve user satisfaction across mobile apps.
This article demonstrates how to collect, clean, and visualize Taobao mooncake sales data using Python libraries such as Pandas, Pyecharts, jieba and collections, revealing top‑selling flavors, regional distribution, price ranges and shop rankings through step‑by‑step data‑processing and charting techniques.
This article introduces an open‑source Spring Boot starter that lets developers integrate, configure, monitor, and visualize thread pools without altering Spring Boot's core implementation, addressing common issues of unmanaged resources and difficult runtime adjustments.
The article explains why event‑tracking data needs governance, outlines a full‑link governance methodology, describes the organizational setup, and details the features of JD Tech’s one‑stop tracking management platform, including metadata unification, one‑click validation, real‑time dashboards, visualization tools, and H5‑native data integration.
This article revisits fundamental graph concepts, clarifies the distinction between graphs and charts, defines nodes, edges, geometry, and properties, and outlines data processing, layout strategies, and rendering approaches using Canvas and SVG, offering a concise roadmap for building a graph engine.
This article outlines a systematic three‑step framework—visual appeal, standout optimization, and comprehensive experiments—to help data‑science teams package and present their models effectively in competitions, complete with practical tips, visual examples, and a GitHub resource for creating compelling model graphics.
This article explains how introducing a data source layer in a visualization building system reduces repetitive component configuration, improves reuse, and empowers non‑developers to create and manage APIs for dynamic UI assembly.
This article explains how Python handles function arguments and default parameters, demonstrates the behavior with a simple code example, and shows how to visualize the execution flow using an online tool, helping readers understand why bar(3+2) yields the expected result.
This article explains the motivation, architecture, and implementation details of a generic map component that supports real‑time heatmap rendering using ThreeJS, covering GIS layer protocols, canvas limitations, WebGL advantages, and code examples for creating radial gradients, instanced meshes, and custom shaders.
This article demonstrates how to replace common Excel operations such as data import, VLOOKUP, pivot tables, and charting with Python libraries like pandas and plotly, providing step‑by‑step code examples, performance tips, and comparisons that help analysts transition from spreadsheet‑based workflows to programmatic data analysis.
This article introduces a collection of lesser‑known NumPy functions—including np.full_like, np.logspace, np.meshgrid, np.triu, np.ravel, np.vstack, np.r_, np.where, np.allclose, np.argsort, np.isneginf, np.polyfit, np.clip, np.count_nonzero, and np.array_split—demonstrating their usage with code examples and visualizations for data‑science and scientific‑computing tasks.
This tutorial shows how to use Python libraries such as itchat, jieba, matplotlib, snownlp, and Tencent Youtu to fetch WeChat friend data and then visualize gender distribution, detect face usage in avatars, generate word clouds and sentiment analysis for signatures, and export location information for mapping.
An in‑depth visual tutorial explains NumPy’s core concepts—from one‑dimensional vectors to high‑dimensional tensors—covering array creation, indexing, arithmetic, broadcasting, sorting, and advanced functions like meshgrid and einsum, empowering developers to harness efficient multidimensional computations in Python.
This article explains the purpose and definition of software architecture diagrams, introduces the 4+1 view classification and the C4 model (system context, container, component, and code diagrams), discusses common pitfalls, and provides practical guidance and tool recommendations for producing self‑describing, audience‑focused architecture visuals.
Learn how to overlay successive word‑guess visualisations in a single Matplotlib figure by reusing the figure manager, colour‑coding letters for correctness, and handling Jupyter‑specific output clearing, enabling a Wordle‑style game without generating multiple plots.
This article introduces the Deploy Dashboard plugin for Jenkins, explains how to visualize deployment status across environments, shows step‑by‑step instructions for adding versions, creating the dashboard view, adding deployment buttons, and provides pipeline code examples for seamless CI/CD integration.
Swagger’s poor JSON handling can hinder API testing, but two sleek visualization tools—JsonHero and JsonVisio—offer formatting, editing, tree views, and easy installation, enabling developers to efficiently view and manipulate JSON data directly from Swagger or standalone.
This article walks through the core PyTorch visualization utilities—making image grids, drawing bounding boxes, segmentation masks, and keypoints—explaining why they are needed, how to set up the pipeline, and providing complete code examples for each computer‑vision task.
This article introduces fifteen widely used Python libraries covering data collection, cleaning, visualization, machine‑learning, and web development, providing a comprehensive toolkit for data scientists and analysts to build end‑to‑end data pipelines.
This article introduces the open‑source visual tool NginxConfig, walks through installing Node.js and NginxConfig, shows how to configure documentation, front‑end, and API sites, generate the Nginx configuration, and deploy it on a Linux server.
Learn how to install Node.js, set up the open‑source NginxConfig visual tool, generate Nginx configuration files for static and dynamic proxies, and deploy them on a Linux server, all with step‑by‑step commands, code snippets, and practical examples.
This article details Meituan's end‑to‑end practice of knowledge‑graph visualization, covering basic concepts, scenario analysis, D3.js‑based architecture, layout optimization, visual‑noise reduction, rich interaction features, 3D extensions, real‑world deployments and future research directions.
The article details how an e‑commerce product middle platform’s front‑end employs visualization technology, a uni‑render approach that shares a Vuex store between an iframe and its parent via a sandboxed Vue instance, and a qiankun‑based micro‑frontend architecture, while addressing cross‑domain and editor integration challenges.
The article explores how front‑end engineering, through reusable component libraries, modular building platforms, and low‑code visual editors, transforms data‑screen development by abstracting complexity, boosting efficiency, and enabling scalable, reusable business components across multiple devices and scenarios.
This article reviews the seven most notable Python libraries and packages of 2018 for data scientists and AI practitioners, including AdaNet, TPOT, SHAP, Optimus, spaCy, Jupytext, and Chartify, with descriptions, installation commands, and usage examples.
This article demonstrates how to download Google’s massive N‑gram dataset, load the 1.4 billion 1‑gram records with Python and the PyTubes library, use NumPy to efficiently compute yearly word frequencies, and reproduce Google Ngram Viewer charts for Python and other programming languages.
In this talk, a Yuque front‑end engineer walks through the past six months of Yuque Board’s new features, unexpected use cases, emerging problems, fresh ideas, and novel methods, illustrating how abstraction, scientific falsification, and innovative thinking drive product evolution.
This article examines the challenges of modernizing legacy systems and presents a comprehensive open‑source toolkit—including syntax analysis, visualization, automated refactoring, and architecture guarding—that enables developers to quickly assess, visualize, and evolve outdated codebases across multiple platforms.
This article surveys academic, commercial, and open‑source word‑cloud solutions, explains the underlying algorithms, visual encodings, layout strategies, interaction techniques, and classifications, and discusses the strengths, limitations, and future directions of word‑cloud visualisation.
This article explains the concept of visual narrative, why it matters for multi‑dimensional data insight, and details AntV's design and implementation approach—including declarative chart definitions, timeline playback, React‑like components, and animation phases—to create interactive data stories.
This article explains the importance of clear architecture diagrams, defines architecture and its visual representations, outlines common diagram types and pitfalls, and introduces the C4 modeling approach with practical guidance for creating self‑describing, audience‑focused system diagrams.
This guide explains how to install the Linux smem tool, use its various options to report RSS, USS, and PSS memory metrics, filter results for specific processes or users, and generate visual pie and bar charts with Python's matplotlib for clearer memory analysis.
Markmap is a JavaScript tool that parses Markdown documents, extracts their hierarchical structure, and renders them as interactive mindmaps in the browser, offering three npm packages, editor plugins, and detailed usage examples with code snippets.
This tutorial demonstrates how to collect the top 2000 entries of the 2021 China Hurun Rich List using Python's requests library, process the data with pandas, and create insightful visualizations in Tableau, covering data extraction, cleaning, and analysis steps.
The article introduces Netease Thunderfire UX's big data team and its multidisciplinary approach to game user experience, covering topics such as mathematics, engineering, product practice, AI, visualization, platform development, data analysis, and tool creation for game data professionals.
This article presents a thorough collection of frequently used pandas commands for importing data, preprocessing, cleaning, transforming, analyzing, and visualizing datasets, complete with code examples and explanations to help Python developers perform efficient data analysis tasks.
The article explains why monitoring production ML models is essential to detect data and target drift, describes the open‑source Evidently AI library and its statistical tests, and demonstrates its use on a weather‑forecast example and a plant‑seedling image classification case, including dashboards, code snippets, and visual analysis of drift impact.
This tutorial walks through a complete pandas‑based workflow for analyzing a concrete‑strength dataset, covering data loading, cleaning, exploratory visualizations, correlation analysis, and targeted sub‑group investigations to uncover factors influencing product strength and suggest improvement measures.
This tutorial demonstrates how to use Python libraries such as itchat, jieba, matplotlib, SnowNLP, and Tencent Youtu SDK to collect WeChat friend information and perform data analysis and visualization on gender distribution, avatar characteristics, signature sentiment, and geographic location, providing practical code examples and visual results.
This article demonstrates how to collect historical Beijing weather data using Python web‑scraping, clean and transform it with pandas, visualize overall and monthly patterns, and extract insights such as the first winter snowfall each year and annual snow‑day counts.
This article walks through scraping Bilibili documentary data with Python, processing it using pandas, and visualizing regional distributions, genre comparisons, yearly trends, episode lengths, popularity metrics, and comment timing to uncover insights about Chinese, UK, and US documentary patterns.
This tutorial explains how to create and configure Grafana Stat panels—including text and background modes, threshold‑based coloring, unit settings, and Markdown/HTML text panels—to visualize metrics such as node uptime, CPU cores, and total memory on a dashboard.
This article explains the purpose and basic concepts of software architecture diagrams, introduces common view types such as scenario, logical, physical, process, and development, discusses criteria for good diagrams, highlights typical pitfalls, and presents the C4 modeling approach with practical examples and tool recommendations.
