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Data Analysis

547 articles · Page 5 of 6
Youzan Coder
Youzan Coder
Aug 21, 2020 · Industry Insights

From PRD Translator to Business Driver: The Three Growth Stages for Engineers

The article outlines three progressive stages for technical staff—from merely following PRD specifications, to understanding business needs and selecting appropriate solutions, and finally to proactively shaping business strategy—while sharing practical methods for demand exploration, project initiation, management, and data‑driven iteration.

Data Analysisbusiness thinkingcareer development
0 likes · 13 min read
From PRD Translator to Business Driver: The Three Growth Stages for Engineers
Liangxu Linux
Liangxu Linux
Aug 19, 2020 · Operations

How to Quickly Analyze Beijing Residency Data with Shell Commands

This tutorial shows how to use standard Unix shell tools such as grep, cut, sort, uniq, awk, and join to extract insights—top companies, most common surnames, popular given names, age distribution, and hometown statistics—from a JSON dataset of over 6,000 Beijing residency applicants.

Data AnalysisJSONShell
0 likes · 13 min read
How to Quickly Analyze Beijing Residency Data with Shell Commands
DevOps Coach
DevOps Coach
Aug 13, 2020 · Databases

How to Benchmark Elasticsearch Clusters with Rally: A Step‑by‑Step Guide

This article explains why large‑scale Elasticsearch deployments need rigorous performance testing, compares available testing tools, walks through installing and configuring the official Rally benchmark suite, details hardware recommendations, shows how to run tests against multiple cloud providers, and teaches you how to interpret the resulting metrics to make informed cluster‑selection decisions.

Data AnalysisElasticsearchRally
0 likes · 16 min read
How to Benchmark Elasticsearch Clusters with Rally: A Step‑by‑Step Guide
MaGe Linux Operations
MaGe Linux Operations
Aug 12, 2020 · Fundamentals

Why Learn Python? 6 Powerful Application Areas You Should Know

Python’s versatility makes it essential across fields—from AI and cloud computing to web development, web scraping, game creation, and data analysis—offering high demand, lucrative careers for IT professionals and productivity boosts for non‑IT workers, as illustrated by real‑world examples and industry trends.

Artificial IntelligenceCloud ComputingData Analysis
0 likes · 5 min read
Why Learn Python? 6 Powerful Application Areas You Should Know
MaGe Linux Operations
MaGe Linux Operations
Aug 5, 2020 · Big Data

8 Must‑Know Python Tools for Data Mining and Analysis

This article introduces eight essential Python libraries—Gensim, TensorFlow, SciPy, NumPy, Matplotlib, Pandas, Scikit‑Learn, and Keras—that empower developers to clean, prepare, merge, and accurately analyze data for effective data mining.

Data AnalysisLibrariesPython
0 likes · 4 min read
8 Must‑Know Python Tools for Data Mining and Analysis
58UXD
58UXD
Aug 5, 2020 · Product Management

Mastering Product Management: How to Decompose Problems and Boost Your Value 10x

This talk guides product managers and designers on breaking down complex goals—like achieving a million‑yuan sales target in three months—through structured problem‑decomposition methods such as MECE and SMART, while outlining a personal development framework that cultivates analytical, communication, and leadership skills across career stages.

Data AnalysisDesign thinkingMECE
0 likes · 7 min read
Mastering Product Management: How to Decompose Problems and Boost Your Value 10x
Alibaba Cloud Developer
Alibaba Cloud Developer
Jul 29, 2020 · Fundamentals

What Is Data Analysis? Definitions, Skills, History, and Practical Steps

This comprehensive guide explains what data analysis is, the types of data, its historical evolution, the relationship between data analysis, data science and business intelligence, essential skills, why analysis matters, and a step‑by‑step framework with models and metric design for effective decision‑making.

AnalyticsBusiness IntelligenceData Analysis
0 likes · 25 min read
What Is Data Analysis? Definitions, Skills, History, and Practical Steps
DataFunTalk
DataFunTalk
Jul 19, 2020 · Product Management

Stranger Social Apps: Business Insights, Data‑Driven Modeling, and Matching Algorithms

This article analyses the unique challenges of stranger‑social platforms such as Tinder and Tantan, exploring business models, user behavior, network effects, gender dynamics, data collection, algorithmic matching, risk control, and system architecture to guide product strategy and optimization.

Data AnalysisProduct Strategymatching algorithms
0 likes · 30 min read
Stranger Social Apps: Business Insights, Data‑Driven Modeling, and Matching Algorithms
Architects Research Society
Architects Research Society
Jul 14, 2020 · Frontend Development

Graph Visualization Ecosystem: Overview of Libraries, Toolkits, and Applications

This article, the final part of the GraphTech ecosystem series, provides a comprehensive overview of the front‑end graph visualization layer, detailing its role, benefits, and a curated list of over 70 open‑source and commercial libraries, toolkits, software, and built‑in visualizers for graph data analysis.

Data AnalysisGraph DatabasesGraph Visualization
0 likes · 9 min read
Graph Visualization Ecosystem: Overview of Libraries, Toolkits, and Applications
Python Crawling & Data Mining
Python Crawling & Data Mining
Jul 2, 2020 · Big Data

How to Identify Top Bilibili Creators Using the IFL Model: A Data‑Driven Guide

This article presents a complete data‑analysis workflow that scrapes Bilibili video metrics from January 2019 to March 2020, cleans and preprocesses 50,130 records, and extends the classic RFM model into an IFL framework—calculating interaction, frequency and like rates—to score and rank up‑creators across multiple categories, with code and datasets provided for replication.

Data AnalysisIFL modelPython
0 likes · 11 min read
How to Identify Top Bilibili Creators Using the IFL Model: A Data‑Driven Guide
Architect
Architect
Jun 30, 2020 · Artificial Intelligence

Analyzing TikTok's US Retention Surge: Algorithmic, Operational, and Marketing Factors

The article examines TikTok's dramatic increase in US user retention by dissecting supply‑side content growth, operational localization, marketing exposure, algorithmic matching, and external influences, and then proposes data‑driven and algorithmic interventions to sustain and amplify the platform's growth.

Data AnalysisTikTokUser Retention
0 likes · 17 min read
Analyzing TikTok's US Retention Surge: Algorithmic, Operational, and Marketing Factors
Full-Stack Internet Architecture
Full-Stack Internet Architecture
Jun 17, 2020 · Fundamentals

Turning User Tags into Actionable Business Insights: A VIP Fruit‑Plate Service Case Study

This article explains how to avoid idle user tags by integrating them into business processes, using a VIP fruit‑plate service example to illustrate tag basics, two promotion strategies, key performance metrics, and deeper implementation steps that turn profiling data into concrete operational value.

Business IntelligenceData AnalysisVIP service
0 likes · 8 min read
Turning User Tags into Actionable Business Insights: A VIP Fruit‑Plate Service Case Study
DataFunTalk
DataFunTalk
Jun 15, 2020 · Artificial Intelligence

Understanding and Handling Bad Cases in E-commerce Recommendation Systems

The article explores why bad cases occur in e‑commerce recommendation and search pipelines, classifies their types, demonstrates data‑driven analysis methods, and proposes practical online and offline strategies—including rule‑based fixes, model improvements, and iterative feedback loops—to continuously improve user experience and business metrics.

Data Analysisbadcasee-commerce
0 likes · 23 min read
Understanding and Handling Bad Cases in E-commerce Recommendation Systems
Fulu Network R&D Team
Fulu Network R&D Team
Jun 11, 2020 · Artificial Intelligence

Intelligent Inventory Management: Comparing Prophet and LSTM for Time‑Series Forecasting

This article presents an intelligent inventory management solution that predicts product consumption using two time‑series algorithms—Facebook's Prophet and LSTM deep learning—detailing data sources, preprocessing, model configuration, evaluation metrics, and a comparative analysis of their performance and suitability.

Data AnalysisLSTMProphet
0 likes · 16 min read
Intelligent Inventory Management: Comparing Prophet and LSTM for Time‑Series Forecasting
Python Programming Learning Circle
Python Programming Learning Circle
Jun 4, 2020 · Fundamentals

Superstore Sales Data Analysis: From Data Preprocessing to RFM Modeling

This article presents a comprehensive analysis of a global supermarket's four‑year sales dataset, covering data collection, preprocessing, exploratory visualizations, sales, quantity, profit, market segmentation, product performance, customer segmentation, RFM modeling, and actionable recommendations to improve revenue and customer retention.

Data AnalysisRFM modelSales Forecasting
0 likes · 27 min read
Superstore Sales Data Analysis: From Data Preprocessing to RFM Modeling
Python Crawling & Data Mining
Python Crawling & Data Mining
May 19, 2020 · Fundamentals

Master Pandas: From Import to Data Cleaning in One Comprehensive Guide

This tutorial walks through essential pandas operations—including importing modules, building a sample shopping dataset, reading and writing CSV files, inspecting data structures, and performing thorough data cleaning such as handling missing values, trimming spaces, case conversion, replacements, deletions, duplicate removal, type casting, and column renaming—complete with code snippets and visual results.

Data AnalysisDataFramePython
0 likes · 10 min read
Master Pandas: From Import to Data Cleaning in One Comprehensive Guide
Architect's Tech Stack
Architect's Tech Stack
May 15, 2020 · Databases

May 2020 Programmer Salary Report and Oracle High‑Performance System Architecture Book Recommendation

The article presents May 2020 programmer salary statistics across China, analyzes data anomalies and corrective rules, highlights regional wage differences, and recommends the book “Oracle High‑Performance System Architecture Practice” for deep understanding of Oracle database performance and optimization techniques.

Data AnalysisOraclebook recommendation
0 likes · 3 min read
May 2020 Programmer Salary Report and Oracle High‑Performance System Architecture Book Recommendation
Architects Research Society
Architects Research Society
Apr 27, 2020 · Fundamentals

What Is an IoT Platform? A Simple Non‑Technical Overview

This article explains what an IoT platform is, how it fits into a complete IoT system, the functions it provides such as connectivity, protocol handling, security, data collection and analysis, and offers guidance on when businesses should adopt one despite cost trade‑offs.

Data AnalysisDevice ManagementHardware
0 likes · 6 min read
What Is an IoT Platform? A Simple Non‑Technical Overview
58UXD
58UXD
Apr 15, 2020 · Product Management

How Designers Can Leverage Data Analysis to Solve Real‑World Problems

Designers often overlook data analysis, yet mastering it helps identify problems, set measurable goals, generate hypotheses, collect and interpret metrics, and draw actionable conclusions, ultimately guiding product decisions and improving conversion rates across various scenarios such as page performance, financial calculations, and insurance plan selection.

Conversion OptimizationData AnalysisUX
0 likes · 12 min read
How Designers Can Leverage Data Analysis to Solve Real‑World Problems
Full-Stack Internet Architecture
Full-Stack Internet Architecture
Mar 17, 2020 · Fundamentals

A Real‑Life Example of User Profiling to Boost Sales

This article uses a vivid kite‑selling story to illustrate how user profiling, data tagging, and recommendation tactics can be combined to increase transaction volume, improve average order value, and avoid common pitfalls such as unclear goals, poor data quality, and unvalidated tags.

Data AnalysisData Qualitymarketing strategy
0 likes · 9 min read
A Real‑Life Example of User Profiling to Boost Sales
DevOps
DevOps
Mar 10, 2020 · Backend Development

Analyzing Git Repository Commit Statistics with libgit2sharp, .NET Core, and PowerBI

This article describes how to collect, process, and visualize Git commit data—including hashes, authors, dates, messages, and line changes—by using native git commands, the libgit2sharp .NET library, a custom cross‑platform CLI tool, and PowerBI dashboards for comprehensive reporting.

.NET CoreBackendCLI
0 likes · 8 min read
Analyzing Git Repository Commit Statistics with libgit2sharp, .NET Core, and PowerBI
FunTester
FunTester
Feb 19, 2020 · Operations

Turning Raw Performance Test Logs into Readable Text Charts with Groovy

This article explains how to replace cumbersome Python‑Plotly visualizations of performance test logs with a lightweight Groovy solution that generates plain‑text bar charts directly in the shell or email, using Unicode block characters and a bucket‑based median algorithm.

Data AnalysisGroovyShell
0 likes · 6 min read
Turning Raw Performance Test Logs into Readable Text Charts with Groovy
360 Tech Engineering
360 Tech Engineering
Feb 13, 2020 · Big Data

COVID-19 Daily Report and Data Analysis – February 12, 2020

The February 12, 2020 COVID‑19 daily report details a sharp rise in national confirmed cases to 59,804, explains the inclusion of clinically diagnosed cases in Hubei, presents provincial death and cure rates, and offers extensive data‑driven analyses of trends, infection coefficients, and regional transmission dynamics.

COVID-19ChinaData Analysis
0 likes · 11 min read
COVID-19 Daily Report and Data Analysis – February 12, 2020
Python Programming Learning Circle
Python Programming Learning Circle
Feb 3, 2020 · Fundamentals

Master Pandas: Essential Data Manipulation Techniques for Python Beginners

This guide introduces pandas, the essential Python library for data science, covering installation, data import/export, basic DataFrame operations, logical filtering, visualization with matplotlib, performance tips using tqdm, and advanced techniques like merging, grouping, and iterating, helping beginners become efficient data analysts.

Data AnalysisData manipulationpandas
0 likes · 8 min read
Master Pandas: Essential Data Manipulation Techniques for Python Beginners
Architecture Digest
Architecture Digest
Jan 28, 2020 · Artificial Intelligence

Predicting COVID-19 Cases Using LSTM Based on SARS Data: Methodology and Evaluation

This article investigates whether a short‑term time‑series algorithm, specifically an LSTM model trained on limited SARS data, can predict and assess COVID‑19 case numbers, describing data collection, model training, experimental validation, error analysis, and practical implications of the findings.

COVID-19 predictionData AnalysisEpidemiology
0 likes · 11 min read
Predicting COVID-19 Cases Using LSTM Based on SARS Data: Methodology and Evaluation
ITPUB
ITPUB
Jan 21, 2020 · Fundamentals

Mastering Data Queries: Pandas vs SQL – A Step‑by‑Step Comparison

This tutorial walks data analysts through a side‑by‑side comparison of common data‑manipulation tasks using pandas in Python and SQL, covering everything from basic selects and filters to joins, aggregations, unions, ordering, case expressions, and data updates with clear code examples.

Data AnalysisSQLTutorial
0 likes · 15 min read
Mastering Data Queries: Pandas vs SQL – A Step‑by‑Step Comparison
Programmer DD
Programmer DD
Jan 5, 2020 · Fundamentals

Why Every Engineer Must Master Business Knowledge to Stay Relevant

The article argues that programmers who only code are becoming replaceable, emphasizing that mastering real-world business processes, data-driven decision making, and continuous curiosity is essential for engineers to remain valuable and drive meaningful product outcomes.

Data AnalysisSoftware Engineeringbusiness
0 likes · 11 min read
Why Every Engineer Must Master Business Knowledge to Stay Relevant
Youzan Coder
Youzan Coder
Dec 30, 2019 · Operations

How to Measure and Improve Project Efficiency: A Practical Guide

This article explains why measurement is essential for management, outlines a step‑by‑step process for collecting and analyzing efficiency metrics, and shows how to turn data‑driven insights into concrete conclusions and actionable improvement plans for software projects.

Data Analysiscontinuous improvementefficiency
0 likes · 10 min read
How to Measure and Improve Project Efficiency: A Practical Guide
Meituan Technology Team
Meituan Technology Team
Nov 21, 2019 · Big Data

Designing a Platformized Jupyter Service Integrated with Spark for Meituan

Meituan Homestay created a platform‑wide Jupyter service built on JupyterHub and Kubernetes that integrates Spark, scheduling, documentation and storage, providing seamless, reproducible notebooks with custom extensions, magics and container isolation to unify data analysis, model training and production workflows.

Data AnalysisJupyterKubernetes
0 likes · 19 min read
Designing a Platformized Jupyter Service Integrated with Spark for Meituan
FunTester
FunTester
Nov 14, 2019 · Backend Development

Web Scraping CBA Match Data with Java: Methodology and Full Code Example

This article explains how to scrape Chinese Basketball Association (CBA) match data from a portal website, analyzes the page structure, extracts table rows using regular expressions, converts them to CSV format, and provides a complete Java/Groovy code example for automated data collection.

CBACSVData Analysis
0 likes · 8 min read
Web Scraping CBA Match Data with Java: Methodology and Full Code Example
MaGe Linux Operations
MaGe Linux Operations
Oct 5, 2019 · Fundamentals

How to Scrape and Analyze Holiday Tourist Spot Data with Python

This tutorial walks you through using Python to collect tourism data from Qunar, extract key fields such as name, price, and rating, store the results in Excel with pandas, and visualize sales and popularity trends using pyecharts, including a simple recommendation algorithm.

Data AnalysisPyechartsPython
0 likes · 8 min read
How to Scrape and Analyze Holiday Tourist Spot Data with Python
Snowball Engineer Team
Snowball Engineer Team
Sep 24, 2019 · Big Data

Snowball Data Middle Platform (AIBO): Architecture, Capabilities, and Future Outlook

The article introduces Snowball's AIBO data middle platform, detailing its storage‑compute separation architecture, core capabilities such as data integration, catalog, tagging, analysis tools, micro‑service data APIs, and outlines future enhancements for security, lineage, and continuous business‑driven iteration.

Data AnalysisData Integrationbig data
0 likes · 12 min read
Snowball Data Middle Platform (AIBO): Architecture, Capabilities, and Future Outlook
DataFunTalk
DataFunTalk
Sep 3, 2019 · Big Data

The Value of Big Data in Machine Learning: Detailed Illustration and Insights

This article explains how big data enhances machine learning by enabling finer-grained data characterization, improving confidence in statistical conclusions, and supporting smarter learning through multiple stages of model development, illustrated with concrete examples and a discussion of sample size dilemmas.

Data Analysisbig datamachine learning
0 likes · 10 min read
The Value of Big Data in Machine Learning: Detailed Illustration and Insights
Python Crawling & Data Mining
Python Crawling & Data Mining
Aug 20, 2019 · Fundamentals

Master Jupyter Notebook: A Step‑by‑Step Data Analysis Guide for Beginners

Learn how to install Jupyter via Anaconda or pip, create and manage notebooks, understand cells and kernels, write and run Python code, explore a Fortune 500 dataset with pandas, clean missing values, and visualize profit and revenue trends using matplotlib and seaborn—all illustrated with screenshots and code snippets.

Data AnalysisJupyter NotebookPython
0 likes · 15 min read
Master Jupyter Notebook: A Step‑by‑Step Data Analysis Guide for Beginners
Python Crawling & Data Mining
Python Crawling & Data Mining
Aug 13, 2019 · Fundamentals

Unlock Jupyter Notebook Power: Shell Commands, Magic, Logging & Seaborn Tricks

This guide explores advanced Jupyter Notebook techniques, including using shell commands, line and cell magic commands, autosave configuration, timing execution, logging customization, running external scripts, integrating Seaborn for enhanced visualizations, managing databases with ipython-sql, and extending functionality with plugins.

Data AnalysisJupyterMagic Commands
0 likes · 17 min read
Unlock Jupyter Notebook Power: Shell Commands, Magic, Logging & Seaborn Tricks
Python Crawling & Data Mining
Python Crawling & Data Mining
Aug 11, 2019 · Fundamentals

How to Scrape and Visualize a Year of Global Earthquake Data with Python

This tutorial walks you through discovering a real‑time earthquake data source, analyzing its pagination API, building a Python scraper with requests, parsing the JSON responses, storing the results in CSV, and performing visual analyses such as top‑magnitude locations, monthly frequency, repeat‑site counts, magnitude distribution, and word‑cloud generation.

CSVData AnalysisEarthquake Data
0 likes · 8 min read
How to Scrape and Visualize a Year of Global Earthquake Data with Python
Python Crawling & Data Mining
Python Crawling & Data Mining
Jul 14, 2019 · Backend Development

What I Learned from 11 Python/Web Interviews: Tips, Mistakes, and Must‑Know Questions

After quitting my job in Shanghai, I went through eleven technical interviews ranging from Python full‑stack to data‑analysis roles, sharing detailed experiences, resume strategies, scheduling tactics, interview outcomes, key takeaways, and a curated list of frequently asked interview questions.

Data AnalysisDjangoInterview Tips
0 likes · 11 min read
What I Learned from 11 Python/Web Interviews: Tips, Mistakes, and Must‑Know Questions
Tencent Advertising Technology
Tencent Advertising Technology
Jun 13, 2019 · Artificial Intelligence

Competition Solution Overview: Data Analysis, Rule‑Based and Neural Network Models for Advertising Prediction

The article details a contestant's end‑to‑end approach for an advertising competition, covering data analysis, rule‑based preprocessing, a three‑layer neural network architecture, model‑rule ensemble weighting, self‑correction strategies for the B phase, and final model‑only solutions that achieved top scores.

AdvertisingCompetitionData Analysis
0 likes · 8 min read
Competition Solution Overview: Data Analysis, Rule‑Based and Neural Network Models for Advertising Prediction
NetEase Media Technology Team
NetEase Media Technology Team
Jun 5, 2019 · Product Management

Mastering AB Testing: From Basics to Scalable Multi‑Layer Architecture

This article explains the fundamentals of AB testing, outlines the iterative workflow, shares best‑practice guidelines, compares single‑layer and multi‑layer experiment frameworks, and details the technical implementation—including SDK design, hashing algorithms, data denoising, and statistical evaluation methods.

AB TestingBackendData Analysis
0 likes · 15 min read
Mastering AB Testing: From Basics to Scalable Multi‑Layer Architecture
58UXD
58UXD
May 29, 2019 · Product Management

How Data Analysis Drives User Growth: From AARRR Funnel to Practical Tools

This article explains fundamental data‑analysis methods, introduces the AARRR user‑growth model with key metrics for each stage, and presents practical tools such as user path analysis, funnel conversion, heatmaps, and A/B testing to help product teams make data‑driven decisions and continuously improve user experience.

AARRRAB TestingData Analysis
0 likes · 9 min read
How Data Analysis Drives User Growth: From AARRR Funnel to Practical Tools
MaGe Linux Operations
MaGe Linux Operations
May 28, 2019 · Big Data

Recreating Google Ngram Trends with Python, PyTubes, and NumPy

This article demonstrates how to download the Google 1‑gram dataset, load and filter billions of rows with the PyTubes library, compute yearly word frequencies using NumPy, and reproduce the classic Python usage trend chart while discussing performance considerations and future improvements.

Data AnalysisGoogle NgramNumPy
0 likes · 9 min read
Recreating Google Ngram Trends with Python, PyTubes, and NumPy
Youku Technology
Youku Technology
May 20, 2019 · Big Data

Data‑Driven Dating Guide: Analyzing Zhihu Answers to Identify Potential Partners

In a playful data‑driven experiment, the author scraped 27,664 Zhihu answers to “What are your dating criteria?”, filtered out short, outdated, high‑profile or already‑matched posts, applied follower‑and engagement‑thresholds to narrow the pool to 480 candidates, then ranked the top 30 by a like‑to‑comment ratio, sharing the code and dataset for reproducibility.

Data AnalysisFilteringZhihu
0 likes · 8 min read
Data‑Driven Dating Guide: Analyzing Zhihu Answers to Identify Potential Partners
360 Tech Engineering
360 Tech Engineering
May 20, 2019 · Fundamentals

A Data‑Driven Guide to Finding a Partner: From Crawling Zhihu Answers to Ranking Candidates

This article walks through a complete data‑analysis workflow—scraping Zhihu dating‑preference answers, cleaning and filtering the data, deriving gender and activity metrics, designing a four‑step screening process, and finally ranking candidates with a custom like‑to‑comment index—to help a single programmer create a concise, high‑quality list of potential partners.

Data AnalysisWeb ScrapingZhihu
0 likes · 9 min read
A Data‑Driven Guide to Finding a Partner: From Crawling Zhihu Answers to Ranking Candidates
58UXD
58UXD
Apr 18, 2019 · Operations

How Winning Design Strategies Boosted Spring Festival Campaign Traffic

This article dissects the 2019 Spring Festival (春运) campaign by 58.com, revealing how a win‑win design mindset, data‑driven insights, and integrated business collaboration transformed user experience, increased traffic, and delivered measurable results across multiple channels and game‑based interactions.

Data AnalysisDesign thinkingmarketing case study
0 likes · 11 min read
How Winning Design Strategies Boosted Spring Festival Campaign Traffic
Python Crawling & Data Mining
Python Crawling & Data Mining
Apr 15, 2019 · Databases

Master SQL Basics: A Concise Review Guide for Data Analysts

This guide provides a concise review of fundamental database concepts—including definitions of databases, RDBMS, SQL, and tables—and walks through essential SQL query techniques, data manipulation commands, schema definition statements, and control language basics, offering practical examples for data analysts.

DDLDMLData Analysis
0 likes · 9 min read
Master SQL Basics: A Concise Review Guide for Data Analysts
dbaplus Community
dbaplus Community
Mar 31, 2019 · Big Data

What Do 10,000+ GitHub Stars Reveal About China’s 996 Work Culture?

An in‑depth data analysis of the 996.ICU GitHub repository shows where the protesting programmers work, which cities they live in, their typical GitHub activity, the most discussed issues, and the common keywords in their bios, highlighting the scale of the anti‑996 movement.

996ChinaData Analysis
0 likes · 9 min read
What Do 10,000+ GitHub Stars Reveal About China’s 996 Work Culture?
Python Crawling & Data Mining
Python Crawling & Data Mining
Mar 24, 2019 · Backend Development

How to Scrape Douban Book Data and Analyze It with Python

This tutorial shows how to collect book metadata such as publisher, publication date, ISBN, price, rating and review count from Douban for a list of titles stored in Excel, using Python requests, lxml XPath parsing, pandas for merging and analysis, and visualizing the results with matplotlib.

Data AnalysisPythonXPath
0 likes · 14 min read
How to Scrape Douban Book Data and Analyze It with Python
Tencent Cloud Developer
Tencent Cloud Developer
Mar 13, 2019 · Fundamentals

Introduction to NumPy, pandas, and Matplotlib for Python Data Analysis

This article introduces Python’s core data‑analysis stack—NumPy for fast multidimensional arrays, pandas for labeled DataFrames, and Matplotlib for interactive plotting—while showing how to set up a Jupyter/VS Code environment, perform basic indexing, slicing, and visualisation, and clean log files with pandas.

Data AnalysisJupyterNumPy
0 likes · 9 min read
Introduction to NumPy, pandas, and Matplotlib for Python Data Analysis
Python Crawling & Data Mining
Python Crawling & Data Mining
Feb 27, 2019 · Fundamentals

R vs Python for Data Analysis: Which Language Wins?

This article presents a detailed infographic comparison of R and Python from a data‑science perspective, outlining their histories, ecosystems, usability, community support, and advantages in data analysis to help readers decide which language better fits their projects.

Data AnalysisData SciencePython
0 likes · 5 min read
R vs Python for Data Analysis: Which Language Wins?
iQIYI Technical Product Team
iQIYI Technical Product Team
Dec 14, 2018 · Artificial Intelligence

AI Applications in Modern Technology and Society

The podcast examines AI’s rapid integration into entertainment, security and personalization, highlighting its use in automated video editing, facial-recognition tagging of celebrities and non-celebrities, while debating ethical concerns such as echo-chambers, emotional nuance, and the technology’s transformative yet limited role across industries.

AIData AnalysisEntertainment
0 likes · 7 min read
AI Applications in Modern Technology and Society
MaGe Linux Operations
MaGe Linux Operations
Dec 6, 2018 · Fundamentals

Mastering AWK: Powerful Text Processing and Reporting Techniques

AWK is a versatile text-processing language that reads files line by line, splits fields by default spaces, and applies pattern-action rules to analyze data, generate reports, and perform complex tasks such as extracting columns, counting records, and scripting with built-in variables, loops, and conditional statements.

Data AnalysisLinuxawk
0 likes · 14 min read
Mastering AWK: Powerful Text Processing and Reporting Techniques
MaGe Linux Operations
MaGe Linux Operations
Nov 30, 2018 · Artificial Intelligence

Avoid These Common NumPy Pitfalls When Doing Machine Learning

This article examines frequent traps when using NumPy for matrix operations in machine learning, comparing its quirks to MATLAB/Octave and offering practical insights to prevent shape errors, inefficient indexing, confusing syntax, and unintuitive code patterns.

Data AnalysisNumPyPython
0 likes · 7 min read
Avoid These Common NumPy Pitfalls When Doing Machine Learning
Python Crawling & Data Mining
Python Crawling & Data Mining
Nov 27, 2018 · Big Data

What Do Python Jobs Really Pay? Inside a Data‑Driven Salary & Skill Analysis

This article crawls Lagou.com to collect 4,500 Python‑related job postings across ten roles, extracts salary, education, experience and skill requirements, visualizes the data with treemaps, rose charts, bar charts and word clouds, and provides detailed insights into each position’s market demands and compensation trends.

Data AnalysisPythonSkills
0 likes · 18 min read
What Do Python Jobs Really Pay? Inside a Data‑Driven Salary & Skill Analysis
Tencent Cloud Developer
Tencent Cloud Developer
Nov 23, 2018 · Big Data

20 Free and Open-Source Data Visualization Tools

These 20 free and open‑source data visualization tools—from JavaScript libraries like D3.js and Chartist.js to user‑friendly platforms such as Datawrapper, Google Data Studio, and Tableau Public—enable businesses and analysts to transform raw data into interactive charts, maps, timelines, and dashboards, improving insight, decision‑making, and profitability.

Data AnalysisData VisualizationJavaScript libraries
0 likes · 12 min read
20 Free and Open-Source Data Visualization Tools
Python Crawling & Data Mining
Python Crawling & Data Mining
Nov 22, 2018 · Big Data

How to Scrape and Analyze China’s Tourist Attractions Data with Python

This article demonstrates how to crawl Qunar’s nationwide tourism listings with Python, extract key fields such as name, level, location and price, handle anti‑scraping measures, and then perform comprehensive data analysis and visualisation—including sales rankings, popularity scores, geographic distribution and geocoding using the Amap API.

Data AnalysisGeocodingPython
0 likes · 11 min read
How to Scrape and Analyze China’s Tourist Attractions Data with Python
Big Data and Microservices
Big Data and Microservices
Sep 3, 2018 · Big Data

From Raw Data to Business Impact: A Complete Data Analyst Skill Guide

The article outlines a comprehensive data‑analyst competency framework, covering data collection, storage, extraction, mining, analysis, visualization, and practical application, and provides concrete questions, techniques, and tool recommendations to help analysts turn raw data into actionable business insights.

Business IntelligenceData AnalysisData Pipeline
0 likes · 9 min read
From Raw Data to Business Impact: A Complete Data Analyst Skill Guide
21CTO
21CTO
Aug 21, 2018 · R&D Management

From Code to Leadership: How Mid‑Career Developers Can Thrive in Management

The article shares a veteran programmer’s journey from facing a mid‑career tech crisis to leveraging data analysis and soft‑skill expertise, illustrating how shifting focus from pure coding to holistic project and business insight can open new management opportunities and sustain relevance in the evolving tech industry.

Data AnalysisR&D managementSoftware Engineering
0 likes · 16 min read
From Code to Leadership: How Mid‑Career Developers Can Thrive in Management
Big Data and Microservices
Big Data and Microservices
Aug 16, 2018 · Big Data

Mastering Big Data Analysis: 5 Core Aspects and 4 Key Methods

This article outlines the five fundamental aspects of big data analysis—visualization, data‑mining algorithms, predictive analytics, semantic engines, and data quality management—and explains four primary analytical approaches: descriptive, diagnostic, predictive, and prescriptive analysis.

Data Analysisbig datadata mining
0 likes · 6 min read
Mastering Big Data Analysis: 5 Core Aspects and 4 Key Methods
Ctrip Technology
Ctrip Technology
Aug 7, 2018 · Artificial Intelligence

Forecasting and Monitoring in Business Intelligence: Practical Data‑Analysis Methods and Model‑Building Tips

The article explains how a data analyst can use statistical and machine‑learning models such as linear regression, tree‑based boosting, STL decomposition, and Prophet for both non‑time‑series forecasting and time‑series monitoring, highlighting data‑quality concerns, feature‑engineering practices, and deployment considerations like PMML packaging.

BIData AnalysisProphet
0 likes · 13 min read
Forecasting and Monitoring in Business Intelligence: Practical Data‑Analysis Methods and Model‑Building Tips
MaGe Linux Operations
MaGe Linux Operations
Aug 2, 2018 · Big Data

Unlocking PUBG Victory: Data‑Driven Insights on Drop Zones, Final Circles, Weapons, and Kill Strategies

This article analyzes 18 million PUBG match records using Python to reveal optimal drop locations, high‑probability final‑circle spots, preferred weapons, and the relationship between kill distance, kill count, and winning chances, providing data‑driven strategies for players seeking more chicken dinners.

Data AnalysisGame AnalyticsPUBG
0 likes · 13 min read
Unlocking PUBG Victory: Data‑Driven Insights on Drop Zones, Final Circles, Weapons, and Kill Strategies
Python Crawling & Data Mining
Python Crawling & Data Mining
Jul 31, 2018 · Big Data

Can Web‑Scraped Movie Reviews Predict Box Office? A Python Data‑Mining Case Study

Using Python to scrape over ten thousand Maoyan comments for the comedy film “The Billionaire” (西虹市首富), this article demonstrates data cleaning, geographic heat‑maps, city‑wise rating analysis, word‑cloud generation, and a simple box‑office forecast based on a comparable movie, illustrating practical web‑scraping and data‑mining techniques.

Box Office PredictionData AnalysisMovie Reviews
0 likes · 10 min read
Can Web‑Scraped Movie Reviews Predict Box Office? A Python Data‑Mining Case Study
MaGe Linux Operations
MaGe Linux Operations
Jul 27, 2018 · Fundamentals

Master Pandas: Essential Techniques for Data Exploration and Analysis

This tutorial introduces Pandas fundamentals, covering installation, data structures, importing CSV files, inspecting and reshaping data, filtering with boolean masks, indexing, applying functions, grouping, merging, quick plotting, and saving results, all illustrated with clear examples and images.

Data AnalysisDataFrameFiltering
0 likes · 14 min read
Master Pandas: Essential Techniques for Data Exploration and Analysis
ITPUB
ITPUB
Jul 23, 2018 · Big Data

What China's Vaccine Procurement Data Reveals: A Province‑Level Analysis

This article documents the collection, cleaning, and statistical analysis of publicly released second‑category vaccine procurement data from 28 Chinese provinces, highlighting data sources, processing steps with pandas, top manufacturers, regional market shares, and the challenges encountered during the effort.

ChinaData Analysisbig data
0 likes · 9 min read
What China's Vaccine Procurement Data Reveals: A Province‑Level Analysis
ITPUB
ITPUB
Jul 23, 2018 · Big Data

Uncovering China’s Vaccine Procurement: A Province‑Level Data Crawl and Analysis

This article documents the collection of public second‑class vaccine procurement data from 28 Chinese provinces, describes the CSV schema, outlines the challenges faced during web scraping, and presents a pandas‑driven statistical analysis that highlights top manufacturers and their provincial market shares.

ChinaData Analysispandas
0 likes · 10 min read
Uncovering China’s Vaccine Procurement: A Province‑Level Data Crawl and Analysis
Tencent Cloud Developer
Tencent Cloud Developer
Jul 23, 2018 · Big Data

Analysis of Chinese Second-Class Vaccine Procurement Data

The study aggregates and cleans 2017‑2020 Chinese second‑class vaccine procurement data from 28 provinces into a 1,529‑record CSV, revealing a right‑skewed distribution where a handful of manufacturers—led by Beijing Kexing and Changchun Changsheng—account for the majority of entries, while noting gaps in several regions and encouraging further collaborative refinement.

Chinese healthcareData Analysisbig data
0 likes · 10 min read
Analysis of Chinese Second-Class Vaccine Procurement Data
Programmer DD
Programmer DD
Jul 10, 2018 · Big Data

Which Car Wins on Didi? Data‑Driven Model Selection for Ride‑Hailing

Using real‑time order and fuel‑point data from the Didi driver app, the author demonstrates a systematic, data‑driven approach to identify the most cost‑effective car models for ride‑hailing across major Chinese cities, complete with methodology, analysis, and city‑specific rankings.

Data AnalysisDidicar selection
0 likes · 19 min read
Which Car Wins on Didi? Data‑Driven Model Selection for Ride‑Hailing
21CTO
21CTO
Jul 6, 2018 · Fundamentals

Why Every Engineer Must Master Business Insight (And How)

The article argues that programmers need to deeply understand business concepts and data-driven decision making, explaining what business entails, why it matters for engineers, and offering practical methods to acquire business knowledge for more impactful, sustainable tech solutions.

Data AnalysisSoftware Engineeringbusiness
0 likes · 11 min read
Why Every Engineer Must Master Business Insight (And How)
Efficient Ops
Efficient Ops
Jun 21, 2018 · Fundamentals

Can Python Predict the 2018 World Cup Champion? A Data‑Driven Analysis

This article demonstrates how to use Python, pandas, and Jupyter Notebook to explore a comprehensive World Cup dataset, clean and enrich the data, visualize win and goal statistics for all teams, and finally predict the top three contenders for the 2018 tournament.

Data AnalysisPythonWorld Cup
0 likes · 12 min read
Can Python Predict the 2018 World Cup Champion? A Data‑Driven Analysis
Qunar Tech Salon
Qunar Tech Salon
Jun 15, 2018 · Artificial Intelligence

Predicting the 2018 FIFA World Cup Winners Using Machine Learning

This article demonstrates how to collect historical football data, perform exploratory analysis and feature engineering, and apply a logistic‑regression model in Python to predict the 2018 FIFA World Cup champion, group‑stage results, and knockout‑stage outcomes.

Data AnalysisFIFA World CupLogistic Regression
0 likes · 8 min read
Predicting the 2018 FIFA World Cup Winners Using Machine Learning
Meituan Technology Team
Meituan Technology Team
May 10, 2018 · Operations

Quality Operations for Intelligent Payment: Improving Test Phase Metrics

By applying a PDCA‑based quality‑operation framework that aligns QA KPIs, drills defect data across dimensions, automates test‑gate checks, and drives continuous improvement actions, Meituan Dianping’s Intelligent Payment team reduced severe defect ratios, met defined metric targets, and boosted iteration efficiency while supporting rapid business growth.

Data AnalysisProcess Improvementmetrics
0 likes · 12 min read
Quality Operations for Intelligent Payment: Improving Test Phase Metrics
Qunar Tech Salon
Qunar Tech Salon
May 4, 2018 · Fundamentals

Quantifying and Analyzing App Performance Slowness: A QA Perspective

The article explains how QA engineers can systematically measure, analyze, and resolve app slowness by quantifying response times, dissecting device fragmentation, network latency, and backend complexity, and establishing a data‑driven quality loop to improve user experience.

Data Analysisapp performancemobile testing
0 likes · 7 min read
Quantifying and Analyzing App Performance Slowness: A QA Perspective
Beike Product & Technology
Beike Product & Technology
Apr 26, 2018 · Big Data

Chain Home's OLAP Platform and Kylin Usage

This article details Chain Home's OLAP platform architecture and Kylin usage, covering the evolution from early ROLAP to MOLAP multi-dimensional engine, Kylin's basic principles, platform structure, application scenarios, usage specifications, capability extensions, and middleware development.

Apache KylinChain HomeCube
0 likes · 11 min read
Chain Home's OLAP Platform and Kylin Usage
MaGe Linux Operations
MaGe Linux Operations
Mar 29, 2018 · Artificial Intelligence

Master Python’s Top Data Analysis & AI Libraries with Hands‑On Code

This article introduces Python’s essential features for data analysis and mining, then reviews the most widely used libraries—NumPy, SciPy, Matplotlib, Pandas, Scikit‑Learn, Keras, and Gensim—each accompanied by concise code examples that demonstrate their core capabilities.

Data AnalysisKerasPython
0 likes · 14 min read
Master Python’s Top Data Analysis & AI Libraries with Hands‑On Code
dbaplus Community
dbaplus Community
Jan 29, 2018 · Operations

How Data‑Driven Monitoring Unlocks Real Value for Ops Teams

This article explains why quantifiable data is essential for evaluating the impact of operational changes, outlines common data‑collection stacks, defines core business and user‑centric metrics, and demonstrates practical monitoring techniques such as PCU analysis, simulated user flows, and intelligent scaling to turn ops work into measurable business value.

Business MetricsData AnalysisDevOps
0 likes · 15 min read
How Data‑Driven Monitoring Unlocks Real Value for Ops Teams