Data · GitHub

🔨 🍇 💻 🚀 GraphScope: A One-Stop Large-Scale Graph Computing System from Alibaba | 一站式图计算系统

阿里巴巴去Oracle数据迁移同步工具(全量+增量,目标支持MySQL/DRDS)

AI-powered Jupyter Notebook. Use AI to generate and edit code cells, automatically fix errors, and chat with your data

PYTHON E POSTGRESQL - EXTRACT TRANSFORM LOAD - ETL - DADOS PÚBLICOS DA RECEITA FEDERAL DO BRASIL - RFB, INSTITUTO BRASILEIRO DE GEOGRAFIA E ESTATÍSTICA - IBGE E AGÊNCIA NACIONAL DO PETRÓLEO, GÁS NATURAL E BIOCOMBUSTÍVEIS - ANP - PYTHON E POSTGRESQL

Run your own PaaS using Docker, Traefik, and great analytics

Apply different analysis & data science tools on your Telegram / Whatsapp chat and get exciting insights!

Stop staring at cron expressions: discover the missing visual calendar that finally lets you manage DAGs like a human.

Cross platform declarative DB framework for apps, inspired by SwiftData, refined by us.

• Zero-Boilerplate Schemas: No need to manually define your database schema (unlike Fluent for example). Vein generates all information it needs automatically from your model declarations using the @Model macro at compile time.
• Identity Map: Ensures a maximum of one in-memory class instance per database row and context.

A lightweight Analytics library that logs events, identifies the user, and dispatches the data at one. 📊

• 🔧 Easy Integration - Single API for multiple analytics services
• 📦 Modular Design - Add only the providers you need

Analyze and predict daily productivity using SQL, machine learning, and psychology. This project combines behavioral data, circadian rhythm analysis, and ElasticNet regression to model focus, stress, and performance, transforming work patterns into actionable insights.

• SQL feature engineering deriving psychology-informed signals (circadian alignment, Yerkes–Dodson arousal, break quality, meeting load, distraction penalty, health score)
• ElasticNet regression baseline with L1/L2 regularization for interpretable coefficients

Predict the profitability of potential coffee shop locations using SQL and Python. Combines data engineering with feature-rich regression modeling, visual analytics, and business insights to support data-driven site selection and retail decision-making.

• SQLite feature store built from CSV inputs
• SQL feature engineering through reusable views, so training and candidate sites are transformed identically (no train/serve skew)

Analyze employee performance and productivity using SQL and Python. Build HR dashboards to evaluate departmental KPIs, efficiency trends, and workload balance. Generates actionable insights through data visualization and KPI aggregation for business decision-making.

• SQL views (src/queries.sql) for department, employee, and daily-level KPI aggregation
• Data-quality validation before load: null checks, rating range, absences domain, non-negative counts

Detect and classify fraudulent transactions using SQL and Python. Generate behavioral features with SQLite, train a Logistic Regression model, and evaluate performance with AUC, precision, recall, and ROC analysis. A complete supervised fraud detection workflow.

• SQL (SQLite) window-function feature engineering for per-user and per-day transaction statistics
• Point-in-time features: every aggregate uses ROWS BETWEEN UNBOUNDED PRECEDING AND 1 PRECEDING, so a transaction never sees its own amount or anything in the future

Detect suspicious financial transactions using SQL and Python. Build user-level behavioral features in SQLite, apply Isolation Forest for anomaly detection, and visualize high-risk patterns. Demonstrates unsupervised fraud analytics and SQL-driven data science workflow.

• SQL-first feature engineering, user-level and daily aggregates computed as SQLite views, not in Python
• Quote-aware SQL statement splitting so multi-statement .sql files (including string literals containing ;) are parsed correctly

Flexible dynamic admin panel for Ktor

• Automatic admin panel generation from your entities
• Support for Exposed, Hibernate, and MongoDB

Polytube is an analytics tool that records gameplay sessions for playtesting and debugging. It uses GPU duplication for high performance and minimal impact on system resources, and can automatically upload recordings to the cloud when valid credentials are provided.

• Add an option to disable wiping out old sessions.
• A Stop() function to stop the recording manually.

An open-source, feature rich & extensible url-shortener + analytics written in Python :cookie:

• Customized short URL's(ex: pygy.co/pygmy)
• Support to create auto expiry URL after some time.