Graph visualization of big messy data

Synthetic dirty data generator

TablePilot：本地优先的复杂表格智能分析工作台 | Local-first messy table analysis workbench for repair plans, insights, and explainable reports

See how a model comes apart when repeatedly photogrammetry'd

Script for classifying your messy directories

Package for entity matching, standardization, and visualization using embeddings from large language models.

A Python tool that transforms clean datasets into realistic messy datasets for testing data cleaning processes

[READ-ONLY MIRROR] A Python implementation for Hadley Wickham's Tidy Data paper

Statistical Programming in SAS

Configurable messy CSV generator for testing data pipelines and ETL processes. Three mess levels, 20+ field types, SQL/XSS injection simulation. No install required.

Cleans and analyses 28,000+ self-reported salaries from the Ask A Manager 2021 Survey. Covers industry pay rankings, experience-salary growth, country comparisons, gender pay gap, and race-education correlations. Built with Python, Pandas, Seaborn, and Matplotlib. 

Robust CSV dialect detection methodology for Python that outperforms existing state of the art solutions by 8.35% in terms of their F1 scores, using only built-in Python modules.

😺 The easiest way to structure unstructured data

Use generator expressions, formatting operations, and cleaning methods to prepare data for analysis.

A Python data cleaning project demonstrating advanced Pandas techniques, regex, and data standardization on a messy HR dataset.

An end-to-end Python data cleaning pipeline using Pandas to resolve corrupt, missing, and inconsistent transactional logs in a Café Sales Dataset.

To get a hands-on experience with real-life messy data, I chose to work with food and nutrient data available on FoodData Central. I wanted to compare nutrients across different types of foods available in the US market.