{"repo":"AmirhosseinHonardoust/Missing-Data-Doctor","free":true,"listed":false,"github":"https://github.com/AmirhosseinHonardoust/Missing-Data-Doctor","clone":"git clone https://github.com/AmirhosseinHonardoust/Missing-Data-Doctor.git","description":"Missing Data Doctor is a diagnostic and treatment toolkit for missing values in machine learning datasets. It profiles missingness patterns, visualizes gaps, applies multiple imputation strategies, and evaluates their impact on model performance. Includes automated plots, metrics, and a full HTML report.","language":"Python","stars":19,"topics":["automation","data-cleaning","data-pipelines","data-preprocessing","data-profiling","data-quality","data-reporting","data-science","data-visualization","eda"],"license":"MIT","category":"data-pipelines","readme_excerpt":"Missing Data Doctor A diagnostic & treatment suite for missing values in tabular machine learning datasets . Missing Data Doctor helps you: - Quantify how much data is missing and where - Visualize missingness patterns across features and rows - Impute missing values using multiple strategies - Evaluate how each imputation choice affects model performance - Report everything in a portable, self-contained HTML report It is designed as a practical data-science tool you can drop into real workflows or showcase as a professional project on GitHub. --- Project Structure Flat layout : all Python modules live directly under src/ (no package folders, no mdd ). --- Quickstart 1. Create and activate a virtual environment (Windows CMD) 2. Install dependencies If you don’t have requirements.txt , install manually: 3. Run the demo pipeline This command: Loads data/example with missing.csv Profiles missingness Generates plots Runs 3 imputation strategies Evaluates a model for each Writes a self-contained run folder with plots + JSON + HTML You’ll get: 4. Open the HTML report --- What the Example Dataset Looks Like data/example with missing.csv is a small synthetic dataset: Key properties: 10 rows with 5 columns: age , income , visits , score , target Missing values: income : 2 missing → 20% visits : 2 missing → 20% age : 1 missing → 10% score : 1 missing → 10% target : no missing target is a binary label: 0/1 (classification problem) This toy dataset is intentionally small so you can easil","default_branch":null,"files":null,"tree":[],"storefront":"/r/AmirhosseinHonardoust","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/AmirhosseinHonardoust/Missing-Data-Doctor/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}