{"id":30462403,"url":"https://github.com/iama02/vet-medicine-analysis","last_synced_at":"2026-05-06T03:31:58.268Z","repository":{"id":310535035,"uuid":"1040244418","full_name":"iama02/vet-medicine-analysis","owner":"iama02","description":"Analysis of 50,000+ veterinary medicine records with Pandas and NumPy, highlighting dosage forms, manufacturers, indications, and shelf life trends.","archived":false,"fork":false,"pushed_at":"2025-08-18T17:23:08.000Z","size":1172,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-08-18T19:24:39.577Z","etag":null,"topics":["numpy","pandas","python"],"latest_commit_sha":null,"homepage":"","language":"Jupyter 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\u0026 NumPy).\n\nThe project demonstrates skills in data cleaning, feature engineering, and preparation for advanced visualization, making it an excellent resource for both data enthusiasts and professionals in the veterinary/healthcare domain.\n\n🚀 Key Analyses\n\n🔬 Data Cleaning \u0026 Transformation – handled missing values, standardized formats\n\n💊 Summarization – by dosage form, manufacturer, and indication\n\n🗂️ Feature Engineering – extracted numeric strength (mg) and calculated shelf life (days)\n\n📊 Data Preparation – structured dataset for visualization and trend analysis\n\n📁 Dataset Features\n\nName – Medicine name\n\nCategory – Type of medicine (e.g., antibiotic, antiviral)\n\nDosage Form – Cream, injection, ointment, etc.\n\nStrength – Dosage strength (mg)\n\nManufacturer – Company producing the medicine\n\nIndication – Medical use case (infection, wound, etc.)\n\nClassification – Prescription or over-the-counter (OTC)\n\nManufactured Date – Date of production\n\nExpiry Date – Expiration date\n\n🛠️ Getting Started\n1️⃣ Clone the repository\ngit clone https://github.com/iama02/vet-medicine-analysis.git\n\n2️⃣ Open the notebook\n\nLaunch vet_med.ipynb in JupyterLab or VS Code\n\n3️⃣ Install dependencies\npip install pandas numpy\n\n🔮 Next Steps\n\n📊 Add visualizations using Matplotlib \u0026 Seaborn\n\n📈 Explore deeper expiry trends, strength variations, and manufacturer distribution\n\n🧠 Extend analysis with predictive modeling (expiry prediction, demand forecasting)\n\n📄 License\n\nThis project is licensed under the MIT License.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fiama02%2Fvet-medicine-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fiama02%2Fvet-medicine-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fiama02%2Fvet-medicine-analysis/lists"}