{"repo":"SaurabhSSB/medical-expense-analysis","free":true,"listed":false,"github":"https://github.com/SaurabhSSB/medical-expense-analysis","clone":"git clone https://github.com/SaurabhSSB/medical-expense-analysis.git","description":"EDA on medical insurance data using Python and R to explore how age, BMI, smoking, and other factors influence claim amounts and health risk profiles.","language":"Jupyter Notebook","stars":12,"topics":["bmi","data-analysis","data-visualization","diabetes","eda","healthcare-analytics","healthcare-insights","insurance","matplotlib","pandas"],"license":"MIT","category":"analytics","readme_excerpt":"🩺 Medical Expense Analysis This repository contains an exploratory data analysis (EDA) of a medical insurance dataset. The goal is to investigate how various demographic and health-related factors such as age, BMI, smoking habits, gender, and diabetes status influence the insurance claim amounts. This project includes both Python and R-based analysis , enabling cross-platform exploration and reproducibility of results using tools like Jupyter Notebooks and R Markdown. --- 📂 Files Included - medical expenses.csv – Cleaned dataset used for analysis - 1 data preprocessing.ipynb – Handling missing values and outliers (Python) - 2 eda.ipynb – Detailed visual EDA with insights (Python) - Insurance EDA.py – Python script version of the analysis - insurance data.docx – Summary, recommendations, and discussion questions - medica expense.Rmd & medica expense.html – R Markdown notebook and rendered HTML output for EDA using ggplot2 and dplyr --- 📊 Dataset Overview The dataset includes the following columns: - age : Age of the policyholder - gender : Male/Female - bmi : Body Mass Index - bloodpressure : Blood pressure level - diabetic : Yes/No - children : Number of children covered by insurance - smoker : Smoking status - region : Residential region - claim : Insurance claim amount --- 🔍 Analysis Highlights - Age & Claim : Older individuals tend to have higher claims. - BMI & Smoking : Smokers and people with higher BMI incur higher medical expenses. - Regional Trends : Southeast re","default_branch":null,"files":null,"tree":[],"storefront":"/r/SaurabhSSB","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/SaurabhSSB/medical-expense-analysis/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."}