{"id":26054794,"url":"https://github.com/tolumie/exploratory-data-analytics-projects","last_synced_at":"2026-04-11T11:42:33.554Z","repository":{"id":281221912,"uuid":"944606198","full_name":"Tolumie/Exploratory-Data-Analytics-Projects","owner":"Tolumie","description":" Exploratory Data Analytics – A collection of projects covering data exploration, feature engineering, hypothesis testing, and predictive modeling across diverse datasets, including insurance, real estate, laptops, cars, COVID-19, and the Olympics.","archived":false,"fork":false,"pushed_at":"2025-03-07T17:00:47.000Z","size":0,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-07T17:33:26.514Z","etag":null,"topics":["data-analysis","data-visualization","data-wrangling","exploratory-data-analysis-eda","feature-engineering","hypothesis-testing","machine-learning","matplotlib","numpy","pandas","predictive-modeling","python","seaborn","statistical-analysis"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Tolumie.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2025-03-07T16:38:58.000Z","updated_at":"2025-03-07T17:11:53.000Z","dependencies_parsed_at":"2025-03-07T17:43:33.268Z","dependency_job_id":null,"html_url":"https://github.com/Tolumie/Exploratory-Data-Analytics-Projects","commit_stats":null,"previous_names":["tolumie/exploratory-data-analytics-projects"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Tolumie%2FExploratory-Data-Analytics-Projects","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Tolumie%2FExploratory-Data-Analytics-Projects/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Tolumie%2FExploratory-Data-Analytics-Projects/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Tolumie%2FExploratory-Data-Analytics-Projects/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Tolumie","download_url":"https://codeload.github.com/Tolumie/Exploratory-Data-Analytics-Projects/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":242532349,"owners_count":20144726,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["data-analysis","data-visualization","data-wrangling","exploratory-data-analysis-eda","feature-engineering","hypothesis-testing","machine-learning","matplotlib","numpy","pandas","predictive-modeling","python","seaborn","statistical-analysis"],"created_at":"2025-03-08T09:59:55.906Z","updated_at":"2026-04-11T11:42:33.486Z","avatar_url":"https://github.com/Tolumie.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# 📊 Exploratory Data Analytics  \n\n## 📌 Overview  \nThis repository contains a collection of **data analytics projects** that focus on **data exploration, feature engineering, hypothesis testing, and predictive modeling**. The datasets cover various domains, including **insurance costs, laptop and used car pricing, house sales, COVID-19 trends, and the Olympic Games**.  \n\n## 📁 Project Descriptions  \n\n### 1️⃣ **Insurance Cost Analysis**  \n- Investigates **insurance cost drivers** using statistical methods.  \n- Explores relationships between **age, BMI, smoking status, and charges**.  \n\n### 2️⃣ **Laptop Pricing Analysis**  \n- Examines factors affecting **laptop prices**, including **brand, specifications, and market demand**.  \n- Builds **predictive models** for price estimation.  \n\n### 3️⃣ **Used Car Pricing Analysis**  \n- Uses **EDA and machine learning** to understand used car pricing trends.  \n- Factors include **mileage, manufacturing year, and brand perception**.  \n\n### 4️⃣ **House Sales in King County (USA)**  \n- Analyzes **real estate trends**, identifying key features influencing **house prices**.  \n- Uses **regression modeling** for price prediction.  \n\n### 5️⃣ **Exploratory Data Analysis of COVID-19 in India**  \n- Examines the **spread, mortality, and recovery trends** of COVID-19 in India.  \n- Uses **time series analysis** to visualize case growth.  \n\n### 6️⃣ **Olympic Games Data Analysis**  \n- Investigates **medal distributions, country participation trends, and athlete performances** over time.  \n\n### 7️⃣ **Machine Learning \u0026 Statistical Analysis Labs**  \n- **Classification with Python:** Covers **logistic regression, decision trees, and SVM**.  \n- **Feature Engineering Lab:** Focuses on **data transformation and new feature creation**.  \n- **Hypothesis Testing Lab:** Applies **z-tests, t-tests, and chi-square tests** to validate assumptions.  \n\n## 🛠️ Key Techniques  \n✔ **Data Wrangling \u0026 Cleaning** – Handling missing values, outlier detection, and feature extraction.  \n✔ **Exploratory Data Analysis (EDA)** – Uncovering patterns and insights through **visualization and statistics**.  \n✔ **Feature Engineering** – Creating new features to improve model accuracy.  \n✔ **Machine Learning Models** – Regression and classification models for predictive analysis.  \n✔ **Hypothesis Testing** – Using **statistical tests to validate findings**.  \n\n## 📂 Files in This Repository  \n- **Data Wrangling Notebooks** – Cleaning and preprocessing datasets.  \n- **EDA Notebooks** – Exploring data distributions and visualizing trends.  \n- **Feature Engineering \u0026 Hypothesis Testing Notebooks** – Transforming data and conducting statistical analysis.  \n- **Machine Learning Notebooks** – Developing and evaluating predictive models.  \n\n## 🚀 Future Enhancements  \n🔹 Integrating **advanced machine learning models** for better predictions.  \n🔹 Expanding **time series forecasting** for financial and pricing trends.  \n🔹 Incorporating **more real-world datasets** for deeper insights.  \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftolumie%2Fexploratory-data-analytics-projects","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftolumie%2Fexploratory-data-analytics-projects","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftolumie%2Fexploratory-data-analytics-projects/lists"}