{"id":20245200,"url":"https://github.com/saksham-jain177/data-analysis","last_synced_at":"2026-05-01T22:35:25.029Z","repository":{"id":186850253,"uuid":"675869831","full_name":"saksham-jain177/Data-Analysis","owner":"saksham-jain177","description":"A collection of data analysis and machine learning projects across various datasets. Explore predictive modeling, data visualization, and insights from real-world data. 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This repository contains a series of notebooks demonstrating different data analysis and machine learning tasks. Each project focuses on a unique dataset and problem statement, showcasing various analytical and predictive techniques.\n\n## Table of Contents\n\n1. [Swiggy Restaurants Data Analysis](#swiggy-restaurants-data-analysis)\n2. [GeeksforGeeks Data Analysis](#geeksforgeeks-data-analysis)\n3. [Cardekho Used Car Price Analysis](#cardekho-used-car-price-analysis)\n4. [Sonar Mine Prediction](#sonar-mine-prediction)\n5. [Big Mart Sales Prediction](#big-mart-sales-prediction)\n6. [California House Price Prediction](#california-house-price-prediction)\n7. [CarDekho Car Price EDA](#cardekho-car-price-eda)\n8. [Credit Card Fraud Detection](#credit-card-fraud-detection)\n9. [Customer Segmentation Using K-Means](#customer-segmentation-using-k-means)\n10. [Fake News Prediction](#fake-news-prediction)\n11. [Gold Price Prediction](#gold-price-prediction)\n12. [Heart Disease Prediction](#heart-disease-prediction)\n13. [House Prices: Advanced Regression Techniques](#house-prices-advanced-regression-techniques)\n14. [Loan Eligibility Prediction](#loan-eligibility-prediction)\n15. [Parkinson's Disease Detection](#parkinsons-disease-detection)\n16. [Spam Mail Prediction](#spam-mail-prediction)\n17. [Used Medical Insurance Prediction](#used-medical-insurance-prediction)\n\n## Swiggy Restaurants Data Analysis\n\n**Description:** This project involves analyzing restaurant data from the Swiggy food delivery platform. Key aspects include:\n\n- **Data Collection:** Access data on restaurant names, cuisines, ratings, reviews, delivery times, and locations.\n- **Data Cleansing and Preparation:** Clean and preprocess the data for analysis.\n- **Restaurant Performance Analysis:** Calculate average ratings, review counts, and identify high-performing restaurants.\n- **Cuisine and Menu Analysis:** Analyze cuisine distribution and popular menu items.\n\n## GeeksforGeeks Data Analysis\n\n**Description:** This project involves scraping and analyzing video data from the GeeksforGeeks YouTube channel.\n\n- **Data Gathering:** Use YouTube Data API to fetch video details such as titles, views, upload dates, and lengths.\n- **Data Processing and Analysis:** Calculate total views and lengths, identify popular topics, and analyze correlations.\n- **Visualization:** Use libraries like matplotlib to create visualizations of trends and patterns.\n\n## Cardekho Used Car Price Analysis\n\n**Description:** Analyze the used car dataset from Cardekho to uncover insights about factors influencing car prices.\n\n- **Data Gathering:** The dataset includes features like selling price, vehicle age, KM driven, engine size, fuel type, seller type, and transmission type.\n- **Data Cleaning and Preprocessing:** Handle missing values, remove duplicates, standardize text columns, and remove outliers.\n- **Exploratory Data Analysis (EDA):** Perform univariate, bivariate, and categorical analyses to identify key trends and insights.\n- **Visualization:** Use libraries like matplotlib and seaborn to create distribution plots, scatter plots, and correlation heatmaps.\n- **Insights and Findings:** Analyze the impact of various factors on car prices and provide recommendations based on the analysis.\n\n## Sonar Mine Prediction\n\n**Description:** Build a machine learning model to classify sonar signals as either mines (M) or rocks (R).\n\n- **Data Gathering:** The dataset includes sonar readings for mines and rocks.\n- **Data Cleaning and Preprocessing:** Verify and handle missing values and outliers.\n- **Exploratory Data Analysis (EDA):** Analyze summary statistics and class distribution.\n- **Model Building:** Create feature matrices, split data, and evaluate models such as Logistic Regression, SVC, Decision Tree, and Random Forest.\n- **Model Comparison:** Compare models based on accuracy and performance metrics.\n- **Insights and Findings:** Determine the best model for sonar signal classification based on accuracy.\n\n## Big Mart Sales Prediction\n\n**Description:** Predict sales for Big Mart using historical sales data.\n\n- **Data Gathering:** Use sales data from Big Mart to create predictive models.\n- **Data Cleaning and Preprocessing:** Handle missing values and preprocess data for modeling.\n- **Model Building:** Build and evaluate regression models to predict sales.\n\n## California House Price Prediction\n\n**Description:** Predict house prices in California using historical data.\n\n- **Data Gathering:** Use historical housing data from California.\n- **Data Cleaning and Preprocessing:** Clean and preprocess data for analysis.\n- **Model Building:** Develop regression models to predict house prices.\n\n## CarDekho Car Price EDA\n\n**Description:** Perform exploratory data analysis on CarDekho's car price dataset.\n\n- **Data Gathering:** Analyze features such as car price, model, and mileage.\n- **Exploratory Data Analysis (EDA):** Identify key trends and patterns in the dataset.\n\n## Credit Card Fraud Detection\n\n**Description:** Build a model to detect fraudulent credit card transactions.\n\n- **Data Gathering:** Use historical credit card transaction data.\n- **Model Building:** Develop and evaluate classification models to detect fraud.\n\n## Customer Segmentation Using K-Means\n\n**Description:** Segment customers into different groups using K-Means clustering.\n\n- **Data Gathering:** Use customer data for clustering.\n- **Model Building:** Apply K-Means clustering to segment customers.\n\n## Fake News Prediction\n\n**Description:** Predict whether a news article is fake or real.\n\n- **Data Gathering:** Use a dataset of news articles.\n- **Model Building:** Develop and evaluate classification models for fake news detection.\n\n## Gold Price Prediction\n\n**Description:** Predict gold prices using historical data.\n\n- **Data Gathering:** Use historical gold price data.\n- **Model Building:** Develop regression models to predict future gold prices.\n\n## Heart Disease Prediction\n\n**Description:** Predict the likelihood of heart disease based on patient data.\n\n- **Data Gathering:** Use health data related to heart disease.\n- **Model Building:** Develop classification models to predict heart disease risk.\n\n## House Prices: Advanced Regression Techniques\n\n**Description:** Use advanced regression techniques to predict house prices.\n\n- **Data Gathering:** Use historical housing data.\n- **Model Building:** Apply advanced regression techniques to improve predictions.\n\n## Loan Eligibility Prediction\n\n**Description:** Predict loan eligibility based on applicant data.\n\n- **Data Gathering:** Use applicant data to determine loan eligibility.\n- **Model Building:** Develop classification models to predict loan approval.\n\n## Parkinson's Disease Detection\n\n**Description:** Build a model to detect Parkinson's disease from patient data.\n\n- **Data Gathering:** Use health data related to Parkinson's disease.\n- **Model Building:** Develop and evaluate classification models for disease detection.\n\n## Spam Mail Prediction\n\n**Description:** Predict whether an email is spam or not.\n\n- **Data Gathering:** Use email data to classify spam and non-spam emails.\n- **Model Building:** Develop classification models to detect spam emails.\n\n## Used Medical Insurance Prediction\n\n**Description:** Predict the likelihood of medical insurance usage based on patient data.\n\n- **Data Gathering:** Use patient data to predict insurance usage.\n- **Model Building:** Develop classification models to predict medical insurance needs.\n\n## License\n\nThis project is licensed under the MIT License.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsaksham-jain177%2Fdata-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsaksham-jain177%2Fdata-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsaksham-jain177%2Fdata-analysis/lists"}