{"repo":"Jeet-Lohar-29/Data_Analysis_EDA_Process","free":true,"listed":false,"github":"https://github.com/Jeet-Lohar-29/Data_Analysis_EDA_Process","clone":"git clone https://github.com/Jeet-Lohar-29/Data_Analysis_EDA_Process.git","description":"Comprehensive exploratory data analysis project using Python, Pandas & Seaborn to extract actionable insights from real-world datasets with advanced visualization and statistical interpretation.","language":"Python","stars":12,"topics":["data-analysis","data-visualization","eda","exploratory-data-analysis","matplotlib","numpy","pandas","python","seaborn"],"license":null,"category":"analytics","readme_excerpt":"🚗 Exploratory Data Analysis on Car Details Dataset 📊 Data-Driven Insights into Automotive Market Trends --- 📌 Project Overview This project performs a comprehensive Exploratory Data Analysis (EDA) on a car details dataset to uncover patterns, trends, and actionable insights related to automotive specifications and customer preferences. The analysis focuses on understanding: Market dominance of car brands Vehicle type distribution Fuel efficiency comparisons Production trends over time Engine type and drivetrain preferences Ground clearance comparison across brands 🔗 Dataset Source: https://carapi.app/features/vehicle-csv-download --- 🎯 Objectives 🔍 Identify the most common car brands and vehicle types ⛽ Compare fuel efficiency across segments (SUVs, Sedans, etc.) 🏭 Analyze production trends by brand over the years 🌱 Explore preferred fuel/engine types (Gas, Hybrid, etc.) 🚗 Examine preferred drivetrain modes (FWD, AWD, RWD) 🏔️ Compare highest ground clearance provided by brands --- 🛠️ Tools & Technologies 👨‍💻 Programming Language Python 3.x 📚 Libraries Used 📊 Pandas – Data cleaning & manipulation 🧮 NumPy – Numerical computations 🎨 Matplotlib – Core visualizations 📈 Seaborn – Statistical & advanced plots 🤖 Scikit-learn – Basic preprocessing & analysis --- 🧹 Data Preprocessing Handling missing values Data type corrections Feature selection & filtering Outlier inspection Structured formatting for analysis This ensures accurate, reliable, and interpretable visu","default_branch":null,"files":null,"tree":[],"storefront":"/r/Jeet-Lohar-29","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/Jeet-Lohar-29/Data_Analysis_EDA_Process/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."}