Lucky Parmar

July 2026 - Aug 2026

Short Project Description – Airbnb Data Analysis Airbnb Data Analysis is a data analytics project developed to analyze Airbnb listings, pricing, availability, customer reviews, and booking trends. The project uses Python, Pandas, NumPy, Matplotlib, Seaborn, and SQL to clean, process, analyze, and visualize data. The analysis helps identify pricing patterns, popular locations, room-type trends, customer preferences, and factors affecting listing performance. Lucky's Role During Internship Collecting and understanding Airbnb datasets Cleaning and preprocessing data Handling missing and duplicate values Performing exploratory data analysis (EDA) Analyzing pricing and availability trends Analyzing popular locations and room types Creating data visualizations and dashboards Using SQL for data extraction and analysis Identifying trends and meaningful business insights Preparing analytical reports and presentations Documenting findings and recommendations Suggested Project Modules for the Internship Report Phase 1: Requirement Analysis & Problem Definition Phase 2: Dataset Collection & Data Understanding Phase 3: Data Cleaning & Preprocessing Phase 4: Exploratory Data Analysis Phase 5: Pricing & Availability Analysis Phase 6: Location & Room-Type Analysis Phase 7: Data Visualization & Dashboard Development Phase 8: SQL-Based Data Analysis Phase 9: Insights & Business Recommendations Phase 10: Final Report & Presentation