Data Analysis & Visualization Built with:

• Python for backend logic and data processing
• Pandas & NumPy for efficient data transformation
• Matplotlib & Seaborn for insightful visualizations
• Plotly & Dash for interactive dashboards
• Folium for Geospatial Mapping
• Web Scraping (BeautifulSoup, Requests)
• REST API Integration for Real-Time Data

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Overview

This repository contains data analysis projects, exploring datasets with statistical insights, visualizations, and interactive dashboards. The projects include EDA (Exploratory Data Analysis), feature engineering, geospatial analysis, and interactive reports.

Core Topics Covered:

• Data Cleaning & Preprocessing → Handling missing values, scaling, encoding
• Exploratory Data Analysis (EDA) → Summary statistics, correlation matrices, distribution plots
• Geospatial Analysis → Mapping locations using Folium
• Web Scraping → Collecting structured data from websites using BeautifulSoup
• REST API Integration → Extracting real-time data from public APIs
• Data Dashboards → Interactive charts using Dash & Plotly

Projects Included:

• Airline Performance
• Canada Immigration Analysis
• Car Price Analysis
• Chicago Data Portal
• Fuel Consumption
• House Price Analysis
• Insurance Cost Analysis

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Dependencies

pip install pandas numpy matplotlib seaborn plotly dash folium requests beautifulsoup4

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License

This repository is licensed under the MIT License.