This repository contains data analysis and financial data projects developed using Python. The focus is on extracting, analyzing, and visualizing real-world datasets to generate insights and support decision-making.
- Analyzed housing dataset (King County, USA)
- Performed data cleaning and exploratory data analysis (EDA)
- Identified key factors influencing housing prices
- Visualized relationships between property features and price
- Analyzed factors affecting insurance costs
- Performed data preprocessing and feature analysis
- Explored relationships between variables and cost drivers
- Built insights into key determinants of insurance pricing
- Extracted financial time-series data using yFinance API
- Processed and structured stock price data
- Prepared data for analysis and visualization
- Collected financial data using web scraping techniques
- Parsed and cleaned raw HTML data
- Structured data for further analysis
- Python
- Pandas
- NumPy
- Matplotlib / Seaborn
- yFinance
- BeautifulSoup
- Data cleaning and preprocessing
- Exploratory data analysis (EDA)
- Data visualization
- Financial data extraction
- Web scraping
- Time-series data handling
These projects demonstrate my ability to work with real-world datasets, apply data analysis techniques, and extract meaningful insights using Python.