This repository highlights applied Python work across web scraping, Excel automation, API integration, and data analysis.
It demonstrates my ability to collect real-world data, transform it, and build reproducible workflows that generate insights.
- bible/ — Scrapes Bible text into structured data for downstream NLP or analysis.
- covid/ — Parses public health tables into clean CSVs for reporting.
- movies/ — Collects titles, ratings, and genres for exploratory data analysis.
- tradingview/ — Pulls market price data for monitoring and trend analysis.
- excel-automation/ — Moves data between Excel and Python: cleaning, transformation, and export.
Demonstrates ETL (Extract, Transform, Load) workflows.
- api-calls/ — Demonstrates API integration and data retrieval.
fbi.py: Fetches data from FBI’s public crime API.chucknorris.py: Retrieves random jokes via the Chuck Norris API.
These projects showcase how to interact with REST APIs and handle JSON responses in Python.
- nfl-analysis/ — Data analysis project using a raw NFL players dataset (
NFL-players.csv).- Cleaned and prepared the dataset using pandas.
- Conducted exploratory data analysis (EDA) to highlight player performance trends.
- Demonstrates structured analysis of real-world sports data with reproducible Python code.
- misc/ — Additional scripts and prototypes, including general data processing examples.
- Clone this repo or download a project folder.
- Install dependencies: pip install -r requirements.txt
- Navigate to the desired folder and run:
- Outputs (CSV/Excel/JSON) are saved locally as defined in each script.
- Python 3.x
- Libraries:
pandas,requests,beautifulsoup4,lxml,openpyxl
- Web scraping projects respect site terms of service and are for educational/portfolio use.
- The NFL project highlights data cleaning and analysis workflows without machine learning.
- API projects demonstrate calling REST endpoints, parsing JSON, and integrating external data.