Python
projects
Analysis, automation, and notebooks that turn raw files into insight.
These projects use Python to clean datasets, explore patterns, and turn raw files into insight. Typical tools include pandas and Jupyter notebooks.
Global stock companies project
This dataset provides comprehensive stock market data for some of the world's leading companies, including Apple, Microsoft, Nvidia, Google, Amazon, Saudi Aramco, Meta, Berkshire Hathaway, TSMC, and Eli Lilly. It covers various financial metrics such as opening and closing prices, trading volumes, and market capitalization.
The notebook looks at trends, relationships, and volatility across those companies so the story is in the data, not just the ticker list.
Loan dataset project
Python analysis of a loan dataset: cleaning, exploring, and shaping the file so patterns in applications and outcomes are easier to see. Typical steps include pandas profiling, handling missing values, and charts that support a credit or risk conversation.
Additional Python work
Further notebooks and scripts for analysis and practice. See the repository for the latest files.