An interactive Streamlit web application showcasing a collection of Python data analysis and visualization scripts. The app presents each script side-by-side with its live output, allowing visitors to view the source code and see the rendered result in real time.
The project demonstrates proficiency in NumPy for numerical computing, including matrix construction from raw string data using regex parsing, axis-based aggregation, and matrix multiplication via np.matmul to compute derived values across datasets. Visualization work covers a range of matplotlib chart types — line plots, bar charts, pie charts, and multi-panel subplot grids — with consistent custom theming applied across all figures.
A text processing pipeline is also featured, reading a word frequency dataset, aggregating counts by word length using Python’s collections.defaultdict, and writing the results to CSV for downstream plotting with np.loadtxt.
The gallery is deployed on Streamlit Community Cloud and built entirely with Python, NumPy, matplotlib, and Streamlit.
Technologies used: Python, NumPy, Matplotlib, Streamlit, Regex, Collections