An interactive Streamlit web application showcasing a collection of data analysis and visualization scripts built with pandas and matplotlib. The app displays each script alongside its live output in a two-column layout, with category filtering to navigate between demos.
The project demonstrates data wrangling with pandas, including reading and cleaning CSV data, boolean filtering, multi-column GroupBy operations, aggregation with mean, standard deviation, and count, and quantile-based binning with pd.qcut. Visualization work spans scatter plots, histograms, bar charts, horizontal bar charts, and 3D plots using matplotlib’s mpl_toolkits.mplot3d extension, all rendered with a consistent dark theme.
Real-world data is used throughout, including a mall customer dataset analyzed by gender and age to compare income distributions, and a word frequency dataset derived from the novel Great Expectations visualized as both a top-50 frequency chart and a word length distribution.
The gallery is deployed on Streamlit Community Cloud and built entirely with Python, pandas, NumPy, matplotlib, and Streamlit.
Technologies used: Python, Pandas, NumPy, Matplotlib, Streamlit, mpl_toolkits