📊 Explore key data visualization techniques in hospitality using Matplotlib and Seaborn through interactive Jupyter notebooks for insightful analysis.

📝 Explore Jupyter notebooks and reusable code to master data science workflows and enhance your skills effectively.

Notebook para interação com dados do Strava, via API.

33 interactive analytic notebooks covering economics, social sciences, and data science. From fundamentals to advanced causal inference with hands-on Python implementations.

Data Analytics Platform

Advanced IPL Cricket Performance Analyzer (2015–2023) with player rankings, all-rounders, Orange/Purple Cap history, and interactive visualizations. Built with Jupyter-Notebook, Python, Pandas, and Streamlit.

Global AI & Data Science Salaries (2020–2025) — Multi-country, multi-role synthetic dataset with full EDA, code notebooks, visualizations, and benchmarking insights.

A hands-on collection of Jupyter notebooks exploring Matplotlib — from basic plots to advanced data visualizations. Covers line charts, bar graphs, scatter plots, subplots, annotations, styling, and real-world visualization techniques for data analysis and storytelling.

An interactive Q&A system that extracts actionable insights from agricultural data (1997–2014). It combines efficient EDA, a rule-based query engine, and a Gradio interface to answer questions on crop yields, rainfall, and production. Built in Jupyter Notebook with a modular, extensible pipeline.

A comprehensive collection of Jupyter notebooks exploring Pandas, from Series and DataFrames to data cleaning, aggregation, merging, and visualization. A complete hands-on guide for mastering data manipulation and analysis with Python.

A Python + SQLite music database with reusable exports, analytics notebook, and a clean, portfolio-ready structure. Built for data engineers, DJs, and Python learners.

Tellery lets you build metrics using SQL and bring them to your team. As easy as using a document. As powerful as a data modeling tool.

Jupyter Notebook analyzing GitHub repository metadata using Python, Parquet, Pandas, and DuckDB

Interactive FastF1 Colab notebook that analyzes Formula 1 undercut/overcut strategies, tyre degradation, and team pace.

Python package for exploratory data analysis providing statistical summaries, data quality checks, outlier detection and batch visualization functions. Supports Jupyter notebooks and terminal environments.

I created some notebooks about different concepts of financial engineering

PM-friendly toolkit for funnels, churn, and A/B testing. Includes sample size calculator, funnel dataset, analysis notebook, and visualizations.

A/B test simulator: binomial conversions, CTR lift, two-proportion z-test, and quick power/MDE exploration in a single Colab notebook.

Fraud Detection in E-Commerce (SQL)

Modular data analysis toolkit for ETL, QA, and reporting in Jupyter notebooks or CLI workflows.