A curated list of sites, docs, and guides I regularly use for data analysis and data science.
Official docs for data wrangling in Python: indexing, joins, groupby, time series, IO, and more.
Machine learning in Python: model APIs, pipelines, preprocessing, metrics, examples, and tutorials.
Plotting library docs including gallery examples for quick visualization patterns.
Guides for DAX, Power Query (M), data modeling, admin, and deployment best practices.
Tutorials, training paths, and sample dashboards to level up Tableau skills.
Datasets, notebooks, and competitions—great for practice, examples, and exploration.
Core numerical computing in Python: arrays, broadcasting, linear algebra, random, and performance tips.
Community articles on analytics, ML, visualization, and practical case studies.
Have a question or a project in mind? Drop me a message — I’m always happy to connect and chat about data, analytics, or new ideas.