Data Science

@datascience · Data & AI · curated by Rowland Kuru

Cleaning, analyzing, and communicating data with Python or R.

16 picks 10 free 13 providers 1 new this week Updated Sep 27

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Python for Data Analysis is written by Wes McKinney, the creator of pandas, and it's free to read online in its third edition. It teaches the tools you'll use every single day — NumPy arrays, pandas DataFrames, grouping, reshaping, time series, and basic plotting — with realistic examples rather than toy ones. Read it alongside a Jupyter notebook and retype the examples on a dataset you care about. It's not a statistics book, so pair it with the Statistics feed once you're comfortable.

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How the levels work here

Beginner · 8Loading, cleaning, summarizing, and charting data. Choose Python or R and stick with it for now.
Intermediate · 5Full analysis projects, communicating results, and the statistics that keep conclusions honest.
Advanced · 3Causal inference, experimentation, and the data engineering that feeds everything else.

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Coursera · DataTalks.Club · edX · freeCodeCamp (BSD 3-Clause) · Jake VanderPlas · Kaggle · Kohavi, Tang & Xu · R4DS Online Learning Community · Scott Cunningham · Storytelling with Data · Udemy · Wes McKinney · Wickham, Çetinkaya-Rundel & Grolemund

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