Python for R Data Scientists

Interactive browser-based tutorial for R users learning Python. No installation required.

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What's Covered

93 exercises across 10 modules:

1. Fundamentals - 0-indexing, slicing, references
2. Data Structures - lists, dicts, sets
3. Control Flow - loops, comprehensions, exceptions
4. Functions - args/kwargs, scope, lambdas
5. NumPy - arrays, broadcasting
6. Pandas - DataFrames (tidyverse equivalent)
7. Polars - modern DataFrame library
8. Stats - statsmodels, scipy.stats
9. Plotly - interactive visualization
10. Capstone - end-to-end project

R Gotchas You'll Learn

• x[0] not x[1] - Python is 0-indexed
• x[1:4] excludes index 4
• y = x creates a reference, not a copy
• def f(lst=[]) - mutable default trap
• Pandas SettingWithCopyWarning
• statsmodels requires explicit C() for categoricals