R Programming / Language and data foundations

R Programming β€” Language and data foundations

Objects, vectors, indexing, structured data, functions, and typed text.

6 lessons Β· No account required

What you will learn

  • Inspect object types and shapes.
  • Preserve identity and missingness in data transformations.
  • Define explicit function and import contracts.

  1. Scripts, objects, and session boundaries

    Build a reproducible base-R calculation whose inputs and assumptions are visible in one script.

    Start learning

  2. Vectors, types, coercion, and recycling

    Make R’s vector rules explicit so convenient arithmetic does not silently change data meaning.

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  3. Indexing, missingness, and shape preservation

    Select the intended observations without losing dimensions or converting unknown conditions into accidental rows.

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  4. Lists, data frames, and factors

    Choose a structure that preserves column meaning, observation grain, and category semantics.

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  5. Functions, lexical scope, and validation

    Make arguments, captured state, return values, and failure conditions part of a reusable function contract.

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  6. Text import, dates, and data contracts

    Turn supplied text into typed observations without hiding missingness, identifiers, or time interpretation.

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