From raw CSV to trustworthy table
Follow the import-tidy-transform-check sequence for a raw CSV.
The fork Dev gets a vendor CSV at 6:10 p.m. with commas in amounts, two header rows, and “N/A” mixed with blanks. The stakeholder says, “Just give me the total by market.” The choice changes what future-you can verify. R for Data Science workflow The R for Data Science workflow separates import, tidy, transform, visualize, model, and communicate because each stage has a different failure mode. Import is about parsing bytes into columns. Tidying is about shape. Transformation is about variables and summaries. Checking is about whether the result still matches reality. The mechanism is staged uncertainty reduction: you make…
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