Tidy a Wide Export
Reshape a wide spreadsheet export into tidy columns before calculating trends in pandas.
before-after step-ladder common-trap-callout The export has one row per sales rep and one revenue column per month. Priya needs a reliable region-month trend. Apply tidy data before aggregation: keep identifiers as identifier columns, move repeated measure headers into a variable column, and store the measured amount in one value column. The tempting shortcut is to sum Jan, Feb, Mar, and Apr separately. That looks fast today, but every new month adds code, and every manual chart update becomes another place for drift. Before Columns: region, rep, Jan, Feb, Mar, Apr. The month variable is hidden in column names. After Columns:…
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