
A Survey Export With Hundreds of Columns Made Usable
A survey CSV has one column per question, 300 wide. Unpivot it to long form with DuckDB, drop blanks, name the questions and check the answer count.
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A survey CSV has one column per question, 300 wide. Unpivot it to long form with DuckDB, drop blanks, name the questions and check the answer count.

Statistical CSVs put flags in value cells: 1,204,300 (p), 5.3 e, and dots for missing. Split number from flag, keep both and check against the stated total.

A log export has quotes inside quoted fields without doubling them. See what Python and DuckDB return, which setting reads them right and how to prove it.

A price list CSV has title lines, a header on row 4, category names written once per group and a footer. Skip, forward fill, filter and check the item count.

An analytics CSV writes numbers as text: 12,430, 42.5%, $1,204.50, (4.1%) and dashes. Convert them with one macro and prove nothing is left unparsed.

A CRM export has notes with line breaks inside quoted fields, so line counts and grep mislead. Parse by records, then flatten the breaks or keep them.

A product export writes names with commas and no quotes, so rows have 6 fields, not 4. Rejoin the middle fields from the good ends and verify every row.

A statement mixes 2026-03-04 and 05/03/2026 in one column. Classify each row, prove the slash order from the data, convert, and check the dates are in order.

Store uploaded Excel files and their parsed rows in PostgreSQL: keep the original, stage, track errors, dedupe by hash and link rows to uploads.

Import XML into PostgreSQL with xmltable: XPath row and column paths, namespaces, attributes, nested elements, large files and validation of a feed.

Choose an Excel chart type from the shape of your query result: line, column, bar, stacked, scatter, histogram or table, with rules and the mistakes to avoid.

Build clear Excel charts from database data: shape the query, pick the chart, keep ranges live, avoid misleading axes, add sparklines, export images.
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