Csv And Spreadsheet Data Conversion
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CSV to Excel: the easiest conversion method
Data conversion sits at the heart of most analytics workflows: an export from one system in CSV, the next system wants JSON, the analyst wants it in Excel, the engineer wants XML. This guide is the practical playbook for getting between formats without losing your data — and which of our free tools handles each conversion.
JSON to CSV for data analysis
Three options, each tractable:
XML to CSV step-by-step
The hidden gotcha most people hit: Excel auto-converts certain strings to dates or numbers. If you have a ZIP code column with leading zeros (“01234”), columns of trade IDs that look like numbers, or anything date-like, Excel will silently corrupt them. Always use Power Query (Data → From Text/CSV) for production data — it lets you lock column types before import.
Preserving file structure when converting formats
For deeply nested or hierarchical XML (3+ levels of nested elements with arrays inside arrays), CSV isn’t the right output format — you’ll get a wide sparse table. Convert to JSON first, then process with a real ETL tool.
Common pitfalls in data conversion
The general principle: lossy conversions are unidirectional. Once you go from a richer format to a flatter one (XML → CSV, JSON → CSV, DOCX → plain text), you can’t recover the original structure perfectly. Plan accordingly: