CSV to JSON Converter

CSV to JSON Converter

Turn a raw CSV export into structured JSON rows, then write a clean CSV back out. Both steps use the Converter node, so there is no Python to write and no LLM in the loop. The parsing is deterministic, which means the same input always produces the same output.

What this workflow does

1. rawCsv holds a messy export: padded header names, padded cell values, and a customer name that contains a comma inside quotes
2. parseCsv runs csvToJson and returns an array of row objects, keyed by the header
3. rebuildCsv runs jsonToCsv over those rows and uses an explicit column order to reorder and drop columns
4. conversionResult returns both the parsed rows and the cleaned CSV text

Why the Converter node

Splitting CSV on commas breaks the moment a field contains a comma, a quote, or a newline. The Converter node follows RFC 4180, so "Grace Hopper, PhD" stays one value instead of becoming two. It also strips a leading UTF-8 BOM, which is what makes Excel exports show up as \ufeffheader in other tools.

Things worth knowing

• trimValues is on by default and strips whitespace from header names and cell values, including inside quoted fields. Turn it off when the padding is real data.
• hasHeader off gives you arrays of cell values instead of objects.
• converterColumns on the jsonToCsv side sets the exact column order. Columns you leave out are dropped, so it doubles as a column filter.
• Set delimiter to \t to read or write tab-separated files.

Use cases

• Normalizing a vendor or CRM export before it reaches a database node
• Feeding parsed rows into a Loop node to process records one at a time
• Reordering and trimming columns before handing a file to another team

Setup

No credentials needed. Paste your own CSV into rawCsv, run the workflow, and adjust converterColumns on rebuildCsv to match the columns you want to keep.