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Parses CSV data into structured data. Use this when a value in your flow holds comma-separated text, such as an exported product list or a file dropped on an SFTP server, and you want to work with each row and column as data you can map and transform. By default the first row is read as column headers, and each following row becomes one item using those headers as field names.

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Fields

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Sample data

FieldValue
Delimiter,
Includes headerson
Input: 
sku,name,price
A1,Wool scarf,19.95
B2,Leather belt,29.50
Output: 
[
    { "sku": "A1", "name": "Wool scarf", "price": 19.95 },
    { "sku": "B2", "name": "Leather belt", "price": 29.5 }
]
Note that values that look like numbers come through as numbers, so 19.95 is a number rather than text.