JSON to CSV Conversion: Tips and Best Practices

Flattening Nested Objects

CSV is flat by design — every value lives in a single cell. JSON is often deeply nested. The key challenge in conversion is flattening nested structures into columns. Dot notation is the standard approach:

// Input JSON
[
  { "name": "Alice", "address": { "city": "NYC", "zip": "10001" } }
]

// Flattened CSV columns:
// name | address.city | address.zip
// Alice| NYC           | 10001

Arrays can be handled by joining values with a separator (e.g., skills.join(', ')) or by creating numbered columns (skills.0, skills.1). The right choice depends on whether you need to query individual array elements in the spreadsheet.

Handling Inconsistent Keys

Real-world JSON often has records with different keys. Record A might have email while Record B has mail. A good converter collects all unique keys across all records and fills missing values with empty cells:

[
  { "name": "Alice", "email": "a@test.com" },
  { "name": "Bob",   "phone": "555-1234" }
]

// CSV with all columns:
// name  | email      | phone
// Alice | a@test.com |
// Bob   |            | 555-1234

Choosing the Right Delimiter

The default delimiter is a comma, but it breaks when your data contains commas (common in addresses, descriptions). Alternatives:

If values contain the delimiter, wrap them in double quotes. If values contain quotes, escape them by doubling: "He said ""hello""".

Large Datasets & Excel Compatibility

Excel has a 1,048,576 row limit and 16,384 column limit. For JSON arrays larger than ~1 million records, split into multiple CSV files or use a database import instead.

Also watch for encoding issues: Excel on Windows expects UTF-8 with BOM for proper non-ASCII character display. Add a BOM (\uFEFF) at the start of the CSV if your data contains special characters.