How to Convert JSON to CSV for Excel and Google Sheets

Start with an array of objects

CSV is a flat table: rows and columns. The JSON shape that maps cleanly onto it is an array of objects, where each object becomes one row and its keys become the column headers. Before converting, make sure your data is in that form — if your API wraps the array in an envelope like { "data": [...] }, extract the inner array first.

[
  { "id": 1, "name": "Ada",   "active": true },
  { "id": 2, "name": "Linus", "active": false }
]

id,name,active
1,Ada,true
2,Linus,false

Flatten nested objects

Spreadsheets have no concept of nesting, so a nested object must be flattened into multiple columns. The common convention is dotted path notation: a field address.city becomes a column named address.city. A converter walks the object and produces one column per leaf value, so the table stays lossless even when the source is deeply nested.

{ "id": 1, "address": { "city": "London", "zip": "EC1" } }

// becomes:
// id,address.city,address.zip
// 1,London,EC1

Handle arrays inside rows

Arrays are the trickiest part of flattening because a single cell cannot hold a list natively. You have a few options depending on the data. Arrays of simple values — like tags — can be joined into one cell with a separator such as a semicolon or pipe. Arrays of objects are usually kept as a JSON string in one cell for later processing, or, when each item deserves its own row, expanded so the parent fields repeat. Decide based on how the spreadsheet will be used: joining is friendlier for humans, while a JSON string preserves structure for re-import.

{ "id": 1, "tags": ["red", "blue"] }

// joined:  id,tags        -> 1,"red;blue"
// json:    id,tags        -> 1,"[\"red\",\"blue\"]"

Quoting, commas, and special characters

CSV has its own escaping rules, and ignoring them is the most common cause of a mangled import. Any value that contains the delimiter, a double quote, or a line break must be wrapped in double quotes, and literal double quotes inside it must be doubled. A good converter does this automatically, but it is worth knowing why a name like "Smith, Jr." needs quoting — without it, the comma splits one field into two and every column after it shifts.

id,note
1,"Smith, Jr."
2,"She said ""hi"""

Delimiters and encoding for Excel

Excel's CSV expectations depend on your regional settings, which causes a lot of confusion. In locales that use a comma as the decimal separator (much of Europe), Excel expects a semicolon as the field delimiter, while US Excel defaults to a comma. If your columns all land in one cell on import, the delimiter is the likely culprit — switch it to match the target locale, or use the import wizard to choose it explicitly.

Encoding matters too. Save the file as UTF-8 so accented characters and non-Latin scripts survive; for older Excel versions, a UTF-8 byte-order mark helps it detect the encoding. Google Sheets handles UTF-8 cleanly and lets you pick the delimiter on import, so it is often the more forgiving target.

Convert it without spreadsheets gymnastics

Rather than wrangling formulas or scripts, paste your JSON into a JSON to CSV converter, which handles flattening, quoting, and delimiter choice for you, then download a file ready to open. For deeply nested payloads, running the data through a JSON Flatten step first gives you full control over the column names before export. And when a colleague sends you a spreadsheet you need back as JSON, a CSV to JSON converter reverses the trip. Everything runs in your browser on JsonDrift, so customer data in those exports never leaves your machine.