How to Convert JSON to CSV (Free, Online, or with Python)

To convert JSON to CSV, map each JSON object to a row and each key to a column header. The fastest way is an online JSON-to-CSV converter; for nested data you flatten objects into dotted column names. In Python, pandas.json_normalize() handles complex structures cleanly.

JSON is hierarchical; CSV is a flat grid. The whole job is turning one into the other without losing data. Here's how.

JSON vs CSV Structure

JSON nests data; CSV is rows and columns:

[
  { "id": 1, "name": "Ada",  "city": "London" },
  { "id": 2, "name": "Alan", "city": "Bletchley" }
]

becomes:

id,name,city
1,Ada,London
2,Alan,Bletchley

Each object becomes a row; each key becomes a column. The conversion is clean when your JSON is a flat array of objects.

Method 1: Convert Online in One Click

The quickest route — no install, nothing leaves your browser. Paste your JSON into our JSON to CSV tool and copy or download the CSV. If you only want to view the data as a grid, JSON to Table renders it as sortable rows.

If the converter errors, your JSON may be invalid — check it first with the JSON Validator.

Method 2: Flatten Nested JSON

Real-world JSON often nests objects:

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

Flatten nested keys with dot notation so they become columns:

id,name,address.city,address.zip
1,Ada,London,EC1

Arrays inside objects are trickier — you either join them into one cell ("admin; editor") or expand them into multiple rows. Decide based on how you'll use the CSV.

Method 3: Convert with Python (pandas)

For large or deeply nested files, Python is ideal:

import pandas as pd
import json

with open("data.json") as f:
    data = json.load(f)

# Flattens nested JSON automatically
df = pd.json_normalize(data)
df.to_csv("output.csv", index=False)

json_normalize expands nested objects into dotted columns; pass record_path and meta to explode nested arrays.

Method 4: Open the CSV in Excel

Once you have the CSV, open it directly in Excel or Google Sheets. If you'd rather go straight to a spreadsheet, see How to Convert JSON to Excel.

Troubleshooting Irregular Keys

If objects have different keys, a good converter unions all keys into the header and leaves blanks where a record lacks a value. Validate and pretty-print messy input first with the JSON Formatter so you can see the structure before converting.

Frequently Asked Questions

How do I convert JSON to CSV? Map each JSON object to a row and each key to a column. Use an online JSON-to-CSV converter, or pandas.json_normalize() in Python.

How do I convert JSON to CSV in Python? Load the JSON, run pandas.json_normalize(data) to flatten it, then call df.to_csv("output.csv", index=False).

How do I handle nested JSON? Flatten nested keys into dotted column names (address.city), and either join or explode inner arrays depending on your needs.

Can Excel open JSON directly? Not as a table. Convert JSON to CSV first (or use Excel's Power Query), then open the result.

How do I convert a JSON array to CSV? A flat array of objects converts directly — each object is a row, each key a column. Paste it into a JSON-to-CSV tool.

How to Convert JSON to CSV (Free, Online, or with Python)