Data Automation & Cleaning Beginner

Flatten Nested API JSON Responses into Clean Tabular CSV in Python

Use pd.json_normalize in Python to flatten deeply nested REST API JSON payloads (orders, trades, webhooks) into a flat CSV table without RAM crashes.

#pandas

Problem Statement

Broker APIs and payment gateways return deeply nested JSON dictionaries that fail when loaded directly into Excel. This script flattens multi-level JSON keys with underscore separators.

Formula / Core Logic

Uses pandas.json_normalize(data, sep='_') to recursively unroll nested child dictionaries into flat columns.

Installation

pip install pandas

convert-large-json-to-csv-python-script.py

import json
import pandas as pd

def flatten_json_to_csv(json_filepath, output_csv='flattened_data.csv', record_path=None):
    with open(json_filepath, 'r', encoding='utf-8') as f:
        data = json.load(f)
    df = pd.json_normalize(data, record_path=record_path, sep='_')
    df.to_csv(output_csv, index=False)
    return df

Get the Complete 100+ Python Quant & Automation Bundle

Instant lifetime access to all production-ready scripts, valuation models, and trading bots ($19).

Buy Full Bundle on Gumroad ($19) →

Frequently Asked Questions

Q: What does the `sep='_'` parameter do?

It joins parent and child keys cleanly, turning `{'user': {'id': 10}}` into a column named `user_id`.