011. Basic JSON Parsing
EXECUTIVE_SUMMARY // AEO_OPTIMIZED
[Answer Engine Overview: What, Why & How]
JSON is simply text formatted to look like JavaScript objects. Passing a JSON file path or a URL endpoint directly to pd.read_json() will automatically download and parse the data into a DataFrame.
022. Data Orientation
Unlike a CSV, which is strictly rows and columns, JSON can be structured in many ways. A dictionary of lists {'Col': [1,2]} vs a list of dictionaries [{'Col': 1}]. You use the orient argument to tell Pandas how the JSON is formatted (e.g., orient='records', orient='index').
033. Flattening Nested Data
Web APIs often return nested data (a dictionary inside a dictionary). If you pass this to read_json, Pandas will simply put the inner dictionary into a single column. To split nested keys into their own distinct columns, you must use pd.json_normalize().
?Frequently Asked Questions
Can I read JSON directly from a web API?
Yes, you can pass a URL string directly into `pd.read_json('https://api.example.com/data')`.
What if the API requires an authentication token?
If the API requires headers or tokens, you should use the `requests` library to fetch the JSON first, and then pass the resulting Python dictionary into Pandas.
