Reading JSON with read_json in Pandas - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the purpose of pandas' read_json function?

The read_json function reads JSON formatted data and converts it into a pandas DataFrame for easy data analysis.

intermediate

Which parameter in read_json helps to specify the orientation of the JSON data?

The orient parameter specifies the expected format of the JSON string, such as 'records', 'split', 'index', or 'columns'.

beginner

True or False: read_json can read JSON data directly from a URL.

True. read_json can read JSON data from a local file path, a URL, or a JSON string.

intermediate

What does the lines=True argument do in read_json?

It tells pandas to treat each line in the file as a separate JSON object, useful for reading JSON data in 'JSON Lines' format.

advanced

How does read_json handle nested JSON objects by default?

By default, nested JSON objects are loaded as dictionaries or lists inside DataFrame cells; further processing is needed to flatten them.

What does pd.read_json('data.json') return?

A A list of JSON objects

B A JSON string

C A Python dictionary

D A pandas DataFrame

read_json reads JSON data and returns a pandas DataFrame for analysis.

Which orient value is used when JSON data is a list of records (dictionaries)?

A 'records'

B 'index'

C 'split'

D 'columns'

The 'records' orient expects a list of dictionaries, each representing a row.

How do you read a JSON file where each line is a separate JSON object?

A Use <code>lines=True</code>

B Use <code>orient='split'</code>

C Use <code>header=None</code>

D Use <code>index_col=0</code>

The lines=True option reads JSON Lines format correctly.

Can read_json read JSON data directly from a web URL?

A No

B Only if saved locally first

C Yes

D Only with extra libraries

read_json supports URLs as input sources.

What happens if JSON data contains nested objects when using read_json?

A Nested objects are automatically flattened

B Nested objects remain as dictionaries or lists inside cells

C An error is raised

D Nested objects are ignored

Nested JSON objects stay nested inside DataFrame cells; you must flatten them manually if needed.

Explain how to use pandas read_json to load JSON data from a file and what parameters you might adjust.

Think about the source of JSON and its structure.

Describe how pandas handles nested JSON objects when using read_json and how you might deal with them.

Consider what happens inside the DataFrame cells.