Python JSON Data Filtering

JSON (JavaScript Object Notation) is a lightweight data-interchange format widely used for storing and exchanging data between a server and a web application. Python, with its built-in json module, provides powerful tools for working with JSON data. In this article, we’ll explore how to filter and manipulate JSON data using Python, focusing on five commonly encountered scenarios.

Python JSON Data Filtering

Below, are the methods of Python JSON Data Filtering in Python.

• Filtering by Key
• Filtering by Value
• Nested JSON Filtering
• Conditional Filering

JSON Data Filtering by Key

In this example, the below code uses the `JSON` module in Python to load a JSON-formatted string representing personal data. It then filters the data by selecting only the “name” and “age” keys, creating a new dictionary called `filtered_data`, and printing the result.

Python3

import json

# Sample JSON data
person_data = '{"name": "John", "age": 30, "city": "New York", "occupation": "Engineer"}'
person = json.loads(person_data)

# Filtering by key
filtered_data = {key: person[key] for key in ["name", "age"]}
print(filtered_data)

Output

{'name': 'John', 'age': 30}

JSON Data Filtering by Value

In this example, the below code utilizes Python’s `json` module to load a JSON array representing people’s data. It then filters the array to retain only those individuals whose age is greater than 30, creating a new list called `filtered_people.

Python3

import json

# Sample JSON array
people_data = '[{"name": "John", "age": 30}, {"name": "Alice", "age": 25}, {"name": "Bob", "age": 35}]'
people = json.loads(people_data)

# Filtering by value
filtered_people = [person for person in people if person["age"] > 30]
print(filtered_people)

Output

[{'name': 'Bob', 'age': 35}]

JSON Data Filtering Using Nested JSON

In this example, the below code employs Python’s `json` module to load a nested JSON object representing book data. It then filters the nested structure to extract the author’s age and prints the result.

Python3

import json

# Sample nested JSON data
book_data = '{"title": "The Python Guide", "author": {"name": "Jane Doe", "age": 40}}'
book = json.loads(book_data)

# Nested JSON filtering
author_age = book["author"]["age"]
print(f"The author's age is {author_age}")

Output

The author's age is 40

JSON Data Filtering Using Conditional Filtering

In this example, in below code `json` module is used to load a JSON array containing product information. The code then performs conditional filtering to create a new list, `in_stock_products`, including only those products with stock quantities greater than 5.

Python3

import json

# Sample JSON array of products
products_data = '[{"name": "Laptop", "price": 1200, "stock": 5}, {"name": "Headphones", "price": 80, "stock": 0}, {"name": "Mouse", "price": 20, "stock": 10}]'
products = json.loads(products_data)

# Conditional filtering
in_stock_products = [product for product in products if product["stock"] > 5]
print(in_stock_products)

Output

[{'name': 'Mouse', 'price': 20, 'stock': 10}]