Reading JSON (read_json) in Data Analysis Python - Mini Project: Build & Apply

Reading JSON Data with pandas

📖 Scenario: You work at a small online store. The store keeps its product data in JSON format. You want to load this data into Python to analyze it easily.

🎯 Goal: Load a JSON string into a pandas DataFrame, then filter products by price.

📋 What You'll Learn

Create a JSON string variable with product data

Create a price threshold variable

Use pandas read_json to load the JSON string into a DataFrame

Filter the DataFrame to keep only products with price above the threshold

Print the filtered DataFrame

💡 Why This Matters

🌍 Real World

Many companies store data in JSON format. Loading JSON into DataFrames helps analyze and visualize data easily.

💼 Career

Data analysts and scientists often read JSON data from APIs or files to prepare data for analysis.

1

Create JSON string with product data

Create a variable called json_data that holds this exact JSON string: [{"product": "Pen", "price": 1.5}, {"product": "Notebook", "price": 3.0}, {"product": "Eraser", "price": 0.5}]

Data Analysis Python

# Create the variable json_data with the exact JSON string
# Your code here

Need a hint?

Use single quotes outside and double quotes inside for the JSON string.

2

Set price threshold

Create a variable called price_threshold and set it to 1.0

Data Analysis Python

json_data = '[{"product": "Pen", "price": 1.5}, {"product": "Notebook", "price": 3.0}, {"product": "Eraser", "price": 0.5}]'
# Create price_threshold variable and set it to 1.0
# Your code here

Need a hint?

Just assign 1.0 to price_threshold.

3

Load JSON and filter products

Import pandas as pd. Use pd.read_json to load json_data into a DataFrame called df. Then create a new DataFrame called filtered_df that contains only rows where the price column is greater than price_threshold.

Data Analysis Python

json_data = '[{"product": "Pen", "price": 1.5}, {"product": "Notebook", "price": 3.0}, {"product": "Eraser", "price": 0.5}]'
price_threshold = 1.0
# Import pandas as pd
# Load json_data into df using pd.read_json
# Create filtered_df with rows where price > price_threshold
# Your code here

Need a hint?

Use square brackets to filter the DataFrame by condition.

4

Print filtered DataFrame

Print the filtered_df DataFrame to show products with price above the threshold.

Data Analysis Python

import pandas as pd

json_data = '[{"product": "Pen", "price": 1.5}, {"product": "Notebook", "price": 3.0}, {"product": "Eraser", "price": 0.5}]'
price_threshold = 1.0

df = pd.read_json(json_data)
filtered_df = df[df['price'] > price_threshold]
# Print filtered_df
# Your code here

Need a hint?

Use print(filtered_df) to display the filtered products.