pandas json normalize single column

Title: Tutorial on Pandas json_normalize for Single Column
Introduction:
Pandas is a powerful data manipulation library in Python, and it provides a handy function called json_normalize for flattening nested JSON structures into a tabular format. In this tutorial, we'll explore how to use json_normalize specifically for a single column in a DataFrame. This is particularly useful when dealing with JSON data stored in a DataFrame column that needs to be flattened for analysis.
Prerequisites:
Scenario:
Let's assume you have a DataFrame with a column containing nested JSON data. We'll demonstrate how to use json_normalize to flatten this nested JSON structure.
Step 1: Import Required Libraries
Step 2: Create Sample DataFrame with Nested JSON in a Column
Step 3: Display Original DataFrame
Step 4: Use json_normalize for Single Column
Step 5: Display Resulting DataFrame
Explanation:
Conclusion:
Using json_normalize on a single column within a DataFrame allows you to efficiently flatten nested JSON data, making it easier to work with and analyze. This tutorial provides a basic example, and you can adapt it to your specific use cases with more complex nested structures.
Feel free to explore more advanced options and parameters provided by json_normalize in the official Pandas documentation: Pandas json_normalize.
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