how to convert flatten table to nested hierarchical json in python

Certainly! Converting a flattened table to nested (hierarchical) JSON is a common task, especially when dealing with data that has a hierarchical structure. In this tutorial, I'll guide you through the process using Python and provide a code example using the pandas library.
Make sure you have the pandas library installed. If you don't have it installed, you can install it using:
Let's create a sample flattened table to work with. In a real-world scenario, you would replace this with your actual data.
Now, let's convert the flattened table to nested JSON. We'll use the groupby and to_dict functions from the pandas library.
The flatten_table_to_nested_json function takes a DataFrame (df), an optional index column (index_col), and a list of columns to be nested (nested_cols).
It iterates through the DataFrame and builds a nested dictionary structure based on the specified nested columns.
The groupby and to_dict functions are then used to convert the DataFrame into a nested dictionary.
This tutorial provides a simple example of how to convert a flattened table to nested JSON using Python and the pandas library. You can adapt the code to your specific dataset and requirements.
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