In this article, we will learn how to convert Pandas DataFrame to Nested Dictionary.

Convert Pandas Dataframe To Nested Dictionary

Converting a Pandas DataFrame to a nested dictionary involves organizing the data in a hierarchical structure based on specific columns. In Python’s Pandas library, we can utilize the groupby function along with apply to create groupings based on chosen columns.

Let’s create a DataFrame that contains information about different products, including their names, prices, and stock quantities. The to_dict method with the parameter orient=records is commonly employed to convert each group into a dictionary of records. Let’s see how to convert dataframe to nested dictionary:

Using to_dict

Output:

{'David': [{'Chain': 'Starbucks', 'Food': 'coffee', 'Healthy': False}, 
{'Chain': 'Chick-fil-A', 'Food': 'grilled chicken', 'Healthy': True}], 
'Emily': [{'Chain': 'Panera Bread', 'Food': 'soup', 'Healthy': True}, 
{'Chain': 'Subway', 'Food': 'sandwich', 'Healthy': True}]}

Let’s see another complex example, to gain in-depth understanding.

Output:

{('Alice', 'Home'): [{'Activity': 'Cooking', 'Duration': 30}, {'Activity': 'Reading', 'Duration': 45}], 
('Bob', 'Work'): [{'Activity': 'Meeting', 'Duration': 60}, {'Activity': 'Working', 'Duration': 120}]}

Conclusion

Hence, we can convert Pandas Dataframe To Nested Dictionary with just few lines of code.