How To Convert Pandas Dataframe To Nested Dictionary

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

Python3

import pandas as pd

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

df = pd.DataFrame(data)

# Convert DataFrame to nested dictionary
nested_dict = df.groupby('Name').apply(lambda x: x[['Chain', 'Food', 'Healthy']].to_dict(orient='records')).to_dict()

print(nested_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.

Python3

import pandas as pd
data = {'Person': ['Alice', 'Bob', 'Alice', 'Bob'],
                'Location': ['Home', 'Work', 'Home', 'Work'],
                'Activity': ['Cooking', 'Meeting', 'Reading', 'Working'],
                'Duration': [30, 60, 45, 120]}

df = pd.DataFrame(data)
nested_dict_another = df.groupby(['Person', 'Location']).apply(lambda x: x[['Activity', 'Duration']].to_dict(orient='records')).to_dict()
print(nested_dict_another)

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.