Converting Pandas dataframe to dictionary – Detailed examples included

This article will guide you through the process of converting a Pandas DataFrame to a dictionary with clear examples.

Sample dataframe:

import pandas as pd
# Sample data: Age and Score for Sachin, Ram, Abhilash, Mike, and Elaine
df = pd.DataFrame({
    'Age': [25, 30, 29, 24, 27],
    'Score': [85, 88, 76, 90, 82]
}, index=['Sachin', 'Ram', 'Abhilash', 'Mike', 'Elaine'])
print(df)

Converting DataFrame to Dictionary:

Using to_dict() Method:

Pandas provides a to_dict() method that can transform a DataFrame into a dictionary. By default, it uses a column-wise orientation.

default_dict = df.to_dict()
print(default_dict)

Output:

{
    'Age': {
        'Sachin': 25,
        'Ram': 30,
        'Abhilash': 29,
        'Mike': 24,
        'Elaine': 27
    },
    'Score': {
        'Sachin': 85,
        'Ram': 88,
        'Abhilash': 76,
        'Mike': 90,
        'Elaine': 82
    }
}

Row-wise Conversion:

If you want to convert your DataFrame into a dictionary with row-wise orientation, you can set the orient parameter to ‘index’.

row_dict = df.to_dict(orient='index')
print(row_dict)

Output:

{
    'Sachin': {'Age': 25, 'Score': 85},
    'Ram': {'Age': 30, 'Score': 88},
    'Abhilash': {'Age': 29, 'Score': 76},
    'Mike': {'Age': 24, 'Score': 90},
    'Elaine': {'Age': 27, 'Score': 82}
}

Refer more on python here : Python
Refer more on Pandas here
Refer more on python here : PySpark