Exporting Pandas DataFrame to JSON File

Pandas a powerful Python library for data manipulation provides the to_json() function to convert a DataFrame into a JSON file and the read_json() function to read a JSON file into a DataFrame.

In this article we will explore how to export a Pandas DataFrame to a JSON file with detailed explanations and beginner-friendly steps.

Exporting Pandas DataFrame to JSON

To export a Pandas DataFrame to a JSON file we use the to_json() function. This function converts the DataFrame into a JSON format making it easy to store and share data. To read the JSON file back into a DataFrame we use the read_json() function. Let’s explore some examples to understand how they work.

Example 1: Exporting a Simple DataFrame

This example demonstrates how to create a small DataFrame with three rows and three columns and save it as a JSON file.

import pandas as pd

df = pd.DataFrame([['a', 'b', 'c'], ['d', 'e', 'f'], ['g', 'h', 'i']],
                  index=['row 1', 'row 2', 'row 3'],
                  columns=['col 1', 'col 2', 'col 3'])

df.to_json('file.json', orient='split', compression='infer', index=True)

df = pd.read_json('file.json', orient='split', compression='infer')
print(df)

Output : 

We can see that the DataFrame has been exported as a JSON file.

Example 2: Exporting a More Detailed DataFrame

In this example we create a DataFrame containing employee details such as ID, Name and Date of Joining. The JSON file is exported using the split orientation which efficiently organizes the data by storing indexes, column names and values separately.

import pandas as pd

df = pd.DataFrame(data=[
    ['15135', 'Alex', '25/4/2014'],
    ['23515', 'Bob', '26/8/2018'],
    ['31313', 'Martha', '18/1/2019'],
    ['55665', 'Alen', '5/5/2020'],
    ['63513', 'Maria', '9/12/2020']],
    columns=['ID', 'NAME', 'DATE OF JOINING'])

df.to_json('file1.json', orient='split', compression='infer')

df = pd.read_json('file1.json', orient='split', compression='infer')
print(df)

Output : 

We can see that this DataFrame has also been exported as a JSON file.

JSON Orientations in Pandas 

Pandas supports multiple orient options for JSON format allowing different ways to structure the data. Choosing the right orientation depends on the use case.

• records: List of dictionaries
• columns: Dictionary with column labels
• index: Dictionary with row indices
• split: Dictionary with index, columns, and data
• table: JSON table schema

Example:

df.to_json('file.json', orient='records')

This saves the DataFrame as a list of dictionaries.