Python Pandas - Reading and Writing JSON Files

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JSON (JavaScript Object Notation) is a lightweight, human-readable data-interchange format widely used for data storage and transfer. It is widely used for transmitting data between a server and a web application. Python's Pandas library provides robust functionalities for reading and writing JSON files efficiently using theread_json() andto_json() methods.

A JSON file stores data in a structured format, which looks similar to a dictionary or a list in Python. A JSON file has.json extension. Below you can see how the data present in the JSON file looks like −

[    {        "Name": "Braund",        "Gender": "Male",        "Age": 30    },    {        "Name": "Cumings",        "Gender": "Female",        "Age": 25    },    {        "Name": "Heikkinen",        "Gender": "female",        "Age": 35    }]

In this tutorial, we will learn about basics of working with JSON files using Pandas, including reading and writing JSON files, and some common configurations.

Reading JSON Files with Pandas

Thepandas.read_json() function is used to read JSON data into a Pandas DataFrame. This function can take a file path, URL, or JSON string as input.

Example

The following example demonstrates how to read JSON data using thepandas.read_json() function. Here we are using theStringIO to load the JSON string into a file-like object.

import pandas as pdfrom io import StringIO# Create a string representing JSON datadata = """[    {"Name": "Braund", "Gender": "Male", "Age": 30},    {"Name": "Cumings", "Gender": "Female", "Age": 25},    {"Name": "Heikkinen", "Gender": "Female", "Age": 35}]"""# Use StringIO to convert the JSON formatted string data into a file-like objectobj = StringIO(data)# Read JSON into a Pandas DataFramedf = pd.read_json(obj)print(df)

Following is the output of the above code −

	Name	Gender	Age
0	Braund	Male	30
1	Cumings	Female	25
2	Heikkinen	Female	35

Writing JSON Files with Pandas

Pandas provides theto_json() function to export or write JSON file using the data from a Pandas DataFrame or Series objects. This function is used to convert a Pandas data structure object into a JSON string, and it offers multiple configuration options for customizing the JSON output.

Example: Basic Example of writing a JSON file

Here is an example demonstrating how to write a Pandas DataFrame to a JSON file.

import pandas as pd# Create a DataFrame from the above dictionarydf = pd.DataFrame({"Name":["Braund", "Cumings", "Heikkinen"], "Gender": ["Male", "Female", "Female"],"Age": [30, 25, 25]})print("Original DataFrame:\n", df)    # Write DataFrame to a JSON filedf.to_json("output_written_json_file.json", orient='records', lines=True)print("The output JSON file has been written successfully.")

Following is the output of the above code −

Original DataFrame:

	Name	Gender	Age
0	Braund	Male	30
1	Cumings	Female	25
2	Heikkinen	Female	35

The output JSON file has been written successfully.

After executing the above code, you can find the created JSON file namedoutput_written_json_file.json in your working directory.

Example: Writing a JSON file using the split orientation

The following example writes a simple DataFrame object into JSON using thesplit orientation.

import pandas as pdfrom json import loads, dumps# Create a DataFramedf = pd.DataFrame(    [["x", "y"], ["z", "w"]],    index=["row_1", "row_2"],    columns=["col_1", "col_2"],)# Convert DataFrame to JSON with 'split' orientationresult = df.to_json(orient="split")parsed = loads(result)# Display the JSON outputprint("JSON Output (split orientation):")print(dumps(parsed, indent=4))

Following is the output of the above code −

JSON Output (split orientation):{    "columns": [        "col_1",        "col_2"    ],    "index": [        "row_1",        "row_2"    ],    "data": [        [            "x",            "y"        ],        [            "z",            "w"        ]    ]}