In this post, we will walk through the process of loading JSON data into a pandas DataFrame using Python. JSON (JavaScript Object Notation) is a popular data format for exchanging data between a server and a web application. Pandas, a powerful data manipulation library in Python, makes it easy to work with JSON data.

Step-by-Step Guide

Sample JSON Data

Let’s assume you have JSON data stored in a file called data.json. Here’s an example of what the content might look like:

[
    {
        "name": "John",
        "age": 30,
        "city": "New York"
    },
    {
        "name": "Anna",
        "age": 22,
        "city": "London"
    },
    {
        "name": "Mike",
        "age": 32,
        "city": "San Francisco"
    }
]

Loading JSON Data into a DataFrame

To load this JSON data into a pandas DataFrame, follow these steps:

1. Read the JSON file:Use the pd.read_json() function to read the JSON file and load it into a DataFrame. Here’s how you can do it:

# Read the JSON file
df = pd.read_json('data.json')

# Display the DataFrame
print(df)

1. This will load the JSON data into a DataFrame and print it.

Example Code

Here’s the complete example code to load the JSON data into a DataFrame and display it:

import pandas as pd

# Read the JSON file
df = pd.read_json('data.json')

# Display the DataFrame
print(df)

Output

The output will be a DataFrame with the JSON data:

    name  age           city
0   John   30       New York
1   Anna   22         London
2   Mike   32  San Francisco

Conclusion

Loading JSON data into a pandas DataFrame is straightforward with the pd.read_json() function. This allows you to leverage the powerful data manipulation capabilities of pandas to analyze and process your JSON data efficiently.