How Can I Efficiently Convert JSON to CSV in Python?

Converting JSON to CSV with Python

Converting a JSON file into a CSV format is a common task in data analysis and data processing pipelines. Python provides several efficient methods to accomplish this conversion, including the use of libraries such as pandas.

In your specific case, you encountered errors while trying to write rows to a CSV file using the csv module. This is because the f object is not a CSV writer object but rather an open file. To fix this issue, you should use the open() function to create a CSV writer object and then write rows to it.

However, using the native Python modules for JSON and CSV handling can be tedious and error-prone. Instead, we recommend using the pandas library, which simplifies this conversion process with just two commands:

1. df = pd.read_json(filepath): This command reads the JSON file into a pandas dataframe named df.
2. df.to_csv(filepath): This command writes the dataframe to a CSV file specified by filepath.

Here is a working minimal example:

import pandas as pd

with open('data.json', encoding='utf-8') as inputfile:
    df = pd.read_json(inputfile)

df.to_csv('data.csv', encoding='utf-8', index=False)

This code will read the JSON file into a pandas dataframe, and then write the dataframe to a CSV file without including the index column. The encoding parameter ensures that the file is properly encoded for special characters.

For more complex JSON structures or handling unstructured JSON data, you may need to explore additional methods or libraries. However, for most common JSON conversion scenarios, using pandas with the read_json() and to_csv() functions is a reliable and efficient approach.

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