The read_json() function is used for the task, which taken the file path along with the extension as a parameter and returns the contents of the JSON file as a python dict object. This will help us to make use of python dict methods to perform some operations.

The first step is to read the JSON file as a python dict object.

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The exported file’s name is the streaming.csv file, in the same directory as the export.json file. So that is why the returning value here is None. In this case, we don’t need to return any data because we are exporting the file. Let’s say we are exporting in the same directory as the export.json file. To do that, we need to provide the export path to create a CSV file. Let’s convert Pandas object to CSV data and print it in the console. Let’s transform the JSON string to Pandas object. I am assuming that the export.json file is in the same directory as your coding file. Pandas allow you to convert the list of lists to DataFrame and specify the column names separately.Ī JSON parser transforms a JSON text into another representation must accept all texts that conform to the JSON grammar. Parsing of the JSON Dataset using pandas is much more convenient.

Pandas read_json() is an inbuilt function that converts a JSON string to a pandas object. Step 2: Read json and transform it into Pandas object That means, when we convert it into a pandas object, the index would be 0, 1, 2, 3, 4, and header columns will be Netflix and Quibi. In the above file, you can see that the keys are index.

Converting json to csv python