Be productive with enhanced authoring capabilities and built-in data visualization.Analyze data across raw formats (CSV, txt, JSON, etc.), processed file formats (parquet, Delta Lake, etc.), leveraging powerful Spark capabilities.Keep data secure with built-in enterprise security features.Easily explore and process data with intuitive low-code experience.With a Microsoft Fabric notebook, you can: Microsoft makes no warranties, expressed or implied, with respect to the information provided here. This information relates to a prerelease product that may be substantially modified before it's released. The desired CSV data is created using the generate_csv_data() function.Microsoft Fabric is currently in PREVIEW.If the value is again a dict then it concatenates the key string with the key string of the nested dict. It checks for the key-value pairs in the dict object.

We normalize the dict object using the normalize_json() function.

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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Python json to csv