Creating separate code for each of these columns seems redundant and inefficient. # Apply the function to each row of the DataFrameĭf_final = pd.concat(, axis=1)ĭf_final.to_csv('resul.csv', index=False)Īlthough I have successfully created separate columns for some nested data, there are still other nested values within these columns. # Custom function to extract values from JSON objects Max_objects = max(len(item_list) for item_list in df_item)
# Determine the maximum number of JSON objects in a cell My goal is to get a csv with all the columns inside the json, and to do this I have to create single columns for each nested index inside the JSON.Ĭredentials = " for i in range(max_items) for key in keys] If the JSON file has a different structure, you may need to adjust the code accordingly.I have a nested json output from an API request. In the example I provided, the JSON file is an array of objects, with each object having the same keys. It is essential to mention that the structure of the JSON file should match the structure that is expected by the code. The file can be generated from different sources, such as an API or data scraping, or it could be a file that you have created on your own. It could be any file that has a valid JSON format, such as a file containing information about products, customers, or weather data. The data.json file in the previous example is a file that contains data in JSON format. If the JSON file has a different structure, you may need to adjust the code accordingly.
Please note that this code assumes that the JSON file is an array of objects, each having the same keys. The fieldnames for the writer are set to the keys of the first element of the data. Then, it creates a new CSV file and uses the CSV module’s DictWriter() class to write the data to the file. In this example, the code first opens the JSON file using the open() function and the JSON module’s load() function, which reads the file’s contents and converts it to a Python object. # Create a new CSV file and write the data with open( 'data.csv', 'w', newline = '') as csv_file: Import csv import json # Open the JSON file with open( 'data.json') as json_file:
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