The desired CSV data is created using the generate_csv_data() function.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.ISRO CS Syllabus for Scientist/Engineer Exam.ISRO CS Original Papers and Official Keys.GATE CS Original Papers and Official Keys.DevOps Engineering - Planning to Production.Python Backend Development with Django(Live).Android App Development with Kotlin(Live).Full Stack Development with React & Node JS(Live).Java Programming - Beginner to Advanced.Data Structure & Algorithm-Self Paced(C++/JAVA).Data Structures & Algorithms in JavaScript.Data Structure & Algorithm Classes (Live).The header row contains the keys from the first row of the JSON data. writerow() method is used to write the header row to the CSV file.A new CSV file is created using the open() function and csv.writer() function.with statement is used to open the JSON file and load its contents into a variable using the json.load function.Necessary modules such as json and csv are imported.Note some of the following in the above code: # Write each row of data from the JSON file into the CSV file With open('test.csv', 'w', newline='') as csv_file:

# Create a new CSV file and write the headers With open('test.json', 'r') as json_file: # Open the JSON file and load its contents into a variable

Python code to convert json to csv