And, the default value of sort_keys is False. And, the keys are sorted in ascending order.īy the way, the default value of indent is None. In the above program, we have used 4 spaces for indentation.

When you run the program, the output will be: Firstly we will see how to parse JSON data in Python, which is an important part of converting JSON data to CSV format. Print(json.dumps(person_dict, indent = 4, sort_keys=True)) To convert any JSON file to a CSV file using Python programming language we have to make JSON keys as headers to convert it into a CSV file. It's common to transmit and receive data between a server and web application in JSON format. I'm looking for a more elegant solution to achieve this with fewer lines of code.Īttached is a sample output JSON for reference.JSON ( Java Script Object Notation) is a popular data format used for representing structured data. python - Unable to convert json to csv for a specific columns in pandas - Stack Overflow Unable to convert json to csv for a specific columns in pandas Ask Question Asked today Modified today Viewed 2 times 0 I have a dataset in this form: df. 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]

I have a nested json output from an API request.

Python json to csv