# Function converts the json string to a dataframe and appends it directly to the CSV fileĭef add_json_string_to_csv(api_result_string):ĭf_with_new_data.to_csv('output. The advantage is that all data is already in the CSV if the program crashes or if you terminate it. Instead of building a huge dataframe over time, the code below appends the fetched data directly into the CSV file. The output of above code: item amount weight price bestbeforeendeateĮDIT: I had another look at the problem and thought I share another solution, which might be better for you. # The dataframe you want to store everythingĭf = add_new_entry_to_dataframe(df, newly_fetched_result)
Input_parsed = json.loads(api_result_string)ĭf_with_new_data = pd.json_normalize(input_parsed) # Function converts the api result to the dataframe and appends it to dfĭef add_new_entry_to_dataframe(df, api_result_string): In order to convert a JSON string into a dict you can simply use the json library. I then get the error: `sequence expected`įirst, your JSON has nested objects, so it normally cannot be directly converted to CSV.Pandas has a function called json_normalize, which can directly convert a dict into a dataframe. The lack of a well-defined standard means that subtle differences often exist in the data produced and. CSV format was used for many years prior to attempts to describe the format in a standardized way in RFC 4180. I am using Django and the error I received is: `file' object has no attribute 'writerow'` The so-called CSV (Comma Separated Values) format is the most common import and export format for spreadsheets and databases. It will be: csvw csv. I have a JSON file I want to convert to a CSV file. You need to simply add the lineterminatorn parameter to the csv.writer.
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