The complete code with the result is shown below : Code: Python3 import pandas as pd df1 pd.readjson file1. Step 3: Convert the concatenated dataframe into CSV file. Step 2 : Concatenate the dataframes into one dataframe. I then get the error: `sequence expected`įirst, your JSON has nested objects, so it normally cannot be directly converted to CSV. Step 1: Load the json files with the help of pandas dataframe. I am using Django and the error I received is: `file' object has no attribute 'writerow'` It allows programmers to say, write this data in the format preferred by Excel, or read data from this file which was generated by Excel, without knowing the precise details of the CSV format used by Excel.

I'm looking for a more elegant solution to achieve this with fewer lines of code.Īttached is a sample output JSON for reference.I have a JSON file I want to convert to a CSV file. The csv module implements classes to read and write tabular data in CSV format. 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. python - Problems joining two CSV tables with ID and exporting as nested JSON - Stack Overflow Ask Question Asked today Modified today Viewed 10 times 0 Problems joining two CSV Tables over ID and exporting as a nested JSON Hey absolute Python beginner here. Read the lines of CSV file using csv.DictReader() function. # Custom function to extract values from JSON objects To convert CSV to JSON in Python, follow these steps: Initialize a Python List. Is there any way or script to parse CSV logs (any pattern) to Json format using lambda function (python) in kinesis. Max_objects = max(len(item_list) for item_list in df_item) I have a scenario, I am receiving all logs in csv format to kinesis firehose directly and with help of lambda function (python) I need to transform the csv logs to json and return the output back to kinesis.

# 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 csv