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Best Practices for Handling Duplicate Elements in Python Lists

Here are three awesome ways that you can use to remove duplicates in a list. These are helpful in resolving your data analytics solutions.  01. Using a Set Convert the list into a set , which automatically removes duplicates due to its unique element nature, and then convert the set back to a list. Solution: original_list = [2, 4, 6, 2, 8, 6, 10] unique_list = list(set(original_list)) 02. Using a Loop Iterate through the original list and append elements to a new list only if they haven't been added before. Solution: original_list = [2, 4, 6, 2, 8, 6, 10] unique_list = [] for item in original_list:     if item not in unique_list:         unique_list.append(item) 03. Using List Comprehension Create a new list using a list comprehension that includes only the elements not already present in the new list. Solution: original_list = [2, 4, 6, 2, 8, 6, 10] unique_list = [] [unique_list.append(item) for item in original_list if item not in unique_list] All three methods will result in uni

Python Program: JSON to CSV Conversion

JavaScript object notion is also called JSON file, it's data you can write to a CSV file. Here's a sample python logic for your ready reference. 

You can write a simple python program by importing the JSON, and CSV packages. This is your first step. It is helpful to use all the JSON methods in your python logic. That means the required package is JSON.

So far, so good. In the next step, I'll show you how to write a Python program. You'll also find each term explained.

What is JSON File

JSON is key value pair file. The popular use of JSON file is to transmit data between heterogeneous applications. Python supports JSON file.

What is CSV File

The CSV is comma separated file. It is popularly used to send and receive data.

How to Write JSON file data to a CSV file

Here the JSON data that has written to CSV file. It's simple method and you can use for CSV file conversion use.

import csv, json

json_string = '[{"value1": 1, "value2": 2,"value3": 1.234}]'
data = json.loads(json_string)
headers = data[0].keys()

with open('sample.csv', 'w') as f:
writer = csv.DictWriter(f, fieldnames=headers)

with open('sample.csv', 'r') as f:
    for row in f:


<_io.TextIOWrapper name='file.csv' mode='r' encoding='UTF-8'>


** Process exited - Return Code: 0 **
Press Enter to exit terminal


The output CSV file has both headers and rows, and the data is comma seprated.



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