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Python Set Operations Explained: From Theory to Real-Time Applications

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A  set  in Python is an unordered collection of unique elements. It is useful when storing distinct values and performing operations like union, intersection, or difference. Real-Time Example: Removing Duplicate Customer Emails in a Marketing Campaign Imagine you are working on an email marketing campaign for your company. You have a list of customer emails, but some are duplicated. Using a set , you can remove duplicates efficiently before sending emails. Code Example: # List of customer emails (some duplicates) customer_emails = [ "alice@example.com" , "bob@example.com" , "charlie@example.com" , "alice@example.com" , "david@example.com" , "bob@example.com" ] # Convert list to a set to remove duplicates unique_emails = set (customer_emails) # Convert back to a list (if needed) unique_email_list = list (unique_emails) # Print the unique emails print ( "Unique customer emails:" , unique_email_list) Ou...
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Numpy Array Vs. List: What's the Difference

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Here are the differences between List and NumPy Array. Both store data, but technically these are not the same. You'll find here where they differ from each other.

Python Lists

Here is all about Python lists:

  • Lists can have data of different data types. For instance, data = [3, 3.2, 4.6, 6, 6.8, 9, “hello”, ‘a’]
  • Operations such as subtraction, multiplying, and division allow doing through loops
  • Storage space required is more, as each element is considered an object in Python
  • Execution time is high for large datasets
  • Lists are inbuilt data types


Array vs list


NumPy Arrays

Here is all about NumPy Arrays:
  • Numpy arrays are containers for storing only homogeneous data types. For example: data= [3.2, 4.6, 6.8]; data=[3, 6, 9]; data=[‘hello’, ‘a’]
  • Numpy is designed to do all mathematical operations in parallel and is also simpler than Python
  • Numpy storage space is very much less compared to the list due to the practice of homogeneous data type
  • Execution time is very less for large datasets
  • Numpy is a third-party library that needs to be installed by Conda or PIP


References

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