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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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Excel Analytics: The complete best explained Free Tutorials

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Can you do analytics—either kind—using Excel? Sure. Excel has a large array of tools that bear directly on analytics, including various mathematical and statistical functions that calculate logarithms, regression statistics, matrix multiplication and inversion, and many of the other tools needed for different kinds of analytics. But not all the tools are native to Excel. 

 For example, some situations call for you to use logistic regression: a technique that can work much better than ordinary least-squares regression when you have an outcome variable that takes on a very limited range of values, perhaps only two. Odds ratios are the workhorses of logistic regression, but although Excel offers a generous supply of least-squares functions, it doesn’t offer a maximum likelihood odds ratio function. 

The below list makes you strong in Excel analytics

  1. Microsoft Excel 2010 Data Analysis With Functions
  2. Analytics with Excel - Book
  3. Cloud data analytics from Excel
  4. Quantitative Analysis with Excel
  5. Data Analysis Using SQL and Excel
  6. Excel Analytics 

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