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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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How to use Pandas Series Method top ideas

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How to use Pandas Series Method top ideas

Here is an example of how to use a Series constructor in Pandas. A one-dimensional array capable of holding any data type (integers, strings, floating-point numbers, Python objects, etc.) is called a Series object in pandas.

Sample DataFrame




Single dimension data


Below is the single dimension data of Index and Value.


 Index Value
 1 10           
 2 40
 3 01
 4 99

Having single value for an index is called Single dimensional data. On the other hand, when one index has multiple values, it is called multi-dimensional array.  

Below is the example for Multi-dimensional array. 

a = (1, (10,20))
mySeries = pd.Series(data, index=index)
Here, pd is a Pandas object. The data and index are two arguments. The data refers to a Python dictionary of "ndarray"  and index is index of data.

Generating DataFrame from single dimension data

The below example shows, how to construct single dimension data (Values and Index).

>>>mySeries = pd.Series([10,20,30], index=[1,2, 'a'])

Special Notes: In the above index list the 'a' represents alpha type.

Once mySeries object created, you can verify Values and Index. Do follow the steps in the screen.

series data 

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