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Python map() and lambda() Use Cases and Examples

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 In Python, map() and lambda functions are often used together for functional programming. Here are some examples to illustrate how they work. Python map and lambda top use cases 1. Using map() with lambda The map() function applies a given function to all items in an iterable (like a list) and returns a map object (which can be converted to a list). Example: Doubling Numbers numbers = [ 1 , 2 , 3 , 4 , 5 ] doubled = list ( map ( lambda x: x * 2 , numbers)) print (doubled) # Output: [2, 4, 6, 8, 10] 2. Using map() to Convert Data Types Example: Converting Strings to Integers string_numbers = [ "1" , "2" , "3" , "4" , "5" ] integers = list ( map ( lambda x: int (x), string_numbers)) print (integers) # Output: [1, 2, 3, 4, 5] 3. Using map() with Multiple Iterables You can also use map() with more than one iterable. The lambda function can take multiple arguments. Example: Adding Two Lists Element-wise list1 = [ 1 , 2 , 3 ]
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Python Set comprehension - How to Use it Read now

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In python, Set does not allow duplicates, and  you can't modify an existing set with a comprehension. But using the Set comprehension you can create a new Set. Set Comprehension  In addition, the comprehension must result in a valid set.  Likewise Dictionary, a set does not allow entries of the same value. If you try to add values to the set that are already there, it will replace the old one with the new one. Explained syntax Set comprehensions using the {} syntax only exist in Python 3. Before that, you'll have to use the set() function to create and work with sets. You might guess, therefore, that one of the best uses of a set is to eliminate duplicates. In fact, this is one of the most basic forms of set comprehension. Given a list, we can duplicate it as a list with a simple list comprehension like this: Details of logic if we change the list comprehension to a set comprehension, we get the same result, but as a set. That means without duplicates. list_copy = [x for x in o
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