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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 Subset: How to Get Subset of Dictionary

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Here's a sample program to get the python subset. In this case, you'll find logic for dictionary subsets.


Subset from a Dictionary in Python


Dictionary python

To illustrate, I have taken a dictionary as below with keys and values.

my_first_dict = {

'HP': 100
'IBM': 200
'NTT': 300
'ABC': 400
'GDF': 500
}

I want to make a subset of values greater than 100 and less than 400. How can you achieve this? No worries, below, you will find the logic.


Logic to get subset out of a dictionary

I am using dictionary comprehension to achieve this.

Syntax:


sub_set = { key:value for key, value in my_first_dict.items() value >100 and value <400}


Result

Dictionary comprehension


References

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