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Python: Built-in Functions vs. For & If Loops – 5 Programs Explained

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Python’s built-in functions make coding fast and efficient. But understanding how they work under the hood is crucial to mastering Python. This post shows five Python tasks, each implemented in two ways: Using built-in functions Using for loops and if statements ✅ 1. Sum of a List ✅ Using Built-in Function: numbers = [ 10 , 20 , 30 , 40 ] total = sum (numbers) print ( "Sum:" , total) 🔁 Using For Loop: numbers = [ 10 , 20 , 30 , 40 ] total = 0 for num in numbers: total += num print ( "Sum:" , total) ✅ 2. Find Maximum Value ✅ Using Built-in Function: values = [ 3 , 18 , 7 , 24 , 11 ] maximum = max (values) print ( "Max:" , maximum) 🔁 Using For and If: values = [ 3 , 18 , 7 , 24 , 11 ] maximum = values[ 0 ] for val in values: if val > maximum: maximum = val print ( "Max:" , maximum) ✅ 3. Count Vowels in a String ✅ Using Built-ins: text = "hello world" vowel_count = sum ( 1 for ch in text if ch i...

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

 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


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] list2 = [4, 5, 6] summed = list(map(lambda x, y: x + y, list1, list2)) print(summed) # Output: [5, 7, 9]

4. Using map() with Custom Functions

You can define a regular function and use it with map().

Example: Squaring Numbers


def square(x): return x ** 2 numbers = [1, 2, 3, 4, 5] squared = list(map(square, numbers)) print(squared) # Output: [1, 4, 9, 16, 25]

5. Combining filter() and map()

You can combine filter() and map() to process data in a pipeline.

Example: Squaring Even Numbers


numbers = [1, 2, 3, 4, 5] squared_evens = list(map(lambda x: x ** 2, filter(lambda x: x % 2 == 0, numbers))) print(squared_evens) # Output: [4, 16]

Summary

  • map() applies a function to each item in an iterable.
  • lambda allows you to define small, anonymous functions in line.
  • They can be combined for concise and expressive transformations of data.

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