Programming Essentials Python - Map Reduce Libraries - Projecting data using map

Projecting Data using map

Learn how to project data using the map function in Python to transform elements in an iterable based on specified logic. Follow step-by-step instructions to apply the concepts discussed in the article and practice hands-on tasks to enhance your understanding.

Explanation for the video

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Key Concepts Explanation

Key Concept 1

The map function can be used on top of an iterable to return a new iterable with elements transformed based on specified logic. Here is an example:

numbers = [1, 2, 3, 4]
squared = map(lambda x: x**2, numbers)

Key Concept 2

The map function takes transformation logic and an iterable as arguments. We can pass the transformation logic either as a regular function or a lambda function. Here is an example:

names = ['Alice', 'Bob', 'Charlie']
uppercase_names = map(lambda name: name.upper(), names)

Hands-On Tasks

Practice the following hands-on tasks to apply the concepts of the map function:

  1. Given a list of numbers, create a new list where each number is squared using the map function.
  2. Given a list of strings, create a new list where each string is capitalized using the map function.


In this article, we explored how to use the map function in Python to project data and transform elements in an iterable. By practicing the hands-on tasks and experimenting with different transformation logics, you can further enhance your understanding of this powerful function. Remember to engage with the community for additional support and learning opportunities.

Watch the video tutorial here