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  3. Python Data Science Toolbox (Part 1)

Exercise

Map() and lambda functions

So far, you've used lambda functions to write short, simple functions as well as to redefine functions with simple functionality. The best use case for lambda functions, however, are for when you want these simple functionalities to be anonymously embedded within larger expressions. What that means is that the functionality is not stored in the environment, unlike a function defined with def. To understand this idea better, you will use a lambda function in the context of the map() function.

Recall from the video that map() applies a function over an object, such as a list. Here, you can use lambda functions to define the function that map() will use to process the object. For example:

nums = [2, 4, 6, 8, 10]

result = map(lambda a: a ** 2, nums)

You can see here that a lambda function, which raises a value a to the power of 2, is passed to map() alongside a list of numbers, nums. The map object that results from the call to map() is stored in result. You will now practice the use of lambda functions with map(). For this exercise, you will map the functionality of the add_bangs() function you defined in previous exercises over a list of strings.

Instructions

100 XP
  • In the map() call, pass a lambda function that concatenates the string '!!!' to a string item; also pass the list of strings, spells. Assign the resulting map object to shout_spells.
  • Convert shout_spells to a list and print out the list.