Filtering and Mapping#

Filtering#

Oftentimes, we have a list of elements and we want to select only a few from it. A common task in a music application, for example, is to select just the songs by a particular artist or from a particular genre. Python (along with many other programming languages) has a function for doing this with lists called filter.

Using filter requires that we first write a function that checks for the items we want from the list. As a first example, let’s try to filter a list of numbers to get just the elements that are less than 10. We need a function that checks numbers to see their size:

>>> def less_than_10(n): return n < 10

Then we can use this function with filter on a list:

>>> l = [5, 100, 3, 50, 6]
>>> list(filter(less_than_10, l))
[5, 3, 6]

Here’s what happened:

  • filter went one-by-one through the elements of the list, and for each:

    • Called the less_than_10 function with that element

    • If the result was True, put the element in the collection it eventually returned

    • If the result was False, left the element out of the collection it eventually returned

The use of list(...) tells Python that we want to get the resulting collection back as a list (there are other kinds in Python, but we aren’t using them right now).

(Above, we defined a function all on one line – this is allowed in Python and is a reasonable thing to do for short functions whose body is just a simple expression. If the body has an if-statement or other multi-line statement, or would be wider than about half a screen-width (this is a bit subjective), it shouldn’t be a one-line function.)

Here’s another example that keeps only the strings that are longer than 5 characters:

>>> def long_string(s): return len(s) > 5
...
>>> l2 = ["long string", "short", "small", "longer"]
>>> list(filter(long_string, l2))
['long string', 'longer']

So filter takes two arguments - a function and a list. It expects the function to take one argument, which will get elements from the list and return True or False. Such functions are often called predicates, a word you may have heard in math. It then calls that function on each element, and produces a new collection of just the elements for which that function returns True.

Mapping#

Another common operation on lists is to make a new list with elements based on the existing ones somehow. For example, we might want to take a list of all the students in a class and get a list of all of their email addresses, or take a list of names and turn them into a list of form emails with the names filled in. Python (along with many other programming languages) has a function for doing this called map.

Using map requires we first write a function that transforms the elements into the new kind of elements. As a first example, let’s try to map a list of numbers to those numbers squared. We need a function that squares numbers:

>>> def square(x): return x * x
...
>>> l = [4, 3, 7, 6]
>>> list(map(square, l))
[16, 9, 49, 36]

Here’s what happened:

  • map went one-by-one through the elements of the list, and for each:

    • Called the square function with that element

    • Put the resulting value into the collection it eventually returned

Here’s another example that makes all the strings all capitals with exclamation points:

>>> def shout(s): return s + "!"
...
>>> l = ["MAP", "IS", "SO", "COOL"]
>>> list(map(shout, l))
['MAP!', 'IS!', 'SO!', 'COOL!']