Introduction to Machine Learning

Below are three useful built-in objects that are often used with for loops.

range()

If you would like to simulate a traditional “counter” style C++ for loop, you can iterate over a range sequence object/type instead.

>>> for i in range(0, 10):
...    print(i)

If you run the example above, you will find that range(0, 10) generates a sequence of numbers from 0 (inclusive) to 10 (exclusive).

The first parameter (start) is optional, and defaults to 0. range(10) is equivalent to range(0, 10)

>>> for i in range(10):
...    print(i)

There is also an optional third step parameter. A bit like in C++, it controls how much you increment the counter after each step.

>>> for i in range(0, 10, 2):
...    print(i)

>>> print(range(0, 5))
>>> print(list(range(0,5)))

enumerate()

Sometimes you may need both the index and the element in the list in a for loop.

[US Billboard Hot 100 Chart Week of October 3, 2020]

enumerate() will provide you with the index (starting at 0 by default) as well as the element in the list.

>>> top_hits = ["Dynamite", "WAP", "Holy", "Laugh Now Cry Later"]
>>> for (position, title) in enumerate(top_hits):
...    print(f"At number {position} we have {title}!")
...
At number 0 we have Dynamite!
At number 1 we have WAP!
At number 2 we have Holy!
At number 3 we have Laugh Now Cry Later!

Oops! The Billboard Chart does not have a position #0! Let’s fix that.

You can either add 1 to the position variable…

>>> for (position, title) in enumerate(top_hits):
...    print(f"At number {position + 1} we have {title}!")
...

Or give enumerate an optional second argument to tell it to start the index at 1.

>>> for (position, title) in enumerate(top_hits, 1):
...    print(f"At number {position} we have {title}!")
...

zip()

zip() is easier explained with an example.

>>> x = [1, 2, 3]
>>> y = [4, 5, 6]
>>> zipped = zip(x, y)
>>> print(list(zipped))
[(1, 4), (2, 5), (3, 6)]
>>> for (a, b) in zip(x, y):
...    print(f"{a}, {b}")
...
1, 4
2, 5
3, 6