Built-in Functions

What if you were asked to find the largest number in a list? With the knowledge you've gained, you could write a loop to check if the current element is larger/smaller than the previous biggest one and update it; if not, you'd continue. But for long lists, this method can be quite time-consuming. Thankfully, there are built-in functions that can make this task more efficient. Here are a few:

min(x, y, ...) - Returns the smallest value among x, y, ...;
max(x, y, ...) - Returns the largest value among x, y, ...;
abs(x) - Gives the absolute value of x;
round(x, n) - Rounds the number x to n decimal places;
pow(x, n) - Raises x to the power of n.

For instance, suppose we want to calculate the population density for a set of countries in the countries list. To do this, we'd divide the population by the area. Here's how it's done:


              1234567891011
            
# Initial data
countries = [["USA", 9629091, 331002651], ["Canada", 9984670, 37742154],
            ["Germany", 357114, 83783942], ["Brazil", 8515767, 212559417],
            ["India", 3166391, 1380004385]]

# Iterating over external list
for i in range(len(countries)):
    if type(countries[i]) is list:
        # Computing population density for a country
        pop_dens = countries[i][2]/countries[i][1]
        print(countries[i][0], pop_dens, 'people per km²')

In the example above, our list had 5 nested sub-lists. We looped through the main list and checked if each item was a list. If it was, we divided the third item (population) by the second item (area).

However, the results were not very reader-friendly since they had more than 10 decimal places. To make them more readable, we can use the round() function to reduce them to just 2 decimal places. Remember, this function takes two arguments: the first is the number you want to round, and the second specifies how many decimal places you want to keep.


              1234567891011
            
# Initial data
countries = [["USA", 9629091, 331002651], ["Canada", 9984670, 37742154],
            ["Germany", 357114, 83783942], ["Brazil", 8515767, 212559417],
            ["India", 3166391, 1380004385]]

# Iterating over external list
for i in range(len(countries)):
    if type(countries[i]) is list:
        # Computing population density for a country
        pop_dens = round(countries[i][2]/countries[i][1], 2)
        print(countries[i][0], pop_dens, 'people per km²')

As you can see, the revised result is much clearer and easier to understand.

Everything was clear?

Thanks for your feedback!

Section 6. Chapter 1