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Learn Built-in Functions in Python | Functions in Python
Introduction to Python
course content

Course Content

Introduction to Python

Introduction to Python

1. First Acquaintance with Python
2. Variables and Types in Python
3. Conditional Statements in Python
4. Other Data Types in Python
5. Loops in Python
6. Functions in Python

book
Built-in Functions in Python

What if you need to find the largest number in a list? With what you've learned, you could write a loop that compares each element to the current largest value, updating it when a bigger number is found. Fortunately, Python provides built-in functions that make this task easier and 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 example, if we need to calculate the population density for a set of countries in the countries list, we simply divide the population by the land area.

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# 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')
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The list contained five nested sub-lists. A loop iterated through the main list, checking if each item was a list. If so, the population density was calculated by dividing the third item (population) by the second item (area).

However, the results were difficult to read due to more than 10 decimal places. To improve readability, you can use the round() function to limit the output to 2 decimal places. This function takes two arguments: the first is the number to be rounded, and the second specifies the number of decimal places to retain.

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# 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')
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Section 6. Chapter 1
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