Built-in Functions in Python
Imagine you have to find the largest number within the 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.
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.
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 kmΒ²')
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).
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 kmΒ²')
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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Imagine you have to find the largest number within the 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.
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.
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 kmΒ²')
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).
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 kmΒ²')
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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