Key Ideas

  • Lists can be nested, e.g. [["Montana", 1015165], ["Wyoming", 582658]]
  • A list can be created from a string
    • declaration = "Four score and seven years ago"
    • declaration.split()
    • declaration.split("and")
  • A string can be created from a list
    • seuss = ["green", "eggs", "and", "ham"]
    • glue = "*"
    • glue.join(seuss)
  • Sequences can be converted into lists, e.g. list("Petra Griffins")
  • A tuple is like a list, except that it is immutable, e.g. today = ("Monday", "February", 13)

Active Learning

  • This page contains 2023 census information when the total population of the U.S. was 316,128,839.

  • The file nested-lists.py contains information about the 10 most populous states.

  • Add a pure function to nested-lists.py that calculates and returns the total population of the information passed into it. Print this value after the function returns it.

  • Modify the program to also print the percentage of the U.S. population that lives in the 10 most populated states.

# state_pops.py

def total_pop(collection):
    total = 0
    # for i in range(len(collection)):
    #     total += (collection[i][1])

    for item in collection:
        total += item[1]

    return total

populations = [["California", 38965193],
               ["Texas", 30503301],
               ["Florida", 22610726],
               ["New York", 19571216],
               ["Pennsylvania", 12961683],
               ["Illinois", 12549689],
               ["Ohio", 11785935],
               ["Georgia", 11029227],
               ["North Carolina", 10835491],
               ["Michigan", 10037261]]

# analysis of 10 most populous US states
total_population = total_pop(populations)           # calculate total population of the list
percent_pop = total_population / 334914895 * 100  # calulates percentage of total US population

print("The total population of these states is {}, which is {:.0f}% of the total US population.".format(total_population, percent_pop))

  • Modify the populations variable to include information about whether each state is landlocked. Consider a landlocked state to be one that does not touch the Atlantic Ocean, the Pacific Ocean or the Gulf of Mexico.

  • Modify the program to also calculate and print the percentage of the population in the 10 most populated states that live in a landlocked state.

# state_pops.py

def total_pop(collection):
    total = 0
    # for i in range(len(collection)):
    #     total += (collection[i][1])

    for item in collection:
        total += item[1]

    return total

def landlocked_pop(collection):
    land_total = 0
    for i in range(len(collection)):
        if collection[i][2] == "no ocean":
            land_total += collection[i][1]

    land_percent = land_total / total_pop(collection) * 100

    return land_percent

populations = [["California", 38965193, "ocean"],
               ["Texas", 30503301, "ocean"],
               ["Florida", 22610726, "ocean"],
               ["New York", 19571216, "ocean"],
               ["Pennsylvania", 12961683, "no ocean"],
               ["Illinois", 12549689, "no ocean"],
               ["Ohio", 11785935, "no ocean"],
               ["Georgia", 11029227, "ocean"],
               ["North Carolina", 10835491, "ocean"],
               ["Michigan", 10037261, "no ocean"]]

# analysis of 10 most populous US states
total_population = total_pop(populations)           # calculate total population of the list
percent_pop = total_population / 334914895 * 100  # calulates percentage of total US population

print("The total population of these states is {}, which is {:.0f}% of the total US population.".format(total_population, percent_pop))

# landlocked population analysis
land_pop_percent = landlocked_pop(populations)
print("The population of the landlocked states is {:.0f}%".format(land_pop_percent))
  • Time permitting, make other interesting enhancements.

HW:

  1. Review Lessons 11-1 to 11-3 and make sure you understand everything we’ve discussed about Python lists.
  2. If there is anything you don’t understand, write it down and ask about it during our next class (there’s a list project coming up…).