Code debugging

[andre-wallan]

Load data

def load_data(url): import urllib.request response = urllib.request.urlopen(url) lines = response.read().decode().splitlines() data_dict = [] for line in lines[1:]: # Skip header values = line.split(',') data_dict.append({ 'Continent': values[0], 'Year': float(values[1]), 'Life Expectancy': float(values[2]) }) return data_dict

Calculate summary statistics

def calculate_summary_stats(data_dict): years = [row['Year'] for row in data_dict] life_expectancies = [row['Life Expectancy'] for row in data_dict] continents = [row['Continent'] for row in data_dict] avg_life_expectancy = sum(life_expectancies) / len(life_expectancies) min_life_expectancy = min(life_expectancies) max_life_expectancy = max(life_expectancies) min_year = years[life_expectancies.index(min_life_expectancy)] max_year = years[life_expectancies.index(max_life_expectancy)] return avg_life_expectancy, min_life_expectancy, max_life_expectancy, min_year, max_year

Find largest drop

def find_largest_drop(data_dict): largest_drop = 0 largest_drop_year = 0 largest_drop_continent = '' for i in range(len(data_dict) - 1): drop = data_dict[i]['Life Expectancy'] - data_dict[i + 1]['Life Expectancy'] if drop > largest_drop: largest_drop = drop largest_drop_year = data_dict[i]['Year'] largest_drop_continent = data_dict[i]['Continent'] return largest_drop, largest_drop_year, largest_drop_continent

Plot life expectancy over time (text-based)

def plot_life_expectancy_over_time(years, life_expectancies): print("\nLife Expectancy Over Time:") for year, life_expectancy in zip(years, life_expectancies): print(f"{year}: {'' int(life_expectancy)} ({life_expectancy:.2f})")

Plot life expectancy by continent (text-based)

def plot_life_expectancy_by_continent(continents, life_expectancies): continent_life_expectancies = {} for continent, life_expectancy in zip(continents, life_expectancies): if continent not in continent_life_expectancies: continent_life_expectancies[continent] = [] continent_life_expectancies[continent].append(life_expectancy) print("\nLife Expectancy by Continent:") for continent, life_expectancies in continent_life_expectancies.items(): avg_life_expectancy = sum(life_expectancies) / len(life_expectancies) print(f"{continent}: {avg_life_expectancy:.2f}")

Calculate correlation between life expectancy and year

def calculate_correlation(years, life_expectancies): sum_years = sum(years) sum_life_expectancies = sum(life_expectancies) sum_years_squared = sum(year2 for year in years) sum_life_expectancies_squared = sum(life_expectancy2 for life_expectancy in life_expectancies) sum_year_life_expectancy = sum(year life_expectancy for year, life_expectancy in zip(years, life_expectancies)) n = len(years) correlation = (n sum_year_life_expectancy - sum_years sum_life_expectancies) / ( (n sum_years_squared - sum_years2) (n sum_life_expectancies_squared - sum_life_expectancies2))**0.5 return correlation

Main function

def main(): url = '(link unavailable)' data_dict = load_data(url) avg_life_expectancy, min_life_expectancy, max_life_expectancy, min_year, max_year = calculate_summary_stats(data_dict) print("Summary Statistics:") print(f"Average Life Expectancy: {avg_life_expectancy:.2f}") print(f"Minimum Life Expectancy: {min_life_expectancy:.2f} in {min_year}") print(f"Maximum Life Expectancy: {max_life_expectancy:.2f} in {max_year}") largest_drop, largest_drop_year, largest_drop_continent = find_largest_drop(data_dict) print(f"\nLargest Drop in Life Expectancy: {largest_drop:.2f} in {largest_drop_continent} from {largest_drop_year} to {largest_drop_year + 1}") country = input("\nEnter a continent: ") country_data = [row for row in data_dict if row['Continent'] == country] if country_data: country_life_expectancies = [row['Life Expectancy'] for row in country_data] country_min_life_expectancy = np.min(country_life_expectancies)

    country_max_life_expectancy = np.max(country_life_expectancies)

    country_avg_life_expectancy = np.mean(country_life_expectancies)
    print(f"\nCorrelation between Life Expectancy and Year: {correlation:.2f}")