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Intermediate Python

Run the hidden code cell below to import the data used in this course.

# Import the course packages
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

# Import the two datasets
gapminder = pd.read_csv("datasets/gapminder.csv")
brics = pd.read_csv("datasets/brics.csv")
gapminder

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Loop through brics DataFrame

for index, row in brics.iterrows(): country = row['country'] population = row['population'] print(f"The population of {country} is {population} million!")

Create histogram of life expectancies for countries in Africa

africa_data = gapminder[gapminder['continent'] == 'Africa'] plt.hist(africa_data['lifeExp'], bins=10) plt.title('Life Expectancies in Africa') plt.xlabel('Life Expectancy') plt.ylabel('Frequency') plt.show()

Simulate 10 rolls of two six-sided dice

import random

for _ in range(10): dice1 = random.randint(1, 6) dice2 = random.randint(1, 6) total = dice1 + dice2

if total == 7 or total == 11:
    print("A win!")
elif total == 2 or total == 3 or total == 12:
    print("A loss!")
else:
    print("Roll again!")

import random
for _ in range(10):
    dice1 = random.randint(1, 6)
    dice2 = random.randint(1, 6)
    total = dice1 + dice2
    
    if total == 7 or total == 11:
        print("A win!")
    elif total == 2 or total == 3 or total == 12:
        print("A loss!")
    else:
        print("Roll again!")
# Loop through brics DataFrame
for index, row in brics.iterrows():
    country = row['country']
    population = row['population']
    print(f"The population of {country} is {population} million!")


# Create histogram of life expectancies for countries in Africa
africa_data = gapminder[gapminder['cont'] == 'Africa']
plt.hist(africa_data['life_exp'], bins=10)
plt.title('Life Expectancies in Africa')
plt.xlabel('Life Expectancy')
plt.ylabel('Frequency')
plt.show()