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Intermediate Python

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

1 hidden cell

Take Notes

Add notes about the concepts you've learned and code cells with code you want to keep.

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# Add your code snippets here

#pour les listes :
# house list of lists
house = [["hallway", 11.25], 
         ["kitchen", 18.0], 
         ["living room", 20.0], 
         ["bedroom", 10.75], 
         ["bathroom", 9.50]]
         
# Build a for loop from scratch

for h in house :
    print( "The " +str(h[0])+  " is " +str(h[1])+ " sqm." )
#Pour les dict 
# Definition of dictionary
europe = {'spain':'madrid', 'france':'paris', 'germany':'berlin',
          'norway':'oslo', 'italy':'rome', 'poland':'warsaw', 'austria':'vienna' }
          
# Iterate over europe
for key, value in europe.items():
    print("the capital of " +key+ " is " +value)
# for Data frame
for lab, row in cars.iterrows():
    print(lab)
    print(row)
# Import cars data
import pandas as pd
cars = pd.read_csv('cars.csv', index_col = 0)

# Adapt for loop
for lab, row in cars.iterrows() :
     print(lab+ ": "+ str(row['cars_per_cap']))
        
        #####Resultat
    US: 809
    AUS: 731
    JPN: 588
    IN: 18
    RU: 200
    MOR: 70
    EG: 45
# Import cars data
import pandas as pd
cars = pd.read_csv('cars.csv', index_col = 0)

# Use .iterrows()
for lab, row in cars.iterrows() :
    cars.loc[lab, "COUNTRY"] = row["country"].upper()
    
    
# Use .apply(str.upper)

cars["COUNTRY"] = cars["country"].apply(str.upper)
print ( cars )

Explore Datasets

Use the DataFrames imported in the first cell to explore the data and practice your skills!

  • Create a loop that iterates through the brics DataFrame and prints "The population of {country} is {population} million!".
  • Create a histogram of the life expectancies for countries in Africa in the gapminder DataFrame. Make sure your plot has a title, axis labels, and has an appropriate number of bins.
  • Simulate 10 rolls of two six-sided dice. If the two dice add up to 7 or 11, print "A win!". If the two dice add up to 2, 3, or 12, print "A loss!". If the two dice add up to any other number, print "Roll again!".
#Jeu de dés: lancé au sort un dé avancé ou reculé d'un pas ou soit quand la face du dé est egale à 6 avancé aléatoirement 

# NumPy is imported, seed is set

# Starting step
step = 50

# Roll the dice
dice = np.random.randint(1,7)

# Finish the control construct
if dice <= 2 :
    step = step - 1
elif dice >2 and dice <=5 :
    step = step + 1
else :
    step = step + np.random.randint(1,7)

# Print out dice and step
print(dice)
print(step)

Make a list random_walk that contains the first step, which is the integer 0. Finish the for loop: The loop should run 100 times. On each iteration, set step equal to the last element in the random_walk list. You can use the index -1 for this. Next, let the if-elif-else construct update step for you. The code that appends step to random_walk is already coded. Print out random_walk.

# NumPy is imported, seed is set

# Initialize random_walk
random_walk = [0]

# Complete the ___
for x in range(100) :
    # Set step: last element in random_walk
    step = random_walk[-1]

    # Roll the dice
    dice = np.random.randint(1,7)

    # Determine next step
    if dice <= 2:
        # Replace below: use max to make sure step can't go below 0
        step = max(0, step - 1)
    elif dice <= 5:
        step = step + 1
    else:
        step = step + np.random.randint(1,7)

    # append next_step to random_walk
    random_walk.append(step)

# Print random_walk
print(random_walk)
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