Intermediate Python

# Definition of countries and capital
countries = ['spain', 'france', 'germany', 'norway']
capitals = ['madrid', 'paris', 'berlin', 'oslo']

# Get index of 'germany': ind_ger
ind_ger = countries.index('germany')

# Use ind_ger to print out capital of Germany
print(capitals[ind_ger])

# Definition of dictionary
europe = {'spain':'madrid', 'france':'paris', 'germany':'berlin', 'norway':'oslo' }

# Add italy to europe
europe['italy'] = 'rome'

# Print out italy in europe
print('italy' in europe)

# Add poland to europe
europe['poland'] = 'warsaw'

# Print europe
print(europe)

# Definition of dictionary
europe = {'spain':'madrid', 'france':'paris', 'germany':'bonn',
          'norway':'oslo', 'italy':'rome', 'poland':'warsaw',
          'australia':'vienna' }

# Update capital of germany
europe['germany'] = 'berlin'

# Remove australia
del(europe['australia'])

# Print europe
print(europe)

# Dictionary of dictionaries
europe = { 'spain': { 'capital':'madrid', 'population':46.77 },
           'france': { 'capital':'paris', 'population':66.03 },
           'germany': { 'capital':'berlin', 'population':80.62 },
           'norway': { 'capital':'oslo', 'population':5.084 } }


# Print out the capital of France
europe['france']['capital']
# Create sub-dictionary data
data = {'capital':'rome','population':59.83}

# Add data to europe under key 'italy'
europe['italy']= data

# Print europe
print(europe)

# Pre-defined lists
names = ['United States', 'Australia', 'Japan', 'India', 'Russia', 'Morocco', 'Egypt']
dr =  [True, False, False, False, True, True, True]
cpc = [809, 731, 588, 18, 200, 70, 45]

# Import pandas as pd
import pandas as pd

# Create dictionary my_dict with three key:value pairs: my_dict
my_dict = {'country': names,'drives_right':dr,'cars_per_cap':cpc}

# Build a DataFrame cars from my_dict: cars
cars = pd.DataFrame(my_dict)

# Print cars
print(cars)

# Import cars data
import pandas as pd
cars = pd.read_csv('cars.csv', index_col = 0)

# Import numpy, you'll need this
import numpy as np

# Create medium: observations with cars_per_cap between 100 and 500
cpc = cars['cars_per_cap']
between  = np.logical_and(cpc > 100, cpc < 500)
medium = cars[between]


# Print medium
print(medium)

# areas list
areas = [11.25, 18.0, 20.0, 10.75, 9.50]

# Change for loop to use enumerate() and update print()
for a in areas :
    print(a)

# areas list
areas = [11.25, 18.0, 20.0, 10.75, 9.50]

# Change for loop to use enumerate() and update print()
# areas list
areas = [11.25, 18.0, 20.0, 10.75, 9.50]

# Change for loop to use enumerate() and update print()
for index, a in enumerate(areas) :
    print("room "+ str(index)+ ": " + str(a))

# house list of lists
house = [["hallway", 11.25], 
         ["kitchen", 18.0], 
         ["living room", 20.0], 
         ["bedroom", 10.75], 
         ["bathroom", 9.50]]
print(house)        
# Build a for loop from scratch
for x in house :
        print("the " + x[0] + " is " + str(x[1]) + " sqm")