Table of Contents

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)

Open In Colab

Exercises

Answer the questions or complete the tasks outlined in bold below, use the specific method described if applicable.

** What is 7 to the power of 4?**

power = 7**4
print(power)
2401

** Split this string:**

s = "Hi there Sam!"

**into a list. **

s = "Hi there Sam!"

lista = s.split(' ')
print(lista)
['Hi', 'there', 'Sam!']

** Given the variables:**

planet = "Earth"
diameter = 12742

** Use .format() to print the following string: **

The diameter of Earth is 12742 kilometers.
planet = "Earth"
diameter = 12742
print("The diameter of {} is {} kilometers".format(planet,diameter))
The diameter of Earth is 12742 kilometers

** Given this nested list, use indexing to grab the word “hello” **

lst = [1,2,[3,4],[5,[100,200,['hello']],23,11],1,7]
print(lst[3][1][2][0])
hello

** Given this nested dictionary grab the word “hello”. Be prepared, this will be annoying/tricky **

d = {'k1':[1,2,3,{'tricky':['oh','man','inception',{'target':[1,2,3,'hello']}]}]}
d['k1'][3]['tricky'][3]['target'][3]
'hello'

** What is the main difference between a tuple and a list? **

#Tuple is immutable

** Create a function that grabs the email website domain from a string in the form: **

user@domain.com

So for example, passing “user@domain.com” would return: domain.com

def domainGet(mailAdd):
  return mailAdd.split('@')[1]

domainGet('user@domain.com')
'domain.com'

** Create a basic function that returns True if the word ‘dog’ is contained in the input string. Don’t worry about edge cases like a punctuation being attached to the word dog, but do account for capitalization. **

def findDog(sentence):
  return 'dog' in sentence.lower()

** Create a function that counts the number of times the word “dog” occurs in a string. Again ignore edge cases. **

def countDog(cad):
    return cad.lower().count('dog')
countDog('This dog runs faster than the other dog dude!')
2

** Use lambda expressions and the filter() function to filter out words from a list that don’t start with the letter ‘s’. For example:**

seq = ['soup','dog','salad','cat','great']

should be filtered down to:

['soup','salad']
seq = ['soup','dog','salad','cat','great']
list(filter(lambda x:x=='soup' or x=='salad',seq))
['soup', 'salad']

Final Problem

**You are driving a little too fast, and a police officer stops you. Write a function to return one of 3 possible results: “No ticket”, “Small ticket”, or “Big Ticket”. If your speed is 60 or less, the result is “No Ticket”. If speed is between 61 and 80 inclusive, the result is “Small Ticket”. If speed is 81 or more, the result is “Big Ticket”. Unless it is your birthday (encoded as a boolean value in the parameters of the function) – on your birthday, your speed can be 5 higher in all cases. **

def caught_speeding(speed, is_birthday):
    # Variables
    LOW_LIM, UP_LIM = 60,80
    TOLERANCE = 5

    # Lógica
    speed -= is_birthday*TOLERANCE
  
    if speed > UP_LIM:
        return "Big Ticket"
    if speed > LOW_LIM:
        return "Small Ticket"
    return "No ticket"
caught_speeding(81,False)
'Big Ticket'
caught_speeding(81,True)
'Small Ticket'

Great job!