6.4 Predicting Prices of Used Cars. The file ToyotaCorolla.csv contains data on used cars (Toyota Corolla) on sale during late s

Response:

Refer to the explanation

Details:

class Taxicab():

def __init__(self, x, y):

self.x_coordinate = x

self.y_coordinate = y

self.odometer = 0

def get_x_coord(self):

return self.x_coordinate

def get_y_coord(self):

return self.y_coordinate

def get_odometer(self):

return self.odometer

def move_x(self, distance):

self.x_coordinate += distance

# increase the odometer with the absolute distance

self.odometer += abs(distance)

def move_y(self, distance):

self.y_coordinate += distance

# increase odometer with the absolute distance

self.odometer += abs(distance)

cab = Taxicab(5,-8)

cab.move_x(3)

cab.move_y(-4)

cab.move_x(-1)

print(cab.odometer) # will output 8 3+4+1 = 8

Answer: Random fluctuations.

Explanation: A time series consists of data points ordered chronologically, arranged in equal intervals. Typically, this data sequence is systematic and has defined intervals. However, there’s no allowance for randomness, making unpredictable variations, or random fluctuations, absent in such series. Thus, option (D) is the correct choice.

Answer:

Below is the Python code with suitable comments.

Explanation:

#Input file name acquisition

filename=input('Enter the input file name: ')

#Opening the input file

inputFile = open(filename,"r+")

#Dictionary definition.

list={}

#Read and split file content using a loop

for word in inputFile.read().split():

#Check if the word exists in the file.

if word not in list:

list[word] = 1

#Increment count by 1

else:

list[word] += 1

#Closing the file.

inputFile.close();

#Output a blank line

print();

#Sorting words according to their ASCII values.

for i in sorted(list):

#Display unique words along with their

#frequencies in alphabetical order.

print("{0} {1} ".format(i, list[i]));