Unit 4

Data Analysis 1

Conceptual and code reading questions

[23.1]

Match the term to its definition.

Term	Definition
Categorical Data	Data falls into separate categories, but those categories can be compared in a specific order.
Ordinal Data	Data are numbers, mathematical operations can be performed on the data and it can be compared to other data.
Numerical Data	Data falls into one of many categories. Those categories are separate and cannot be compared.

Term	Definition
Categorical Data	Data falls into one of many categories. Those categories are separate and cannot be compared.
Ordinal Data	Data falls into separate categories, but those categories can be compared in a specific order.
Numerical Data	Data are numbers, mathematical operations can be performed on the data and it can be compared to other data.

[23.2]

Identify the data type of each of the following examples.

Question	Categorical	Ordinal	Numerical
Favorite Movie
Restaurant Rating
Test Score
Education Level
Height
Customer Satisfaction
Eye Color
Weight
Type of Pet

Solution:

Question	Categorical	Ordinal	Numerical
Favorite Movie	X
Restaurant Rating		X
Test Score			X
Education Level		X
Height			X
Customer Satisfaction		X
Eye Color	X
Weight			X
Type of Pet	X

[23.3]

Briefly explain the difference between ordinal data and numerical data.

[23.4]

Identify whether the following statements are true or false.

Statement	True	False
CSV files store data that is nested, like trees.
CSV files store data in rows and columns.
JSON files can represent nested data structures.
A spreadsheet is an example of structured data
Each row in a CSV file represents one record
A plaintext file cannot store numbers

Statement	True	False
CSV files store data that is nested, like trees.		X
CSV files store data in rows and columns.	X
JSON files can represent nested data structures.	X
A spreadsheet is an example of structured data	X
Each row in a CSV file represents one record	X
A plaintext file cannot store numbers		X

[23.5]

Which statement best explains why CSV files can be described as "two-dimensional"?

a. They only store two types of data
b. They represent data using rows and columns
c. They always contain two variables
d. They can only be read using spreadsheet software

[23.6]

Match the term to its definition.

Term	Definition
Slicing	Used to break up data that is separated by a known delimiter
Split	Used to remove parts of the data that are unnecessary.
Index	Used to remove whitespace (spaces, tabs, and newlines) from the front and back of a string
Strip	Used to find the location of the beginning or end of a section

Term	Definition
Slicing	Used to remove parts of the data that are unnecessary.
Split	Used to break up data that is separated by a known delimiter
Index	Used to find the location of the beginning or end of a section
Strip	Used to remove whitespace (spaces, tabs, and newlines) from the front and back of a string

[23.7]

If s = “I like ice cream”, what is the result of s.split()?

a. [“I like ice cream”]

b. [“Ilikeicecream”]

c. [“I”, “like”, “ice”, “cream”]

d. [“I like”, “ice cream”]

[23.8]

If s = “computer”, what is the result of s[1:4]?

a. “comp”

b. “put”

c. “omp”

d. “Uter”

[23.9]

If s = “banana”, what is the result of s.index(“a”)?

a. 0

b. 1

c. 2

d. 3

e. 4

[23.10]

If s = “I like ice cream”, what is the result of s.strip()?

a. [“Ilikeicecream”]

b. “Ilikeicecream”

c. “I I like like ice ice cream cream”

d. “I like ice cream“

Code Writing questions

[23.11]

Assume we have the following list, lst = [“apple”, “orange”, “Banana”, “STRAWberry”, “grapE”, “raspberry”]. Write some lines of code to change each word in the list to be all caps.

for i in range(len(lst)):
  lst[i] = lst[i].upper()
print(lst)

[23.12]

Assume we have the following list, lst = [“apple”, “orange”, “Banana”, “STRAWberry”, “grapE”, “raspberry”]. Write some code such that all the words in the list have the first letter capitalized and the rest of the letters in lowercase.

# for each word in the list, 
# make the first letter (index 0) in upper case
# and the rest of the list (index 1 and on) in lower case
for i in range(len(lst)):
    lst[i] = lst[i][0].upper() + lst[i][1: ].lower()

[23.13]

The code below is from lecture, where we were parsing a chat log. Assume each message occurs on an individual line.

# example code  
f = open("chat.txt", "r") 
text = f.read() 
f.close() 

people = [ ] 
for line in text.split("\n"): 
    start = line.index("From") + \ len("From") 
    line = line[start:] 
    end = line.index(" : ") 
    line = line[:end] 
    line = line.strip() 
    people.append(line) 
    print(people)

Using the code above as an example, write your own code to count the number of times the name Clare appears in the chat log.

Solution (one way of solving it):

f = open("chat.txt", "r")
text = f.read()
f.close()

count = 0
for line in text.split("\n"):
    start = line.index("From") + len("From")
    line = line[start:]
    end = line.index(" : ")
    line = line[ :end]
    line = line.strip()
    if(line == 'Clare'):
        count += 1
print(count)

[23.14]

The code below is from lecture, where we were parsing a chat log. Assume each message occurs on an individual line.

# example code
f = open("chat.txt", "r") 
text = f.read() 
f.close() 

people = [ ] 
for line in text.split("\n"): 
    start = line.index("From") + \ len("From") 
    line = line[start:] 
    end = line.index(" : ") 
    line = line[:end] 
    line = line.strip() 
    people.append(line) 
    print(people)

Using the code above as an example, write your own code to find who sent a message to Professor Rivers .

f = open("chat.txt", "r")
text = f.read()
f.close()

people = []
for line in text.split("\n"):
    start = line.index("From") + len("From")
    line = line[start:]
    end = line.index(" : ")
    line = line[ :end]
    line = line.strip()
    if "Rivers" in line:
        newEnd = line.index(" to ")
        line = line[ :newEnd]
        line = line.strip()
        people.append(line)
print(people)

[23.15]

The code below is from lecture, where we were working with a 2D list with ice cream data.

# Assume data is a 2D list parsed from the file 
for row in range(len(data)): 
    data[row].pop(0) # remove the ID 
    chocCount = 0 # count number of chocolate 
    for col in range(len(data[row])): 
        # Make all flavors lowercase 
        data[row][col] = data[row][col].lower() 
        if "chocolate" in data[row][col]: 
            chocCount += 1 
    # track chocolate count 
    data[row].append(chocCount) 
print(data)

Using the code above as an example, write your own code to find the number of times strawberry ice cream appeared in the dataset.

strawberryCount = 0
for row in range(len(data)):
    data[row].pop(0)
    for col in range(len(data[row])):
        data[row][col] = data[row][col].lower()
        if "strawberry" in data[row][col]:
            strawberryCount += 1
print(strawberryCount)

[23.16]

The code below is from lecture, where we were working with a 2D list with ice cream data.

# Assume data is a 2D list parsed from the file 
for row in range(len(data)): 
    data[row].pop(0) # remove the ID 
    chocCount = 0 # count number of chocolate 
    for col in range(len(data[row])): 
        # Make all flavors lowercase 
        data[row][col] = data[row][col].lower() 
        if "chocolate" in data[row][col]: 
            chocCount += 1 
    # track chocolate count 
    data[row].append(chocCount) 
print(data)

Using the code above as an example, write your own code to find the number of times vanilla ice cream or matcha ice cream appeared in the dataset. Note: this involves searching for multiple words.

count = 0 # vanilla and matcha count variable
for row in range(len(data)):
    data[row].pop(0)
    for col in range(len(data[row])):
        data[row][col] = data[row][col].lower()
        if "vanilla" in data[row][col] or "matcha" in data[row][col]:
            count += 1
print(count)

Unit 3

Data Analysis I

Conceptual and code reading questions

Code Writing questions

Unit 4

Data Analysis 1

Conceptual and code reading questions

Code Writing questions