Word frequency analysis in Data Analysis Python - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to split the text into words.

Data Analysis Python

text = "Data science is fun and data is powerful."
words = text.[1]()

Drag options to blanks, or click blank then click option'

Areplace

Bjoin

Cstrip

Dsplit

Attempts:

3 left

💡 Hint

Common Mistakes

Using join() instead of split()

Using replace() which changes characters but does not split

Using strip() which only removes whitespace from ends

The split() method breaks the text into a list of words separated by spaces.

2fill in blank

medium

Complete the code to count how many times each word appears.

Data Analysis Python

from collections import [1]
counter = [1](words)

Drag options to blanks, or click blank then click option'

AOrderedDict

Bdefaultdict

CCounter

Dnamedtuple

Attempts:

3 left

💡 Hint

Common Mistakes

Using defaultdict which needs manual counting

Using OrderedDict which keeps order but does not count

Using namedtuple which is for fixed data structures

Counter from collections counts the frequency of each item in a list.

3fill in blank

hard

Fix the error in the code to get the most common word and its count.

Data Analysis Python

most_common_word, count = counter.[1](1)[0]

Drag options to blanks, or click blank then click option'

Amostcommon

Bmost_common

Ccommon_most

Dcommon

Attempts:

3 left

💡 Hint

Common Mistakes

Misspelling the method name

Using a method that does not exist

Trying to access attributes instead of calling a method

The correct method name is most_common() which returns a list of tuples with word and count.

4fill in blank

hard

Fill both blanks to create a dictionary of words longer than 3 letters and their counts.

Data Analysis Python

filtered_counts = {word: counter[word] for word in counter if [1](word) [2] 3}

Drag options to blanks, or click blank then click option'

Alen

B>

C<

Dcount

Attempts:

3 left

💡 Hint

Common Mistakes

Using count instead of len for word length

Using < instead of > for filtering

Not calling len as a function

We use len(word) to get word length and filter words with length greater than 3 using >.

5fill in blank

hard

Fill all three blanks to create a sorted list of words by frequency in descending order.

Data Analysis Python

sorted_words = sorted(counter.items(), key=lambda [1]: [2][[3]], reverse=True)

Drag options to blanks, or click blank then click option'

Ax

C1

D0

Attempts:

3 left

💡 Hint

Common Mistakes

Using 0 instead of 1 to sort by word instead of count

Using a different variable name inconsistently

Forgetting reverse=True for descending order

The lambda function takes each item x and sorts by the second element x[1] which is the count. reverse=True sorts descending.

Practice

1.

What does word frequency analysis help us understand about a text?

easy

A. How many times each word appears in the text

B. The total number of characters in the text

C. The number of sentences in the text

D. The length of the longest word in the text

Solution

1. Step 1: Understand the purpose of word frequency analysis

   Word frequency analysis counts how often each word appears in a text.

2. Step 2: Compare options with the purpose

   Only How many times each word appears in the text matches this purpose exactly.

3. Final Answer:

   How many times each word appears in the text -> Option A

4. Quick Check:

   Word frequency = count of each word [OK]

Hint: Focus on counting words, not characters or sentences [OK]

Common Mistakes:

• Confusing word count with character count
• Thinking it counts sentences
• Assuming it finds longest word length

2.

Which Python code correctly imports the tool to count word frequencies?

?

easy

A. import wordcount from collections

B. import Counter from collections

C. from collections import wordfreq

D. from collections import Counter

Solution

1. Step 1: Recall the correct import syntax for Counter

   The correct way is 'from collections import Counter'.

2. Step 2: Check each option's syntax

   Only from collections import Counter uses valid Python import syntax and correct name.

3. Final Answer:

   from collections import Counter -> Option D

4. Quick Check:

   Correct import = from collections import Counter [OK]

Hint: Remember 'from collections import Counter' exactly [OK]

Common Mistakes:

• Using wrong import order
• Trying to import non-existent modules
• Using invalid syntax like 'import Counter from'

3.

What is the output of this code?

from collections import Counter
text = "apple banana apple orange banana apple"
words = text.split()
count = Counter(words)
print(count)

medium

A. Counter({'apple': 1, 'banana': 1, 'orange': 1})

B. {'apple': 3, 'banana': 2, 'orange': 1}

C. Counter({'apple': 3, 'banana': 2, 'orange': 1})

D. {'apple': 1, 'banana': 2, 'orange': 3}

Solution

1. Step 1: Split the text into words

   The text splits into ['apple', 'banana', 'apple', 'orange', 'banana', 'apple'].

2. Step 2: Count each word using Counter

   'apple' appears 3 times, 'banana' 2 times, 'orange' 1 time.

3. Final Answer:

   Counter({'apple': 3, 'banana': 2, 'orange': 1}) -> Option C

4. Quick Check:

   Count matches word occurrences [OK]

Hint: Count words carefully; Counter shows counts with 'Counter()' [OK]

Common Mistakes:

• Ignoring Counter output format
• Miscounting word frequencies
• Confusing dictionary and Counter print styles

4.

Find the error in this code that tries to count words:

from collections import Counter
text = "Hello world! Hello"
words = text.split()
count = Counter(words.lower())
print(count)

medium

A. Cannot call lower() on a list; should call on each word

B. Missing import statement for Counter

C. split() should be split(' ')

D. Counter cannot count strings

Solution

1. Step 1: Identify the type of 'words'

   words is a list of strings after split().

2. Step 2: Check the use of lower()

   Calling words.lower() is invalid because lists have no lower() method; lower() applies to strings.

3. Final Answer:

   Cannot call lower() on a list; should call on each word -> Option A

4. Quick Check:

   lower() works on strings, not lists [OK]

Hint: Apply lower() to each word, not the whole list [OK]

Common Mistakes:

• Calling lower() on list instead of string
• Ignoring error messages
• Thinking split() needs arguments

5.

You want to count words ignoring case and punctuation in this text:

text = "Hello, hello! How are you? Are you fine?"

Which code correctly cleans and counts words?

hard

A. import re
from collections import Counter
words = re.findall(r'\w+', text)
count = Counter(words)
print(count)

B. import string
from collections import Counter
clean_text = text.lower().translate(str.maketrans('', '', string.punctuation))
words = clean_text.split()
count = Counter(words)
print(count)

C. from collections import Counter
words = text.split()
count = Counter(words)
print(count)

D. from collections import Counter
words = text.lower().split()
count = Counter(words)
print(count)

Solution

1. Step 1: Understand the need to remove punctuation and lowercase

   To count words ignoring case and punctuation, text must be lowercased and punctuation removed.

2. Step 2: Check each option's approach

   import string from collections import Counter clean_text = text.lower().translate(str.maketrans('', '', string.punctuation)) words = clean_text.split() count = Counter(words) print(count) uses string.punctuation with translate() to remove punctuation and lowercases text before splitting, which is correct.

3. Final Answer:

   Code that lowercases and removes punctuation before counting -> Option B

4. Quick Check:

   Clean text + Counter = accurate word frequency [OK]

Hint: Remove punctuation and lowercase before splitting words [OK]

Common Mistakes:

• Not removing punctuation
• Counting words with mixed cases separately
• Using split() without cleaning text