Word frequency analysis in Data Analysis Python - Mini Project: Build & Apply

Word frequency analysis

📖 Scenario: Imagine you have a short paragraph of text from a book or an article. You want to find out how many times each word appears in that text. This is useful for understanding which words are used most often.

🎯 Goal: You will create a program that counts how many times each word appears in a given text and then shows the counts.

📋 What You'll Learn

Create a dictionary with words as keys and their counts as values

Use a variable to hold the text to analyze

Use a loop to count the words

Print the final word counts

💡 Why This Matters

🌍 Real World

Word frequency analysis helps in understanding text data, like finding popular topics or keywords in articles, social media, or customer reviews.

💼 Career

Data scientists and analysts use word frequency counts to prepare text data for further analysis or machine learning.

1

Create the text data

Create a variable called text and set it to the exact string: 'Data science is fun and data is powerful'

Data Analysis Python

# Create a variable called text with the given string
# Your code here

Hint

Use single or double quotes to create the string exactly as shown.

2

Prepare the word list

Create a variable called words that contains the list of words from text by splitting text on spaces using text.split()

Data Analysis Python

text = 'Data science is fun and data is powerful'
# Create a list called words by splitting text on spaces
# Your code here

Hint

Use the split() method on the text variable without any arguments.

3

Count the words

Create an empty dictionary called word_counts. Then use a for loop with the variable word to go through each word in words. Inside the loop, add 1 to the count for each word in word_counts. If the word is not in the dictionary, add it with count 1.

Data Analysis Python

text = 'Data science is fun and data is powerful'
words = text.split()
# Create an empty dictionary called word_counts
# Use a for loop to count each word in words
# Your code here

Hint

Use dict.get(key, 0) to get the current count or 0 if the word is new.

4

Display the word counts

Write a print statement to display the word_counts dictionary.

Data Analysis Python

text = 'Data science is fun and data is powerful'
words = text.split()
word_counts = {}
for word in words:
    word_counts[word] = word_counts.get(word, 0) + 1
# Print the word_counts dictionary
# Your code here

Hint

Use print(word_counts) to show the dictionary.

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