Approach

1. Understand the Requirement: Determine the task of identifying the most frequent non-banned word in the paragraph.

2. Input Parsing: Read the paragraph and banned words list, ensuring case insensitivity for the paragraph.

3. Word Frequency Calculation: Count occurrences of each word in the paragraph that is not on the banned list.

4. Determine the Most Frequent Word: Identify the word with the highest frequency and ensure it is unique.

Key Points

• Clarity: Ensure you understand the difference between banned and allowed words.

• Frequency Count: Use a methodical approach to count word occurrences accurately.

• Uniqueness: The solution guarantees that the most frequent non-banned word will be unique.

Standard Response

• Input: A paragraph and a list of banned words.

• Output: The most frequent non-banned word in lowercase.

Tips & Variations

Common Mistakes to Avoid

• Ignoring Case Sensitivity: Ensure the comparison is case insensitive.

• Overlooking Punctuation: Clean the input to avoid punctuation affecting word counts.

Alternative Ways to Answer

• For longer texts, consider using advanced data structures like Counter from the collections module for efficiency.

Role-Specific Variations

• Technical Roles: Emphasize the importance of efficiency in counting algorithms.

• Creative Roles: Focus on language variety and the richness of vocabulary used.

Follow-Up Questions

• What strategies did you use to ensure accuracy in your word count?

• How would you handle ties in word frequency, if applicable?

Formatting & SEO Guidelines

• Keywords: Identify, frequency count, non-banned words, unique word, case insensitivity.

• Readability: Use bullet points, short paragraphs, and clear headings.

This structured approach ensures a comprehensive understanding of the task at hand, providing clarity and direction for job seekers or anyone tackling similar problems