[Solved] You have a list of documents:docs = ['Data Science is fun', 'I love machine learning', 'Deep learning and data']You want to create a dictionary where keys... Which code snippet correctly does this? | NLP

NLP - Text Similarity and Search

You have a list of documents:

docs = ['Data Science is fun', 'I love machine learning', 'Deep learning and data']

You want to create a dictionary where keys are unique words (case-insensitive) from all documents, and values are lists of document indices where the word appears. Which code snippet correctly does this?

Aword_docs = {} for i, doc in enumerate(docs): for word in doc.lower().split(): word_docs.setdefault(word, []).append(i)

Bword_docs = {} for i, doc in enumerate(docs): for word in doc.split(): word_docs[word].append(i)

Cword_docs = {word: i for i, doc in enumerate(docs) for word in doc.lower().split()}

Dword_docs = {} for doc in docs: for word in doc.lower().split(): word_docs[word] = doc

Step-by-Step Solution

Solution:

Step 1: Understand the goal
Create a dictionary mapping each unique lowercase word to a list of document indices where it appears.
Step 2: Analyze each option
word_docs = {} for i, doc in enumerate(docs): for word in doc.lower().split(): word_docs.setdefault(word, []).append(i) uses setdefault to initialize lists and appends indices correctly with lowercase words. word_docs = {} for i, doc in enumerate(docs): for word in doc.split(): word_docs[word].append(i) misses initializing lists and ignores case. word_docs = {word: i for i, doc in enumerate(docs) for word in doc.lower().split()} creates a dict with last index only, not lists. word_docs = {} for doc in docs: for word in doc.lower().split(): word_docs[word] = doc overwrites values with document strings, not indices.
Final Answer:
word_docs = {} for i, doc in enumerate(docs): for word in doc.lower().split(): word_docs.setdefault(word, []).append(i) -> Option A
Quick Check:
Use setdefault and lowercase words for correct mapping [OK]

Quick Trick: Use setdefault to build lists for each word [OK]

Common Mistakes:

MISTAKES

Not initializing lists before appending
Ignoring case normalization
Overwriting dictionary values instead of appending

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Step 2: Analyze each option

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