Create a sorted list from the defaultdict, using words across the entire corpus. To achieve this, use the .items() metho

Here's the completed code: ``` # Import defaultdict from collections import defaultdict # Save the fifth document: doc doc = corpus[4] # Sort the doc for frequency: bow_doc bow_doc = sorted(doc, key=lambda w: w[1], reverse=True) # Print the top 5 words of the document alongside the count for word_id, word_count in bow_doc[:5]: print(dictionary.get(word_id), word_count) # Create the defaultdict: total_word_count total_word_count = defaultdict(int) for word_id, word_count in itertools.chain.from_iterable(corpus): total_word_count[word_id] += word_count # Create a sorted list from the defaultdict: sorted_word_count sorted_word_count = sorted(total_word_count.items(), key=lambda w: w[1], reverse=True) # Print the top 5 words across all documents alongside the count for word_id, word_count in sorted_word_count[:5]: print(dictionary.get(word_id), word_count) ``` The code creates a sorted list called `sorted_word_count` by using `sorted()` on `total_word_count.items()`. It then prints the top five words and their counts using a for loop.