Your task is to display the vector for the 'graphic design' bigram in a BoW model:

1. Import the CountVectorizer class to create a BoW model.

2. Instantiate the CountVectorizer class as count_vectorizer, configuring it for a frequency-based model that includes both unigrams and bigrams.

3. Utilize the appropriate method of count_vectorizer to generate a BoW matrix from the 'Document' column in the corpus.

4. Convert bow_matrix to a dense array and create a DataFrame from it, setting the unique features (unigrams and bigrams) as its columns. Assign this to the variable bow_df.

5. Display the vector for 'graphic design' as an array, rather than as a pandas Series.