Import process from thefuzz. Store the unique cuisine_types into unique_types. Calculate the similarity of 'asian', 'ame

Here's the code to import `process` from `thefuzz`, store unique cuisine types, and calculate similarity of 'asian', 'american', and 'italian' to all possible cuisine types: ```python from fuzzywuzzy import process # Store the unique values of cuisine_type in unique_types unique_types = restaurants['cuisine_type'].unique() # Calculate similarity of 'asian' to all values of unique_types print(process.extract('asian', unique_types, limit=len(unique_types))) # Calculate similarity of 'american' to all values of unique_types print(process.extract('american', unique_types, limit=len(unique_types))) # Calculate similarity of 'italian' to all values of unique_types print(process.extract('italian', unique_types, limit=len(unique_types))) ``` In this code, we first import `process` from `fuzzywuzzy`. We then use the `.unique()` method to get the unique values of the `cuisine_type` column in the `restaurants` DataFrame, and store them in a new variable called `unique_types`. Finally, we use the `process.extract()` function to calculate the similarity of 'asian', 'american', and 'italian' to all possible cuisine types. We pass the string to match as the first argument, the list of choices as the second argument (`unique_types`), and the number of matches to return as the `limit` parameter (which we set to the length of `unique_types`). We print the results using the `print()` function.