This exercise will be using the [Airbnb dataset] (http://insideairbnb.com/get-the-data.html) for NYC called 'listings.csv'. You can download it directly [here] (http://data.insideairbnb. com/united-statesyew-york-city/2022-12-04/visualisations/listings.csv) a) Produce a Heatmap using the Folium package (you can install it using pip) of the mean listing price per location (lattitude and longitude) over the NYC map. (5 points) Hints: 1. generate a base map of NYC to plot over: default_location =[40.693943,73.985880] 2. generate an HTML file named index. html - open it in your browser and you'll see the heatmap Lvar/foldersr/dnxv080j4qvf48cpxw1w39880000gn/T/ipykernel 65019/3495829452.py:6: Dtypewarning: Columns (17) have mixed types. Specify dtype option on import or set low_memory=False. df=pd. read_csv("listings. csv") b) Plot a bar chart of the average price per room type. Briefly comment on the relation between price and room type. - (2.5 pts) -> your answer here c) Plot on the NYC map the top 10 most reviewed listings (Note: some could be in the same location) - (5 pts) Python -> your answer here