The Orange data is in built in R. Write code to perform a kmeans analysis of the age and circumference attributes. Write code to plot the result. Write a few sentences on how you determined the number of clusters to use.

Complete the docstring using the information attached (images):def upgrade_stations(threshold: int, num_bikes: int,                     stations: List["Station"]) -> int:    """Modify each station in stations that has a capacity that is less than    threshold by adding num_bikes to the capacity and bikes available counts.    Modify each station at most once.     Return the total number of bikes that were added to the bike share network.     Precondition: num_bikes >= 0     >>> handout_copy = [HANDOUT_STATIONS[0][:], HANDOUT_STATIONS[1][:]]    >>> upgrade_stations(25, 5, handout_copy)    5    >>> handout_copy[0] == HANDOUT_STATIONS[0]    True    >>> handout_copy[1] == [7001, 'Lower Jarvis St SMART / The Esplanade', \                            43.647992, -79.370907, 20, 10, 10]    True    """