Part $2-$ Rank stations by usage

In this part of the lab, you will complete the rank$\_$station$\_$usage function. This function will

analyze bikeshare data within a specific year and quarter to determine the stations that were used

most frequently within that year and quarter. The function takes the following inputs:

bikeshare$\_$df $-$ A pandas DataFrame containing bikeshare data formatted like the

DataFrame returned by the create$\_$bikeshare$\_$df function

year $-$ an int specifying the year we want to analyze

quarter $-$ an int specifying the quarter we want to analyze

The function should return a DataFrame that is indexed by station names and has the following

columns:

DOCUMENT UPDATED April $9,2024$ TO REFLECT THAT PART $1$ IS OPTIONAL AND FOR BONUS

MARKS

The returned DataFrame's rows should be sorted in descending order according to the

combined$\_$departure$\_$return$\_$count values $($i$.$e$.,$ the station with the highest total usage

should be in the first row of the returned DataFrame$).$

Example usage