Create a DataFrame named faculty$\_$grade$\_$dist by performing the following steps.

$$ Group the records in the grades DataFrame according to fid.

$$ Perform the following aggregations:

o Count the number of grades that have been issued by each faculty member. Name the

resulting column N$.$

o Use aggregation operations to create columns named countA, countB, countC, countD,

and countF. Each of these columns should contain a count of the number of grades of the

indicated type that have been assigned by each faculty member. This can be accomplished

using the SUM and CASE keywords discussed above.

$$ Use a join to pull in columns from the faculty DataFrame.

$$ Use select$()$ to select the following columns: fid, first$\_$name, last$\_$name, dept, and N$.$ Use

the same call to select$()$ to create five new columns named propA, propB, propC, propD, and

propF. Each of these new propX columns should be calculated by dividing the associated countX

column by N and rounding the results to $2$ decimal places.

Display the first $5$ records of the faculty$\_$grade$\_$dist DataFrame.