P$1.$ Using any process you like, create the following table as a pandas DataFrame named $$Vendors$.$ The top row is column names; the left$-$most column is row names:

Office Stuff Superstore Medingstone, Inc. Treadstone, Inc.

address $43$ Wallaby Way $1337$ Broadmore Ave. $415$ East $71$st St$.$

City Sydney New York City New York City

State ND NY NY

zipcode $584011010810021$

Phone $701-456-1557212-683-1448212-413-3322$

supply$\_$type Office Supplies Therapy Tools Other Assets

P$2.$ Transpose the Vendors DataFrame and re$-$save it with the same name.

P$3.$ Create a new column named $$vendor$\_$name$$ with the same values as the row names $($after transposition$).$

P$4.$ Create a column of zeroes named $$NY$.$

P$5.$ In a single statement, replace the values in $$NY$$ with $1$ if the state variable is equal to $$NY$.$

P$6.$ Use a summary method from Table $5-8$ on pg$.162$ of PDA to calculate how many vendors are from $$NY$.$

P$7.$ Use a summary method from Table $5-8$ on pg$.162$ of PDA to calculate the proportion of vendors that are from $$NY$.$

P$8.$ Drop the $$NY$$ column from your DataFrame.