Consider a DataFrame named df with columns named P2010, P2011, P2012, P2013, 2014 and P2015 containing float values. We want to use the apply method to get a new DataFrame named result_df with a new column AVG. The AVG column should average the float values across P2010 to P2015. The apply method should also remove the 6 original columns (P2010 to P2015). For that, what should be the value of x and y in the given code? frames = ['P2010', 'P2011', 'P2012', 'P2013', 'P2014', 'P2015']
df['AVG'] = df[frames ].apply(lambda z: np. mean(z), axis=x)
result_df df. drop(frames, axis=y)
a. x = 1 y = 0.
b. x = 1 y = 1.
c. x = 0 y = 1.
d. x = 0 y = 0.

7.23 main lab 7 - online shopping cart background this main lab extends the earlier prep lab "online shopping cart part 1". (you should save this as a separate project from the earlier prep lab). you will create an on-line shopping cart like you might use for your on-line purchases. the goal is to become comfortable with setting up classes and using objects. requirements this lab can be done individually or as pair programming. expanded itemtopurchase class (15 points) extend the itemtopurchase class as follows. we will not do unit testing in this lab so we will not be giving you the names of the member functions. create good ones on your own. create a parameterized constructor to assign item name, item description, item price, and item quantity (default values of "none" for name and description, and 0 for price and quantity). additional public member functions set an item description get an item description print the cost of an item - outputs the item name followed by the quantity, price, and subtotal (see example) print the description of an item - outputs the item name and description (see example) additional private data members a string for the description of the item. example output of the function which prints the cost of an item: bottled water 10 @ $1.50 = $15.00 example output of the function which prints the item description: