22. You have dataframe called food_prices below:ItemStorePriceDatePearA0.992017PearB1.992017PeachA2.992017PeachB3.492017BananaA0.392017BananaB0.492017SteakA5.992017SteakB 6.992017steakB4.992015 and another called food_transactions below: IndexCustIDItemStoreQuantity01PearA511PearB1022PeachA332PeachB142BananaA252BananaB162SteakA4 Which of the following line of code will give the ouput below?IndexCustIDItemStoreQuantityPriceDate01PearA50.99201711PearB101.99201722PeachA32.99201732PeachB13.49201742BananaA20.39201752BananaB10.49201762SteakA45.992017food_transactions.merge(food_prices,on = ['item','store'])food_transactions.join(food_prices,on = ['item','store'])food_transactions.concat(food_prices,on = ['item','store'])food_prices.concat(food_transactions,on = ['item','store'])None of the above

---------------------------------------------------------------------------NameError Traceback (most recent call last)Cell In[12], line 5 3 # We load the prices and calculate the future return 4 prices=pd.read_csv('Prices.zip',parse_dates=['date']).set_index(['id','date']).squeeze()----> 5 future_returns=cp.log(prices,groupby('id'),shift(-1)/ prices).rename('fut_ret') 7 # We load the information signals 8 factors=pd.read_csv('A2_Data.zip',parse_dates=['date']).set_index(['id','date'])NameError: name 'cp' is not defined

KeyError Traceback (most recent call last)Cell In[94], line 2 1 # Sales by customer type----> 2 sales_by_customer_type = july.groupby('Customer Type')['Amount'].sum().sort_values(ascending=False) 4 # Plotting 5 plt.figure(figsize=(12, 8))File ~\anaconda3\lib\site-packages\pandas\core\frame.py:9183, in DataFrame.groupby(self, by, axis, level, as_index, sort, group_keys, observed, dropna) 9180 if level is None and by is None: 9181 raise TypeError("You have to supply one of 'by' and 'level'")-> 9183 return DataFrameGroupBy( 9184 obj=self, 9185 keys=by, 9186 axis=axis, 9187 level=level, 9188 as_index=as_index, 9189 sort=sort, 9190 group_keys=group_keys, 9191 observed=observed, 9192 dropna=dropna, 9193 )File ~\anaconda3\lib\site-packages\pandas\core\groupby\groupby.py:1329, in GroupBy.__init__(self, obj, keys, axis, level, grouper, exclusions, selection, as_index, sort, group_keys, observed, dropna) 1326 self.dropna = dropna 1328 if grouper is None:-> 1329 grouper, exclusions, obj = get_grouper( 1330 obj, 1331 keys, 1332 axis=axis, 1333 level=level, 1334 sort=sort, 1335 observed=False if observed is lib.no_default else observed, 1336 dropna=self.dropna, 1337 ) 1339 if observed is lib.no_default: 1340 if any(ping._passed_categorical for ping in grouper.groupings):File ~\anaconda3\lib\site-packages\pandas\core\groupby\grouper.py:1043, in get_grouper(obj, key, axis, level, sort, observed, validate, dropna) 1041 in_axis, level, gpr = False, gpr, None 1042 else:-> 1043 raise KeyError(gpr) 1044 elif isinstance(gpr, Grouper) and gpr.key is not None: 1045 # Add key to exclusions 1046 exclusions.add(gpr.key)KeyError: 'Customer Type'

Make the following changes to your compute_bill function:While you loop through each item of food, only add the price of the item to total if the item’s stock count is greater than zero.if the item is in stock and after you add the price to the total, subtract one from the item’s stock count.

---------------------------------------------------------------------------AttributeError Traceback (most recent call last)Cell In[12], line 5 2 a = df.groupby(['City', 'Cuisines']).size().reset_index(name='Counts') 4 # Find the most prevalent cuisines in each city----> 5 n = a.loc[df.count.groupby('City')['Counts'].idxmax()].head(5)AttributeError: 'function' object has no attribute 'groupby'

1.Working with data for the store Four (name_store), write a query to calculate the change in total revenue in each category (category) and in the store in general after the sale of each product (name) on June 2, 2019. Store the results in the category_accum and store_accum variables, respectively. Sort the values by id_product. Print the product prices (price) before the results.The first rows of the resulting table should look like this:STORE_NAME CATEGORY PRODUCT_NAME PRICE CATEGORY_ACCUM STORE_ACCUMFour milk Borden Super Chox Chocolate Drink, 1 gal 2.38 2.38 2.38Four milk Fairlife 2% Chocolate Reduced Fat Milk, 52 oz 3.16 5.54 5.54Four milk Мoo-Moo Select Ingredients Fat Free Milk, 1 gal 2.28 7.82 7.82