What will the following code generate?tech_stocks = {'META': 400, 'JPM': 300, 'Apple': 220}print(tech_stocks)A.A pandas series with three stocks, along with their pricesB.A pandas dictionary with three stocksC.A pandas DataFrame with three stocks along with their pricesD.A Python dictionary with three key/value pairs

What will the following code generate?portfolio_df = pd.DataFrame({'stock ticker symbols' : ['FB', 'TSLA', 'T'],'price per share [$]' : [20, 30, 40],'Number of stocks' : [1, 1, 1]})stocks_dollar_value = portfolio_df['price per share [$]'] * portfolio_df['Number of stocks']print('Total portfolio value = {}'.format(stocks_dollar_value.sum()))A.Total portfolio value = 90B.Total portfolio value = 100C.Total portfolio value = 2,400D.Total portfolio value = 600

What is the output of the following Python code:Codeimport numpy as npimport pandas as pddata={'name':['Alice','Bob','Ben'], 'order':[1,3,2], 'sector':['Sales','Finance','Marketing'] }df=pd.DataFrame(data)print(df)

What will be the output of the following Python code snippet?>>> a={1:"A",2:"B",3:"C"}>>> del amethod del doesn’t exist for the dictionarydel deletes the values in the dictionarydel deletes the entire dictionarydel deletes the keys in the dictionary

NameError Traceback (most recent call last)Cell In[13], 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=np.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 'groupby' is not defined

in python, how to find the highest number in a DataFrame for different stocks