See attached
Python / Jupyter – Assignment 2 Assignment 2.1 - Scalar variables, templating and datetimes¶ · create the following variables: sales = "9589220.12" commission_rate = "0.13456999" · Convert sales to a float, and print it as a string with a preceeding $ sign and comman separation every 000s using the as_currency function. Drop the values after the decimal place. · Convert commission_rate to a float, and print it as a string followed by the % sign with 3 decimal places. Assignment 2.2 - Lists · Create a list caled travel_destinations with the following elements: Italy, France, Australia, Germany, China · Create a new list of only the 4th and 5th list entries · Add South Africa to travel_destinations as the first entry · Remove Germany from the list travel_destinations · Sort the list travel_destinations into reverse alphabetical order Assignment 2.3 - Dictionaries¶ · Create a dictionary with the following names (as the keys) and their ranking (as the value) · Soccer: 1 · Football: 3 · Tennis: 7 Basketball: 2 · Add the key:value of Rugby:9 to this list · Remove the entry for Football. · Assignment 2.4 - Operators · Find the investment value of $250 invested at a 3 percent return over 10 years. · Format your results using the as_currency function with 2 decimal places. · Using a country list with the elements Italy, France, Australia, Germany, China - Generate a boolean (True or False) to see if Bulgaria is in the list - Generate a boolean (True of False) to see if China is in the list Assignment 2.5 - Math functions on scalars and lists · Create a list with the values corrsponding to years of experience of members of your analytics team. experience = [4, 7, 23, 9, 10] · Among the math functions .prod(x), .log(x), .sqrt(x), which can accept the variable x as the experience list? · Comment on why any error messages occur · Assignment 2.6 - Statistic functions on lists · import the file daily_adjusted_IVV.csv, and convert the close column to a list. · Calculate the mean, standard deviation and quartiles from this list · Verify your calculations by also performing them in Excel timestamp,open,high,low,close,adjusted_close,volume,dividend_amount,split_coefficient 1/7/2021,377.4711,381.26,377.28,380.47,380.47,6051650,0,1 1/6/2021,371.02,378.37,370.46,374.92,374.92,4343066,0,1 1/5/2021,369.44,373.83,369.44,372.67,372.67,4310505,0,1 1/4/2021,376.69,376.82,366.16,370.22,370.22,7103724,0,1 12/31/2020,373.2,376.04,372.6,375.39,375.39,4713052,0,1 12/30/2020,373.74,374.4309,372.95,373.3,373.3,2727467,0,1 12/29/2020,375.15,375.4,372.2,372.81,372.81,5401585,0,1 12/28/2020,373.15,373.94,372.44,373.53,373.53,2335819,0,1 12/24/2020,369.42,370.36,368.8098,370.31,370.31,2040697,0,1 12/23/2020,369.6301,370.955,368.7,368.88,368.88,3234329,0,1 12/22/2020,369.49,369.67,367.42,368.56,368.56,3441988,0,1 12/21/2020,366.3,370.14,363.38,369.27,369.27,5221646,0,1 12/18/2020,372.36,372.48,368.36,370.49,370.49,6697564,0,1 12/17/2020,371.69,372.195,369.8745,371.96,371.96,6485616,0,1 12/16/2020,369.62,370.91,368.625,369.9,369.9,5512871,0,1 12/15/2020,367.14,369.35,365.69,369.31,369.31,8472663,0,1 12/14/2020,368.44,369.57,364.21,364.35,364.35,3797572,1.6102,1 12/11/2020,366.27,367.93,364.615,367.62,366.002475,4501555,0,1 12/10/2020,366.75,369.214,365.811,368.08,366.460451,3151144,0,1 12/9/2020,372.28,372.42,367.325,368.28,366.659571,3758194,0,1 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