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- PLZ help with the followng:bbhosted.cuny.edu/webapps/assessment/take/launch.jsp?course assessment_id=_1787700_1&course_ id3 1950256 1&content_id= 55349866 1&istep=Dnull ¥ Question Completion Status: Given a truth table below with the first two columns of truth values provided: b. f(p,a) 1 T 2 T 3 F 4 Which of the answers below contains the truth values for the third column when f(p,q) = (peq) →(q) ? Column 3 Column 3 truth values: Column 3 Column 3 truth values: Column 3 truth values truth truth values: values: 1 T 1 T 1 F 1 T None of the other 1 F O2 T O 2 F O answers provided is O 2 F 2 T correct. 2 T 3 F 3 T 3 F 3 T 3 F 4 T 4F 4 T 4 T 4 F Save All Answers Click Save and Submit to save and subnut. Chck Save All Answers to save all answers. Type here to search 6 66 F. F.Code in which following teem. .
- Mattings View Tell me what you w to do 165 M- AlloCel AaBbCd AaBbC AaBbce AaB ABCD ABOCED A08bCD AaBbCcD ABBCCD AnBbCcl B 1 Normal No low eping ding 1 Tile Suositte Subia Em Loginsess Qu 1 Q1) If y₁ =sin(x), y2 = cos(x), y₁ = tan(x), where -Q/ solue the equation [500] = [DI]°+BL +BH ÷ CX DI = 2000 H [DI] = 130 Bx = 148AH CX = 22 HConsider the following Employee table: ID Name Hire Date Address Salary *** 15/5/2010 Isa Town 20/6/2012 Hamad Town 5/6/1989 Zahra Town 1/10/2005 Salman Town 17/5/2017 Hessa Town Isa $4000.00 $3500.00 $6500.00 $9000.0 $4500.00 Hamad Zahra Salman Hessa Write a PUSQL program segment to retrieve the id, name, and Salary of the employees whose salaries greater than 4000 using an explicit cursor. Use the editor to format your answer 123 45Suppose Pep/9 contains the following four hexadecimal values: Only question #6.6. What function and formula was used in cell E13?a. =MEAN(E3:E12)b. =AVERAGE(E3:E12)c. =SUM(E3:E12)d. =TOTAL(E3:E12)What is the Manhattan distance between different points as shown below? Fill the table with appropriate Manhattan distances. As an example, the distance between points A and C is computed in the appropriate table cellHW7_3 Ball bearings are hardened through a process known as quenching-submersion of the heated ball bearing in oil or water in order to cool it rapidly. The data below represent the temperature of the ball at various points in the cooling process time (sec) 0 30 Temp (C) 800 457 269 79 46 60 150 240 Plot the data (as discrete points). In the same figure window, also plot a) interpolating polynomial, (use polyfit and polyval) b) piecewise cubic interpolation (not-a-knot) and c) piecewise cubic interpolation (shape-preserving) Include a legend for the three methods used: polynomial interpolation, not-a-knot, shape-preserving. Then looking at the plot, choose the method you believe to be the best and smoothest fit of all these to predict the temperature after 3 minutes of cooling. Print the result using fprintf.Use Python Code Your task is : Visualization of confirmed cases of COVID-19 by country . (Use pandas to read the data table csv. Example df = pd.read_csv('COVID19.csv' ) then make a visualization using that csv table) Province/State Country Lat Long ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## 2/1/2020 2/2/2020 2/3/2020 2/4/2020 2/5/2020 2/6/2020 2/7/2020 2/8/2020 2/9/2020 ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## 3/1/2020 3/2/2020 3/3/2020 3/4/2020 3/5/2020 3/6/2020 3/7/2020 3/8/2020 3/9/2020 ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## 4/1/2020 4/2/2020 4/3/2020 4/4/2020 4/5/2020 4/6/2020 4/7/2020 Afghanistan 33 65 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0…Use Python Code Your task is : Number of reported COVID-19 deaths by country. (Use pandas to read the csv table. Example : df = pd.read_csv('Covid19Deaths.csv') then do the code using the dataframe) COVID-19 Deaths table (csv): Province/State Country/Region Lat Long ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## 2/1/2020 2/2/2020 2/3/2020 2/4/2020 2/5/2020 2/6/2020 2/7/2020 2/8/2020 2/9/2020 ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## 3/1/2020 3/2/2020 3/3/2020 3/4/2020 3/5/2020 3/6/2020 3/7/2020 3/8/2020 3/9/2020 ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## ######## 4/1/2020 4/2/2020 4/3/2020 4/4/2020 4/5/2020 4/6/2020 4/7/2020 Afghanistan 33 65 0 0 0 0 0 0 0 0…SEE MORE QUESTIONS