Python Project

 Task 1 (50 points): (Intro to Data Science: Survey Response Statistics) Twenty students were asked to rate on a scale of 1 to 5 the quality of the food in the student cafeteria, with 1 being “awful” and 5 being “excellent”. Place the 20 responses in a list. 1, 2, 5, 4, 3, 5, 2, 1, 3, 3, 1, 4, 3, 3, 3, 2, 3, 3, 2, 5 Write a program that does the following: (a) Determine and display the frequency of each rating. (b) Use the built-in functions, statistics module functions and NumPy or Panda functions covered in the course materials to display the following response statistics: minimum, maximum, range, mean, median, variance and standard deviation. (c) Display a bar chart showing the response frequencies and their percentages of the total responses. Grading Rubric – 10 points for defining functions. – 15 points for finishing Task1(a)-(c). – 5 points for appropriate comments. – 10 points for a runnable python program with correct data visualization. – 10 points for screenshots of the program. Task 2 (50 points): (Classification with k-Nearest Neighbors and the Digits Dataset) Read the file “09-02-MachineLearning.pdf” and the python program “” to learn the algorithm of k-Nearest Neighbors with the Digits dataset for recognizing handwritten digits. Re-write the python program by doing the following subtasks: (a) Write code to display the two-dimensional array representing the sample image at index 24 and numeric value of the digit the image represents. (b) Write code to display the image for the sample image at index 24 of the Digits dataset. (c) For the Digits dataset, what numbers of samples would the following statement reserve for training and testing purposes? X train, X test, y train, y test = 1 train test split(,, random state=11, test size=0.60) 2 (d) Write code to get and display these numbers. (e) Rewrite the list comprehension in snippet [50] using a for loop. Hint: create an empty list and then use the built-in function “append”. Grading Rubric – 15 points for finishing Task2(a)-(e). – 5 points for appropriate comments. – 20 points for a runnable rewritten python program – 10 points for screenshots of the program. 

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