PLEASE DO THIS IN PYTHON Part 4 - Performance of binary_search Modify your binary_search function to count the number of comparisons (==, <, <=, >, or >=). The function will now return both the number of comparisons made and the True or False result. The code below calls your function, and creates a simple ASCII bar chart of the number of comparisons (divided by 10, to account for small differences). Test Code max_elements = 100000 for length in range(1, max_elements, 10000): values = list(range(1, (2 * length) + 1, 2)) num_comparisons, found = binary_search(values, length + 1, 0, len(values) - 1) num_comparison_string = format(num_comparisons, '03d') print(num_comparison_string, '*' * (num_comparisons // 10))

In cell C18 type a VLOOKUP function to find the corresponding letter grade (from column D) for the name in A18. The table array parameter is the same as in B18. Type FALSE for the range lookup parameter. Copy the formula in C18 to C19:C22Notice this formula works correctly for all cells. Range lookup of FALSE means do an exact match on the lookup value whether or not the table array is sorted by its first column. In cell E11, type an IF function that compares the score in B11 with the minimum score to pass in A5. If the comparison value is true, display Pass. Otherwise, display Fail. Copy the formula in E11 to E12:E15. Did you use appropriate absolute and relative references so the formula copied properly? In cell F11, type an IF function that compares the grade in D11 with the letter F (type F). If these two are not equal, display Pass. Otherwise, display Fail. Copy the formula in F11 to F12:F15

Must be written in the coral language. Complete the PrintArray function to iterate over each element in dataValues. Each iteration should put the element to output. Then, put "*" to output. Ex: If dataValue's elements are 2 4 7, then output is: 2*4*7*

Python question Application: Big-O Notation (Q8-11)  For each of the time complexities in this segment give the tightest bound in terms of a simple polylogarithmic function using big-O notation. Note: use the ‘^’ symbol to indicate exponents, i.e., write O(n^2) for O(n2).   Question 8 (Big-O Notation 1) T(n) =  n2+ log n + n   Question 9 (Big-O Notation 2) T(n) = n/3 + 4 log n + 2n log(n)   Question 10 (Big-O Notation 3) T(n) = 7n5 + 2n   Question 11 (Big-O Notation 4) T(n) = (n%5) + 12,000

Prompt: In Python language, write a function that applies the logistic sigmoid function to all elements of a NumPy array. Code:   import numpy as np import math import matplotlib.pyplot as plt import pandas as pd   def sigmoid(inputArray):               modifiedArray = np.zeros(len(inputArray))               #YOUR CODE HERE:               return(modifiedArray) def test(): inputs = np.arange(-100, 100, 0.5) outputs = sigmoid(inputs) plt.figure(1) plt.plot(inputs) plt.title('Input') plt.xlabel('Index') plt.ylabel('Value') plt.show() plt.figure(2) plt.plot(outputs,'Black') plt.title('Output') plt.xlabel('Index') plt.ylabel('Value') plt.show() test()