Answered: Write an algorithim DELETE(A,N,POS) to…

Write an algorithim DELETE(A,N,POS) to delete an element at POS. You can use the following array to implement your algorithim {3,8,12,5,6} This can be pseudocode

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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Write the function lastOf which searches the array a for the last occurance of any value contained in the array b. Returns the index if found. If not found, return -1. arrays.cpp 1 #include 2 3 int lastof(const int a[), int alen, const int b[], int blen) 4 { int res = 0; for (int i = 0; i =0 ; j--) if (b[j] == a[i]) { if(res[1, 9, 4, 5, 1, 5, 1, 12, 8, 11, 2, 11, 7, 8] b1->[7, 5, 9] last0f(al, 14, b1, 3): -1 Expected: 12 al->[1, 9, 4, 5, 1, 5, 1, 12, 8, 11, 2, 11, 7, 8] b2->[7, 7] lastof (al, 14, b2, 2): -1 Expected: 12 a2->[3, 2, 1, 14, 10, 6, 13, 1ө, 11, 13, 14] b2->[7, 7] lastof (a2, 11, b2, 2): -1 Expected: -1 а2->[3, 2, 1, 14, 10, 6, 13, 1ө, 11, 13, 14] b1->[7, 5, 9] last0f (a2, 11, b1, 3): -1 Expected: -1 а2->[3, 2, 1, 14, 10, 6, 13, 10, 11, 13, 14] b3->[11, 2, 1, 15] lastof (a2, 11, b3, 4): -1 Expected: 8 Score 2/5
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In [ ]: We obtained an array with N = 10 values, scattered about mean of 25 (mm). Let's calculate the mean, standard deviation, standard deviation of the mean and 20-uncertainty SL of these numbers. In the following code, do these steps: • In the first cell, add a brief comment that explains what each statement does. Start each comment with a # sign. • In the second cell, delete the raise Not ImplementedError() code line and print the standard deviation and 20-uncertainty on the screen (follow the example for mean_L) mean_L = np.mean (L) print("Mean length: ", mean_L) stddev_L = np. std (L, ddof=1) stddev_mean_L = stddev_L/np.sqrt(N) uncertainty_L = 2*stddev_mean_L In [ ] V #YOUR CODE HERE raise NotImplementedError() #calculates the mean of L In the above code, the green expressions on the right hand side, such as np.mean, np. std and np.sqrt are functions built into the numpy package of Python. The names on the left hand side are variable names invented by me.
Note: Set a random seed of 100 for this assignment. All arrays should contain random numbers between 0 and 1 (zero is inclusive). Create a one-dimensional array of twenty float random numbers. Assign the sum of these values to Q1. Assign the max of these values to Q2. Create a four by five array of random numbers. Take the minimum values in each array and create an array of those values. Assign it to Q3. Assign the mean of all the array values to Q4. Create an array with the following values: 2, 3, np.nan (this should represent a missing value), and 5. Use a numpy function to find the sum of the values in this array. Assign the sum to Q5 (you should expect a numerical value here). Create two separate arrays each containing four random numbers. Concatenate the two arrays and assign it to Q6. Create a four by four array of random numbers and call it q7. Concatenate this array with itself and assign it to Q7. Create a two by four array of…