need help with Q4 {x}>Os✓ Q3:Take the minimum values (numpy function) in each array of q3 and create an array of those values. Assign it to Q3.[8] Q3 = np.min(array2d, axis=1)print (Q3)[0.08846017 0.31306644 0.1107879 0.20012361]( ) Start coding or generate with AI.Q▾ Q4:Assign the mean (numpy function) of all the q3 array values to Q4.import numpy as0.17810953074806235B✓ Oscompleted at 11:30 AMCreate an array with the following values: 2, 3, np.nan (this should represent a missing value), and 5. Use a numpof the values in this array. Assign the sum to Q5 (you should expect a numerical value here).<>VQ5:☑

Step 1: This has already been completed correctly by Q3! Using the np.min function with axis=1, or…

Answered: {x} > Os ✓ Q3: Take the minimum values…

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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//convert array of numbers from farenheit to celcius// example:// argument: [23, 32, 41, 50, 59]// return: [-5, 0, 5, 10, 15]// hint: use Array.mapfunction toCelcius(array){ } //write a function that takes an input array and returns an array of booleans (>=75) or fail (<75)// example:// argument: [20, 30, 50, 80, 90, 100]// return: [false, false, false, true, true, true]// hint: use Array.mapfunction passOrFail(array){ }
What does each line of code mean?
java - netbeans
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()
Q3: find the vector c=[2 5 6] from the array (A) [2 4 6 A = 5 5 7 3 6 6. 61
Xy---6. code.
Print the elements of the array ‘a’ using the mentioned notations: int a[]={1,2,3,4,5}; int *p; p = a; for (int i = 0; i< 5; i++) { //Subscript notation with name of array //Subscript notation with pointer 'p' //Offset notation using array name //Offset notation using pointer 'p' }
Programming language: Processing from Java Question attached as photo Topic: Use of Patial- Full Arrays
/*Code: Construct BST From Sorted ArraySend FeedbackGiven a sorted integer array A of size n, which contains all unique elements. You need to construct a balanced BST from this input array. Return the root of constructed BST.Note: If array size is even, take first mid as root.Input format:The first line of input contains an integer, which denotes the value of n. The following line contains n space separated integers, that denote the values of array.Output Format:The first and only line of output contains values of BST nodes, printed in pre order traversal.Constraints:Time Limit: 1 secondSample Input 1:71 2 3 4 5 6 7Sample Output 1:4 2 1 3 6 5 7 */public class SortedArrayToBst { /* Binary Tree Node class * * class BinaryTreeNode<T> { T data; BinaryTreeNode<T> left; BinaryTreeNode<T> right; public BinaryTreeNode(T data) { this.data = data; } } */…
Prompt: In Python language, wrte 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()
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Q: Write a program / Pseudo code / Algorithm that inserts the following numbers into two Separate arrays. L1 à 50 30 25 75 82 28 77 L2 à 50 40 25 75 80 21 37 30 After Insertion median should be calculated for each adjacent element from both array structures, after computing median print / Output that array M. if M is the median them M0 = (L1[0]+L2[0]) /2 M1 = (L1[1]+L2[1]) /2 …………..

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