SALESMANColunns Data Constraints IGrants IStatstics Triggers IFlashback IDependendes Detals IParttons Indexes IsQ.XB Sort. Fiter:0 SNAME150 Tucker151 Bernstein152 Hall1530lsen154 Cambrault155 Tuvault156King157 Sully158 McEwenOSALESMAN ID0 COMMISSION O SALARY0.3 100000.25 250000.25 100000.2 159000.2 57000.15 5820ParisNew York(null)London(null)(null)(null)(null)(null)(null)(null)New YorkParisLondonParis5003 Lauson Hense ManilaRome23460.35 500000.35845015960.3 45200.3 100000.15 100000.13 100000.11 100000.14 458960.12 100000.13 156250.35159 Smith160 Doran5001 James Hoog5002 Nail Knife5005 Pit Alex5006 Mc Lyon10111213141516175007 Paul AdamSalesmanSALESMANColumns Deta (Constrants Grants IStatistics |Triggers IFlashback Dependencies Details Parbitions |Indexes |SQL* a- Actions..COLUMN NAMEI SALESMAN ID2 SNAME3CITYCOMMISSION5 SALARYl0 DATA TYPENUMBER (5,0)VARCHAR2 (30 BYTE)VARCHAR2 (15 BYTE)NUMBER (5,2)NUMBER (11,2)O NULLABLENoYesYesYesYesStructure of the salesman tableFigure 7.1Using figure 7.1, which among the following commands will you use to change the commission of the salesman?• deleteo update• select• insert into

Structured Query Language is used to store, manipulate and retrieve data from relational DBMS. The…

SALESMAN Colunns Data Constrants lerants istatstes ITrogers IFiashback lDeperdendes IDetals İPartons lindeses Isq X Sort. Fiter SALESMAN D 150 Tucker 151 Bernstein SNAME 0 COMMISSION SALARY 0.3 10000 0.25 25000 Paris New York (null) London (null) (null) (null) (null) (null) (null) (null) New York 2 152 Hall 1530lsen 154 Cambrault 155 Tuvault 156 King 157 Sully 158 McEwen 0.25 10000 0.2 15900 0.2 5700 0.15 5820 0.35 50000 4 0.35 8450 0.35 1596 159 Smith 160 Doran 5001 James Hoog 5002 Nail Knife 5005 Pit Alex 5006 Mc Lyon 5003 Lauson Hense Manila 5007 Paul Adam 0.3 4520 10 0.3 10000 0.15 10000 0.13 10000 0.11 10000 0.14 45896 11 12 Paris London Paris 13 14 15 0.12 10000 0.13 15625 16 17 Rome Salesman SALESMAN Solumrs Deta Corstrants lGrants IStatstca Triogers Fleshback Desendencies iDetais iPartitors lindexes ISQL Actors. COLUMN NAME 1 SALESMAN ID 2 SNAME 3CITY * COMMISSION 5 SALARY DATA TYPE NUMBER (5,0) VARCHAR2 (30 BYTE) VARCHAR2 (15 BYTE) NUMBER (5,2) NUMBER (11,2) O NULLABLE No Yes Yes Yes Yes Structure of the salesman table Figure 7.1 Using figure 7.1, which among the following commands will you use to change the commission of the salesman? delete o update select insert into

SALESMAN Colunns Data Constrants lerants istatstes ITrogers IFiashback lDeperdendes IDetals İPartons lindeses Isq X Sort. Fiter SALESMAN D 150 Tucker 151 Bernstein SNAME 0 COMMISSION SALARY 0.3 10000 0.25 25000 Paris New York (null) London (null) (null) (null) (null) (null) (null) (null) New York 2 152 Hall 1530lsen 154 Cambrault 155 Tuvault 156 King 157 Sully 158 McEwen 0.25 10000 0.2 15900 0.2 5700 0.15 5820 0.35 50000 4 0.35 8450 0.35 1596 159 Smith 160 Doran 5001 James Hoog 5002 Nail Knife 5005 Pit Alex 5006 Mc Lyon 5003 Lauson Hense Manila 5007 Paul Adam 0.3 4520 10 0.3 10000 0.15 10000 0.13 10000 0.11 10000 0.14 45896 11 12 Paris London Paris 13 14 15 0.12 10000 0.13 15625 16 17 Rome Salesman SALESMAN Solumrs Deta Corstrants lGrants IStatstca Triogers Fleshback Desendencies iDetais iPartitors lindexes ISQL Actors. COLUMN NAME 1 SALESMAN ID 2 SNAME 3CITY * COMMISSION 5 SALARY DATA TYPE NUMBER (5,0) VARCHAR2 (30 BYTE) VARCHAR2 (15 BYTE) NUMBER (5,2) NUMBER (11,2) O NULLABLE No Yes Yes Yes Yes Structure of the salesman table Figure 7.1 Using figure 7.1, which among the following commands will you use to change the commission of the salesman? delete o update select insert into

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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FIX THIS CODE Using python Application CODE: import csv playersList = [] with open('Players.csv') as f: rows = csv.DictReader(f) for r in rows: playersList.append(r) teamsList = [] with open('Teams.csv') as f: rows = csv.DictReader(f) for r in rows: teamsList.append(r) plays=len(playersList) for i in range(plays): if playersList[i]['team']=='Argentina' and int(playerlist[i]['minutes played'])<200 and int(playersList[i] ['shots'])>20: print(playersList[i]['last name']) c0=0 c1=0 c2=0 for i in range(len(teamsList)): if int(teamsList[i]['redCards'])==0: c0=c0+1 if int(teamsList[i]['redCards'])==1: c1=c1+1 if int(teamsList[i]['redCards'])==2: c2=c2+1 print("Number of teams with zero redcards:",c0) print("Number of teams with zero redcards:",c1) print("Number of teams with zero redcards:",c2) ratio=0 for i in range(len(teamsList)): if int(teamsList[i]['games']>3) and if int(teamsList[i]['goalsFor'])/int(teamsList[i]['goalsAgainst'])<ratio:…
I have the following JAVA CODE: deleteButton.addActionListener((e -> {int row= table.getSelectedRow();if (row>= 0) {String uName = (String) table.getValueAt(selectedRow, 0);JSONArray array= readJSONFile("sample.json");for (int i = 0; i < deleteArray.size(); i++) {JSONObject obj = (JSONObject) deleteArray.get(i);String username= (String) obj.get("username");if (uName.equals(currentUName)) {array.remove(i);tableModel.removeRow(row);break;}}}}));} Please make a code that will delete the details on the selected row on the JSON file.
1. Given the following hash function for storing records on courses:f(title) = ASCII value of first character in the title - 64Example: f(Biology I) = 66 – 65 = 1 (ASCII value of B is 66) a. Explain why this is or is not a good hash function.b. What improvement(s) could be made? 2. Assume that the hash function is: f(key) = key % Ba. What is the problem if B is too small?b. What is the problem if B is too large?c. What is the big-0 run-time if there are n records?d. What does the run-time for a find, insert, and delete each approach as B gets verylarge?
BY USING PYTHON The file100000 in question 2 is shown in question 1. QUESTION 2: Perform a benchmark analysis of the following searching methods:- Linear (Sequential) Search- Binary Search- Hashing Read the file “file100000” into a list. Sort the file using the one of fast sorting algorithms. You can use orderedSequentialSearch, binarySearch, and HashTable code given in https://runestone.academy/runestone/books/published/pythonds/SortSearch/toctree.html. Fill the hash table with key values stored in the file100000. The data values mapping to the key values can be assigned to a string like “Data” + str(key). Make the hash table size 10% bigger. For example you can set self.size = 110017 which is a prime number.Generate a list of 1000 random numbers using random.randint(0,100000). By using the searching methods, make a search of these random numbers. Record their total execution times into a file named “searchStats.txt”. The “searchStats.txt” file should contain entries for…
please update generateRandoms, letterToGrades, sumBetween, countCharacters //A6Utilities.java import java.io.IOException;import java.nio.file.Files;import java.nio.file.Paths;import java.security.SecureRandom;import java.util.List;import java.util.TreeMap;import java.util.function.Function;import java.util.stream.Collectors;public class A6Utilities {/*** Returns the corresponding letter grade. Don't modify this method, simply use it when converting single* grades to their equivalent letter grade** @param grade the integer grade to convert* @return the letter grade equivalent to the integer grade*/private static char letterGrade(final int grade) {if (grade < 0) return '?';else if (grade < 60) return 'F';else if (grade < 70) return 'D';else if (grade < 80) return 'C';else if (grade < 90) return 'B';else if (grade <= 100) return 'A';else return '?';}/*** The method uses Java Streams only. Don't use any looping structures, conditional statements are OK (IF, TERNARY,…
What does the following code segment and subroutine do? .equ SIZE =128.equ TABLE_L =$60.equ TABLE_H =$00 rjmp RESET .def A =r13.def B =r14.def cnt2 =r15.def cnt1 =r16.def endL =r17.def endH =r18 mystery: mov ZL,endLmov ZH,endHmov cnt2,cnt1i_loop: ld A,Z ld B,-Z cp A,B brlo L1 st Z,A std z+1,BL1: dec cnt2 brne i_loop dec cnt1 brne mystery ret Converts temperature values from one scale to another Adds a constant to a table of bytes Sorts numbers in ascending order Converts ASCII characters from lower case to upper case
import numpy as npimport matplotlib.pyplot as pltfrom sklearn.cluster import KMeansfrom sklearn.cluster import DBSCAN from sklearn.datasets import make_blobs n_samples = [750,750,750] cluster_std = 1 random_state = 200 X, Y_true = make_blobs(n_samples=n_samples, random_state=random_state, cluster_std=cluster_std) plt.scatter(X[:, 0], X[:, 1], marker='.', c=Y_true) #DBSCAN model, setting up required parameters eps = 0.4min_Samples = 10db = DBSCAN(eps=eps, min_samples=min_Samples).fit(X)labels = db.labels_labels # To count number of clusters in labels, ignoring noise if present.n_clusters_ = len(set(labels)) - (1 if -1 in labels else 0)n_noise_ = list(labels).count(-1) print('Estimated number of clusters: %d' % n_clusters_)print('Estimated number of noise points: %d' % n_noise_) # Plot result# Use black to label noise points.unique_labels = set(labels)colors = plt.cm.Spectral(np.linspace(0, 1, len(unique_labels))) core_samples_mask = np.zeros_like(db.labels_,…
Question 4 A ) Our List ADT supports: Group of answer choices all the collection operations indices iteration retrieving an element based on its key All of these are correct B )Our Collection ADT supports: Group of answer choices retrieval by priority storage of null first in first out access retrieving an element based on its key All of these are correct Full explain this question and text typing work only thanks All part solution send me
#The Iris Dataset import sklearn.datasetsimport matplotlib.pyplot as plt import numpy as np import scipy iris = sklearn.datasets.load_iris() Write a function that takes in an index i and prints out a verbose desciption of the species and measurements for data point i. For example:Data point 5 is of the species setosaIts sepal length (cm) is 5.4Its sepal width (cm) is 3.9Its petal length (cm) is 1.7Its petal width (cm) is 0.4
Retrieving a value using its associated key can be accomplished using anindexer, which works just like an indexer for an array. A key is passed in asthe index value, and the value associated with the key is returned, unless thekey doesn’t exist, in which a null is returned.Write short code segment demonstrates how this technique works:
Sort by reverse domain: Write a data type Domain that represents domain names,including an appropriate compareTo() method where the natural order is in order ofthe reverse domain name. For example, the reverse domain of cs.princeton.edu isedu.princeton.cs. This is useful for web log analysis. Hint: Use s.split("\\.") tosplit the string s into tokens, delimited by dots. Write a client that reads domain names from standard input and prints the reverse domains in sorted order
A search strategy that allows for immediate item access is. A search using binary digits B a search using linear data C a search using binary trees D a search using hash tables