library(clustifyr) # calculate correlation res <- clustify( input pbmc_matrix_small, metadata = pbmc_meta$classified, cbmc_ref, ref_mat query_genes pbmc_vargenes ) # print assignments cor_to_call(res) #> # A tibble: 9 x 3 #> # Groups: cluster [9] #> cluster type r #> #> 1 B 0.909 #> 2 CD14+ Mono CD14+ Mono 0.915 #> 3 FCGR3A+ Mono CD16+ Mono 0.929 #> 4 Memory CD4 T CD4 T 0.861 #> 5 Naive CD4 T CD4 T 0.889 #> 6 DC DC 0.849 #> 7 Platelet Mk 0.732 #> 8 CD8 T NK 0.826 #> 9 NK NK 0.894 # plot assignments on a projection plot_best_call( cor_mat = res, metadata = pbmc_meta, cluster_col = "classified"

library(clustifyr) # calculate correlation res <- clustify( input pbmc_matrix_small, metadata = pbmc_meta$classified, cbmc_ref, ref_mat query_genes pbmc_vargenes ) # print assignments cor_to_call(res) #> # A tibble: 9 x 3 #> # Groups: cluster [9] #> cluster type r #> #> 1 B 0.909 #> 2 CD14+ Mono CD14+ Mono 0.915 #> 3 FCGR3A+ Mono CD16+ Mono 0.929 #> 4 Memory CD4 T CD4 T 0.861 #> 5 Naive CD4 T CD4 T 0.889 #> 6 DC DC 0.849 #> 7 Platelet Mk 0.732 #> 8 CD8 T NK 0.826 #> 9 NK NK 0.894 # plot assignments on a projection plot_best_call( cor_mat = res, metadata = pbmc_meta, cluster_col = "classified"

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

See similar textbooks

Similar questions

Split the column “category_name” into multiple columns without removing the original column. For example, a row with “Kids/Toys/Dolls & Accessories” in the category_name column, would be split across the newly created columns as “Kids”, “Toys” and “Dolls & Accessories”. Use the existing functionality in OpenRefine that creates multiple columns from an existing column based on a separator (i.e. in this case ‘/’). Provide the number of columns that are created in this operation. Remove the newly created columns that do not have values in all rows.
You are writing an application. You need a data structure that will allow you to store a large set of distinctive objects. The common operations performed on the set of objects are: lookup, insert, and delete. No traversal will be performed on the data set. The client wants the program to be as efficient as possible. Which of the following data structures should you use in your design? Question 25 options: hash table linked list heap binary search tree
Please check the instructions on the images given. Sample output are also given on the image while the code for modification is provided below. hash.c #include <stdlib.h>#include <stdio.h> struct Node { int val; struct Node * next;}; struct HashTable { int size; struct Node ** table;}; struct Node * create_node(int val);struct HashTable * create_table(int size);void destroy_table(struct HashTable * h);void display_table(struct HashTable *h);int hash_function(int key, int size);void insert(struct HashTable *h, int val);int search(struct HashTable * h, int val);struct Node * delete(struct HashTable * h, int val); void main(){struct HashTable * h = create_table(8);display_table(h); int val_insert[12] = {12, 31, 45, 83, 72, 29, 84, 39, 61, 24, 10, 50}; for (int i=0; i<12; i++) { insert(h,val_insert[i]);}display_table(h); int val_search[4] = {29, 99, 72, 20};for (int i=0; i<4; i++) { int result = search(h,val_search[i]); printf("Search value %2d:…
#ifndef NODES_LLOLL_H#define NODES_LLOLL_H #include <iostream> // for ostream namespace CS3358_SP2023_A5P2{ // child node struct CNode { int data; CNode* link; }; // parent node struct PNode { CNode* data; PNode* link; }; // toolkit functions for LLoLL based on above node definitions void Destroy_cList(CNode*& cListHead); void Destroy_pList(PNode*& pListHead); void ShowAll_DF(PNode* pListHead, std::ostream& outs); void ShowAll_BF(PNode* pListHead, std::ostream& outs);} #endif #include "nodes_LLoLL.h"#include "cnPtrQueue.h"#include <iostream>using namespace std; namespace CS3358_SP2023_A5P2{     // do breadth-first (level) traversal and print data void ShowAll_BF(PNode* pListHead, ostream& outs) { cnPtrQueue queue; CNode* currentNode; queue.push(pListHead->data); while (!queue.empty()) { currentNode = queue.front(); queue.pop(); if…
#ifndef NODES_LLOLL_H#define NODES_LLOLL_H #include <iostream> // for ostream namespace CS3358_SP2023_A5P2{ // child node struct CNode { int data; CNode* link; }; // parent node struct PNode { CNode* data; PNode* link; }; // toolkit functions for LLoLL based on above node definitions void Destroy_cList(CNode*& cListHead); void Destroy_pList(PNode*& pListHead); void ShowAll_DF(PNode* pListHead, std::ostream& outs); void ShowAll_BF(PNode* pListHead, std::ostream& outs);} #endif #include "nodes_LLoLL.h"#include "cnPtrQueue.h"#include <iostream>using namespace std; namespace CS3358_SP2023_A5P2{     // do breadth-first (level) traversal and print data void ShowAll_BF(PNode* pListHead, ostream& outs) { cnPtrQueue queue; CNode* currentNode; queue.push(lloLLPtr->getHead()); while (!queue.empty()) { currentNode = queue.front(); queue.pop(); if…
Review concepts for VB.net: Please explain the following concepts (what they do and how to use them): -              dvgList.DataSource = query.ToList -              dgvList.CurrentCell = Nothing -              dgvList.Columns(“name”).HeaderText = “Student Name” -              dgvList.RowHeadersVisible = True or False
You are writing an application for the 911 dispacher office for a city. You need a data structure that will allow you to store all the residents' phone numbers and addresses. The common operations performed on the set of objects are: lookup an address based on the calling phone number. The client wants the program to be as efficient as possible. Which of the following data structures should you use in your design? Question 43 options: Hash table Binary search tree Heap Sorted linked List
orderdp.cpp: #include <fcntl.h> #include <stdlib.h> #include <unistd.h> #include <inttypes.h> #include "orders.h" item::item(uint16_t s, uint16_t q) : sku(s), quantity(q) { } item_list::item_list() : items(NULL), num_products(0) { } void item_list::add(const item& i) { items = (item**)realloc(items, (num_products+1)*sizeof(item*)); items[num_products] = new item(i); num_products++; } order::order(uint16_t o, std::string n) : order_id(o), customer_name(n) { } void order::addItem(const item& i) { product_items.add(i); } order** read_orders(const char* filename, uint16_t* num_orders) { int fd; fd = open(filename, O_RDONLY); int err = fd; if (err == -1) { return NULL; } read(fd, num_orders, sizeof(*num_orders)); order** orders = new order*[*num_orders]; for (int i=0; i<*num_orders; i++) { uint16_t order_id; uint16_t num_products; read(fd, &order_id,…
Sort results by reverse domain: Create a data category. Domain that depicts domain names, including a suitable compareTo() function where the natural order is in reverse domain name order. For example, cs.princeton.edu's mirror name is edu.princeton.cs. This is helpful for analysing site logs. Use s.split(".") to divide the string s into pieces separated by underscores. Create a client that takes normal input and displays the reverse domains in sorted order.
Create a random sized linked list of randomly generated integers. Insert 25 to 75 random integers in the inclusive range 0 to 100 into the linked list. Display the contents, the sum, the count, and average of the integers. Create a program named LastnameFirstname17.c, that does the following: Define a structure named node that stores a single integer and a pointer to another node. You may use the struct definition in linkedlist.c as a template to get started. Keep in mind that the data in the linkedlist.c example was a string implemented as a char[]. For this assignment, the data is an integer, just a single int. You may want to define a typedef to create alias' for the node structure and node pointer for convenience. Setup your program to generate random numbers. Import the necessary includes and seed the random function. Generate a random integer between 25 and 75, inclusive, this number will be the size of the linked list. The size of the linked list: int size = 25 + rand()…
nycflights13::flights Q4<- flights %>%filter(carrier == "JFK") %>%summarise(average_dist = mean(distance)%>%summarise(max_dist = max(average_dist))%>%group_by(Q4, month, day)%>%head(Q4[order(dat$month),(dat$day),(dat$max_dist)],n=5) *not pictured, I did upload, tidy verse, dplyr, and the nycflights13 libraries. Error: Incomplete expression: Q4<- flights %>% filter(carrier == "JFK") %>% summarise(average_dist = mean(distance)%>% summarise(max_dist = max(average_dist))%>% group_by(Q4, month, day)%>% head(Q4[order(dat$month),(dat$day),(dat$max_dist)],n=5) RStudio Question: I can't figure out what is wrong with my code. Could someone take a look at it? See below for what I am trying to do, my code and my error output. I am trying to find what 5 days of the year had the highest mean distance from JFK airport, using the nycflights13 library. I want to format it in month, day, andvmean distance.
True or FalseAn application works directly with a database, modifying rows, deleting rows, adding new rows, and so forth.