Answered: How do I recode/convert values in a…

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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How do I recode/convert values in a data frame from non-numeric to binary "TRUE" "FALSE", in Rstudio

$R RStudio File Edit Code View Plots Session Build Debug Profile Tools Help A Go to file/function BA - Addins - R Project: (None) - O Project 5 Logistic Modeling.R* * Environment History Connections Tutor aO a A O Source on Save 9 required<-c("gtools") Run + Source - * Import Dataset - List - Global Environment- 10 11 installed<-installed. packages () [, 'Package'] Data 12 O wibc 699 obs. of 12 varia.m 13 for (pkg in required) 14 - { values if (!pkg %in% installed) { cat ("Installing package:", pkg, "\n") install.packages (pkg) } chr [1:699] "benign" ".. chr [1:699] "benign" ".. installed chr [1:113] "asserttha. 15 A 16 - class 17 18 pkg required "gtools" "gtools" 19 - 20 cat ("Loading package", pkg, "\n") require(pkg, character.onīy=TRUE) 21 sourcepir "" 22 23 - } 24 25 26 # load dataset 27 28 wibc<-read.csv("WI_breast_cancer.csv") 29 30 # let's see what the data look 1like 31 #3 32 head (wibc) str (wibc) 33 34 Files Plots Packages Help Viewer # recode categorical variables for use with glm procedure. Convert "malignant" to TRUE # and "benign" to FALSE. Copy data frame and add new "malignancy" column. class<-wibcsclass class 35 36 C Refresh 37 R: The F Distribution - Find in Topic 38 39 FDist {stats} R Documentation 40 # ADD YOUR CODE HERE n = 1 wibc2 = cbind (wibc,replicate(n,wibc$class)) wibc2 colnames (wibc2)<-c("x", "Id", "cl. thickness","cell.size","cell. shape","Marg. adhesion", "Epith.c.size","Bare.nuclei","B1.cromatin", "Normal.nucleoli", "Mitoses", "class", "malignancy") 41 42 The F Distribution 43 44 45 Description 46 head (wibc2) str(wihc2) 47 Density, distribution function, quantile function and random generation for the F distribution with dfl and df2 degrees of freedom (and optional non-centrality parameter ncp) 39:1 (Top Level) : R Script : Console Terminal x Jobs x + } Loading package gtools Loading required package: gtools > wibc<-read.csv("WI_breast_cancer.csv") # let's see what the data look 1ike > # > head (wibc) Usage df (x, df1, df2, ncp, log = FALSE) pf (g, df1, df2, ncp, gf (p, df1, df2, ncp, lower.tail = T! lower.tail = T! rf (n, df1, df2, ncp) Id cl.thickness cell.size cell.shape Marg. adhesion Epith.c.size Bare. nuclei B1.cromatin Normal.nucleoli Mitoses class Arguments 11 1000025 2 2 1002945 3 3 1015425 benign benign benign benign benign 1 malignant 10 1. 1 х, ч vector of quantiles. 4 4 1016277 8. 8 4 1. vector of probabilities. 5 5 1017023 6 6 1017122 > str (wibc) 'data. frame': $ X 4 1. 1. 1. 10 10 10 number of observations. If length (n) > 1, the length is taken to be the number 699 obs. of 12 variables: : int 1 2 3 4 5 6 7 8 9 10 ... 1000025 1002915 1015425 1016277 1017023 1017122 1018000 1018561 103307g 1033078$

Transcribed Image Text:R RStudio File Edit Code View Plots Session Build Debug Profile Tools Help A Go to file/function BA - Addins - R Project: (None) - O Project 5 Logistic Modeling.R* * Environment History Connections Tutor aO a A O Source on Save 9 required<-c("gtools") Run + Source - * Import Dataset - List - Global Environment- 10 11 installed<-installed. packages () [, 'Package'] Data 12 O wibc 699 obs. of 12 varia.m 13 for (pkg in required) 14 - { values if (!pkg %in% installed) { cat ("Installing package:", pkg, "\n") install.packages (pkg) } chr [1:699] "benign" ".. chr [1:699] "benign" ".. installed chr [1:113] "asserttha. 15 A 16 - class 17 18 pkg required "gtools" "gtools" 19 - 20 cat ("Loading package", pkg, "\n") require(pkg, character.onīy=TRUE) 21 sourcepir "" 22 23 - } 24 25 26 # load dataset 27 28 wibc<-read.csv("WI_breast_cancer.csv") 29 30 # let's see what the data look 1like 31 #3 32 head (wibc) str (wibc) 33 34 Files Plots Packages Help Viewer # recode categorical variables for use with glm procedure. Convert "malignant" to TRUE # and "benign" to FALSE. Copy data frame and add new "malignancy" column. class<-wibcsclass class 35 36 C Refresh 37 R: The F Distribution - Find in Topic 38 39 FDist {stats} R Documentation 40 # ADD YOUR CODE HERE n = 1 wibc2 = cbind (wibc,replicate(n,wibc$class)) wibc2 colnames (wibc2)<-c("x", "Id", "cl. thickness","cell.size","cell. shape","Marg. adhesion", "Epith.c.size","Bare.nuclei","B1.cromatin", "Normal.nucleoli", "Mitoses", "class", "malignancy") 41 42 The F Distribution 43 44 45 Description 46 head (wibc2) str(wihc2) 47 Density, distribution function, quantile function and random generation for the F distribution with dfl and df2 degrees of freedom (and optional non-centrality parameter ncp) 39:1 (Top Level) : R Script : Console Terminal x Jobs x + } Loading package gtools Loading required package: gtools > wibc<-read.csv("WI_breast_cancer.csv") # let's see what the data look 1ike > # > head (wibc) Usage df (x, df1, df2, ncp, log = FALSE) pf (g, df1, df2, ncp, gf (p, df1, df2, ncp, lower.tail = T! lower.tail = T! rf (n, df1, df2, ncp) Id cl.thickness cell.size cell.shape Marg. adhesion Epith.c.size Bare. nuclei B1.cromatin Normal.nucleoli Mitoses class Arguments 11 1000025 2 2 1002945 3 3 1015425 benign benign benign benign benign 1 malignant 10 1. 1 х, ч vector of quantiles. 4 4 1016277 8. 8 4 1. vector of probabilities. 5 5 1017023 6 6 1017122 > str (wibc) 'data. frame': $ X 4 1. 1. 1. 10 10 10 number of observations. If length (n) > 1, the length is taken to be the number 699 obs. of 12 variables: : int 1 2 3 4 5 6 7 8 9 10 ... 1000025 1002915 1015425 1016277 1017023 1017122 1018000 1018561 103307g 1033078

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