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title: “Titanic Case study” author: “Raminder Singh” date: “February 3, 2018” output: html_document —write.csv(output, file = “output.csv”) setwd(‘C:/Users/v-ramins/Documents/Prof. Sameer Mathur/Data Analytics applications in Management/Titanic Case study’) Titanic <- read.csv(“Titanic Data.csv”) View(Titanic) library(psych) library(dplyr) library(data.table) SurvivorCount <- table(Titanic\(Survived) View(SurvivorCount) percentsurvival <- transform(as.data.frame(table(Titanic\)Survived)),percentage_column=Freq/nrow(Titanic\(Survived)*100) percentsurvivor <- (sum(Titanic\)Survived)/889)100 View(percentsurvivor) TitancDimsFirstClass <- Filter(Titanic, Pclass == ‘1’) describe(TitancDimsFirstClass) View(TitancDimsFirstClass) TitancDimsFirstClass <- Filter(Titanic, Pclass = 1) describe(TitancDimsFirstClass) View(TitancDimsFirstClass) TitancDimsFirstClass <- filter(Titanic, Pclass = 1) TitancDimsFirstClass <- filter(Titanic, Pclass == “1”) describe(TitancDimsFirstClass) View(TitancDimsFirstClass) TitancDimsFirstClass <- filter(Titanic, Pclass == “1” & Survived == “1”) describe(TitancDimsFirstClass) View(TitancDimsFirstClass) percentsurvivor1class <- (sum(TitancDimsFirstClass\(Survived)/889)*100 View(percentsurvivor1class) TitancDimsFirstClass <- filter(Titanic, Pclass == "1" ) describe(TitancDimsFirstClass) View(TitancDimsFirstClass) TitancDimsFirstClassSurvRate <- (134/214)*100 View(TitancDimsFirstClassSurvRate) TitancDimsFirstClassFemale <- filter(Titanic, Pclass == "1" & Sex == "female" ) describe(TitancDimsFirstClassFemale) View(TitancDimsFirstClassFemale) TitancDimsFirstClass <- filter(Titanic, Pclass == "1" ) describe(TitancDimsFirstClass) View(TitancDimsFirstClass) TitancDimsFirstClassSurv <- sum(TitancDimsFirstClass\)Survived) View(TitancDimsFirstClassSurv) TitancDimsFirstClassFemalesURV <- filter(Titanic, Pclass == “1” & Sex == “female” & Survived == “1”) View(TitancDimsFirstClassFemalesURV) percent1classfemalesurv <- (89/92)100 View(percent1classfemalesurv) View(SurvivorCount) SurvivorCountFemale <- filter(Titanic\(Sex == "female" & Titanic\)Survived == “1”) View(SurvivorCountFemale) SurvivorCountFemale <- filter(Titanic\(Sex == "female" & Titanic\)Survived == “1”) SurvivorCountFemaleintermediate <- filter(Titanic\(Sex == "female") SurvivorCountFemale <- filter(Titanic, Sex == "female" & Survived == "1") View(SurvivorCountFemale) percentfemaleSurv <- (231/340)*100 view(percentfemaleSurv) percentfemaleSurv <- (231/340)*100 view(percentfemaleSurv) percentfemaleSurv <- (231/340)*100 view(percentfemaleSurv) View(percentfemaleSurv) females <- filter(Titanic, Titanic\)Sex == “female”) View(females) femalesSurv <- filter(Titanic, Titanic\(Sex == "female" & Titanic\)Survived == “1”) View(femalesSurv) FemaleSurvivalRate <- (231/312)*100 View(FemaleSurvivalRate)