Saif_Khi_R_Assignment2

Saif_KHI_R_Assingnment.R

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+#Question 1)
+library("ggplot2")
+library("lubridate")
+library("dplyr")
+library(tidyr)
+library("DataCombine")
+hospitaldata <- read.csv("hospitaldata.csv")
+names(hospitaldata)<-gsub("..","",names(hospitaldata),fixed = TRUE)
+names(hospitaldata)<-gsub(".","_",names(hospitaldata),fixed = TRUE)
+View(hospitaldata)
+
+#removing character M from age i.e 28M
+hospitaldata$Age <- as.numeric(gsub("[^0-9]",'',hospitaldata$Age))
+
+#Question 2)
+hospitaldata$Date <- as.Date(strptime(hospitaldata$Date, "%a, %B %d, %Y"))
+
+Max_day <-  hospitaldata %>%
+  mutate(Day=weekdays(hospitaldata$Date),label=TRUE) %>%
+  group_by(Day) %>%
+  summarize(visits=length(Day)) %>%
+  print
+ggplot(Max_day,aes(x=Day,y=visits))+geom_bar(stat="identity",fill="slateblue")+ggtitle("Visits per Weekday")+labs(x="Day",y="Visits")
+
+#Question 3)
+mean(hospitaldata$Age, na.rm = TRUE)
+
+#Question 4)
+child <- filter(hospitaldata, Age > 1 & Age < 13) %>%
+  select(-(Date:Time)) %>%
+  select(-(Sex:Next_Apt)) %>%
+  count() %>%
+  print
+#Question 5)
+
+hospitaldata$Sex <- gsub("f","F",hospitaldata$Sex)
+hospitaldata$Sex<-gsub("\\s|-",NA,hospitaldata$Sex)
+qplot(data=hospitaldata, Sex, fill=Procedure)+ggtitle("Procedure vs Gender")+labs(x='Gender',y='Procedure')
+
+#Question 6)
+qplot(data=hospitaldata, fill=ConsultingDoctor, as.numeric(TotalCharges))+ggtitle("Highest Salary")+labs(x='TotalCharges',y='ConsultingDoctor')
+
+#Question 7)
+qplot(data=hospitaldata, as.numeric(TotalCharges), fill=Procedure)+ggtitle("Procedure")+labs(x='TotalCharges',y='Procedure')
+
+#Question 8)
+hour_and_visits <-  hospitaldata %>%
+  select(Time) %>%
+  mutate(Hour = hour(hm(format(strptime(hospitaldata$Time, "%I:%M %p"), "%H:%M")))) %>%
+  group_by(Hour) %>%
+  summarize(visits=length(Hour)) %>%
+  arrange(desc(visits)) %>%
+  print     # printing 13 the highest hour, i.e. actaully 1 AM/PM in 12 hour format
+
+#Question 9)
+
+
+#Question 10)
+visitor_repeated <- select(hospitaldata,id) %>%
+  group_by(id) %>%
+  summarise(visits=length(id)) %>%
+  arrange(desc(visits)) %>%
+  filter(visits > 1) %>%
+  print 
+
+#Question 11)
+
+visitor_repeated <- select(hospitaldata,id) %>%
+  group_by(id) %>%
+  summarise(visits=length(id)) %>%
+  arrange(desc(visits)) %>%
+  filter(visits > 1) %>%
+  print 
+
+#Question 12)
+
+hospitaldata %>% 
+  count(id, Procedure) %>%
+  slice(which(n>1))%>%
+  filter(!is.na(Procedure))%>%
+  select(id,Procedure)
+
+#Question 13)
+Age_median <- hospitaldata %>% 
+  select(Sex,Age) %>%
+  group_by(Sex) %>%
+  summarise(median(Age, na.rm = TRUE)) %>%
+  print
+
+#Question 14)
+hospitaldata$TotalCharges<-as.numeric(as.character(hospitaldata$TotalCharges))
+sum_of_Balance <- sum(hospitaldata$TotalCharges, na.rm = TRUE)
+print(sum_of_Balance)
+
+#Question 15)
+hospitaldata$TotalCharges<-as.numeric(as.character(hospitaldata$TotalCharges))
+consult_amount <- hospitaldata%>%
+  select(Procedure,TotalCharges) %>%
+  group_by(Procedure) %>%
+  filter(Procedure == 'Consultation') %>%
+  summarise(sum(TotalCharges,na.rm=TRUE)) %>%
+  print
+
+#Question 16)
+data <- hospitaldata %>%
+  select(Age,TotalCharges) %>%
+  filter(!is.na(Age),!is.na(TotalCharges))
+cor(data$Age,data$TotalCharges)
+
+#Question 17)
+Number_of_visits_by_age <- hospitaldata %>%
+  select(id,Age) %>%
+  group_by(Age) %>%
+  summarize(visits=length(Age)) %>%
+  arrange(desc(visits)) %>%
+  filter(!is.na(Age)) %>%
+  print
+
+ggplot(data=Number_of_visits_by_age,aes(x=as.numeric(Age),y=visits))+geom_bar(stat='identity',fill='slate blue')+ggtitle("Number Of Visits By Age")+labs(x='Age',y='Visits')
+
+
+#Question 18)
+
+sum(hospitaldata$TotalCharges[hospitaldata$Procedure=="X Ray" | hospitaldata$Procedure=="Scalling"],na.rm = TRUE)
+
+
+write.csv("~/hospitaldata.csv", row.names = FALSE)
+View(hospitaldata)