diff --git a/hifsa_isb_r_assignment2/R assignment 2.R b/hifsa_isb_r_assignment2/R assignment 2.R
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+library(plyr)
+library(dplyr)
+library(lubridate)
+library(tidyr)
+library(ggplot2)
+"1. removed the dots in the names"
+names(hospitaldata) <- gsub(x = names(hospitaldata),
+                        pattern = "\\.",
+                        replacement = " ")
+names(hospitaldata)
+
+"2. day of the week is expected to have most visits"
+df<-hospitaldata$Date
+df<-wday(mdy(df), label=TRUE)
+df
+table(df)
+
+"3. What is the average age of patients"
+nage<-as.numeric(hospitaldata$Age) 
+mean(nage, na.rm = TRUE)
+
+"4. How many children were entertained"
+age<-as.numeric(hospitaldata$Age)
+ages<-subset(age, age >= 1 & age < 12)
+length(ages)
+
+"5. Which gender type had what kind of procedure in abundance? 
+i.e. Female visit mostly because of Gynae Problem"
+select(group_by(hospitaldata, Procedure, Sex) ) %>%
+table() %>%
+  View()
+
+"6. Which Doctor is earning highest?"
+a<-hospitaldata$`Total  Charges`
+
+hospitaldata$`Consulting  Doctor`[which.max(a)]
+
+
+"7. Which procedure type earns more money?"
+max(a, na.rm = T, filter = c(hospitaldata$Procedure))
+
+"8. Which time of the day has highest frequency of visits by hour?"
+df2 <- hospitaldata$Time 
+gsub("-", "NA" ,df2)
+d<-hour(hm(format( s <- strptime(df2, "%I:%M %p" ), format = "%H:%M")))
+count(d)%>%
+  View()
+"9. Create a bracket of time by 
+Morning, Afternoon, Evening, Night 
+(6am - 12pm - Morning, 12 pm- 4 pm, 
+Afternoon, 4 pm- 7pm, Evening, 7pm - 6 am, Night)."
+
+"10. How many patients are repeated visitors?"
+b<- ddply(hospitaldata,.(id),nrow )
+repeated <-subset(b, b$V1>1)
+View(repeated)
+
+"11. Give us the id of repeated visitors."
+View(repeated)
+
+"12. Which patients visited again for the same problem"
+  problem <- ddply(hospitaldata,.(id, Specialty),nrow)
+    cv<- subset(problem,problem$V1>1)
+     View(cv)
+
+"13. What is the median age for Females and Males?"
+gsub("-", "NA" ,hospitaldata$Age)
+toupper(hospitaldata$Sex)
+fmed <- subset(hospitaldata, Sex=='F' , select = as.numeric(Age))
+median(fmed$Age, na.rm =T)
+mmed <- subset(hospitaldata, Sex=='M' , select = as.numeric(Age))
+median(mmed$Age, na.rm= T)
+
+"14. What is the total amount in balance?"
+g <- hospitaldata$`Amount  Balance` <- as.numeric(gsub('[,]', '', hospitaldata$`Amount  Balance`))
+sum(g, na.rm = T)
+
+"15. How much money was made by Procedure Type "Consultation"?"
+proct <- subset(hospitaldata, Procedure == "Consultation")
+sum(proct$`Total  Charges`, na.rm= T)
+
+"16. Is there a relation between Age and Total Charges paid?"
+d <-as.numeric(hospitaldata$Age)
+f <-as.numeric(hospitaldata$`Total  Charges`)
+cor.test(x=d,y=f)
+
+"17. Which Age group had highest number of visits?"
+z<- ddply(hospitaldata,.(id, Age),nrow )
+repeated1 <-subset(z, z$V1>1)
+repeated1
+View(repeated1)
+"18. What is the total cost earned by Procedure Type X Ray and Scalling together?"
+cost1 <- subset(hospitaldata, Procedure == "X Ray")
+cost2 <- subset(hospitaldata, Procedure == "Scalling")
+sum(cost1$`Total  Charges`,cost2$`Total  Charges`, na.rm= T)