R-Assignment-2/hifsa_isb_r_assignment2/R assignment 2.R at 0485034ec8cf1c79b551f081db80be1908d6eae6 · DataIntelligenceHub/R-Assignment-2 · GitHub

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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)