submitting all questions

Hajra-Tanveer_Islamabad_r_assignment/Assignment_2_R.R

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+library(readr)
+library(dplyr)
+library(tidyr)
+library(lubridate)
+hospitaldata <- read_csv("~/Assignments/R_Assignments/Hajra-Tanveer_Islamabad_r_assignment/hospitaldata.csv")
+hospital_tbl <- tbl_df(hospitaldata)
+View(hospital_tbl)
+
+#Part 1: Remove "."
+names(hospital_tbl) <- gsub(".", " ", names(hospital_tbl), fixed = TRUE)
+
+#Part 2: Which day of the week is expected to have most visits?
+
+hospital_tbl <- hospital_tbl %>%
+  separate(Date, into =c("Day", "Date"), ",", extra = "merge")
+
+#Part 3: What is the average age of patients?
+#we will replace all month olds and - with NA 
+hospital_tbl[hospital_tbl == "-"] <- NA 
+#hospital_tbl$Age <- gsub(x = hospital_tbl$Age, pattern = "M | -", replacement = NA)
+#why does this ^ not work?!!!
+hospital_tbl$Age
+Filter_infants <- hospital_tbl%>%
+  filter(!grepl('M', Age))
+Filter_infants
+Non_infants <- as.numeric(Filter_infants$Age)
+avg_age <- mean(Non_infants, na.rm = TRUE)
+avg_age
+
+
+#Part4:How many children were entertained? (Make a Bracket of Age from 1-12)
+Filter_infants$Age <- as.numeric(Filter_infants$Age)
+Filter_infants%>%
+  filter(Age <= 12)%>%
+  count
+
+
+
+#Part5: Which gender type had what kind of procedure in abundance? 
+#i.e. Female visit mostly because of Gynae Problem
+hospital_tbl %>%
+  group_by(Sex, Specialty)%>%
+  summarise(count = n())%>%
+  arrange(desc(count))
+
+
+#Part6: Which Doctor is earning highest?
+hospital_tbl %>%
+  group_by(`Consulting  Doctor`)%>%
+  summarise(richest = sum(as.numeric(`Total  Charges`), na.rm = TRUE))%>%
+  arrange(desc(richest))
+
+#Part7:Which procedure type earns more money?
+hospital_tbl %>%
+  group_by(Procedure)%>%
+  summarise(richest = sum(as.numeric(`Total  Charges`), na.rm = TRUE))%>%
+  arrange(desc(richest))
+
+#Part8:Which time of the day has highest frequency of visits by hour?
+Time_tbl<- hospital_tbl
+Time_tbl$Time<-hour(strptime(Time_tbl$Time,"%H"))
+typeof(Time_tbl$Time)
+Time_tbl%>%
+  group_by(Time)%>%
+  summarise(count = n())
+#problem: we dont know if 1 AM or PM
+
+
+#Part9: Create a bracket of time by Morning, Afternoon, Evening, 
+#Night (6am – 12pm – Morning, 12 pm- 4 pm, Afternoon, 4 pm- 7pm, Evening, 
+#7pm – 6 am, Night).
+
+
+#Part10:How many patients are repeated visitors?
+hospital_tbl %>%
+  group_by(id)%>%
+  summarise(count=n())%>%
+  filter(count >1)%>%
+  count
+
+
+#Part11:Give us the id of repeated visitors
+hospital_tbl %>%
+  group_by(id)%>%
+  summarise(count=n())%>%
+  filter(count >1)
+
+
+#Part12: Which patients visited again for the same problem?
+hospital_tbl %>%
+  group_by(id,Specialty)%>%
+  summarise(count=n())%>%
+  filter(count >1)
+
+
+#Part13:What is the median age for Females and Males?
+females_ages<- Filter_infants%>%
+  filter(Sex == "F")
+median_females <- median(females_ages$Age, na.rm = TRUE)
+median_females
+males_ages<- Filter_infants%>%
+  filter(Sex == "M")
+median_males <- median(males_ages$Age, na.rm = TRUE)
+median_males
+
+#Part14:What is the total amount in balance?
+total_balance <- hospital_tbl
+total_balance$`Amount  Balance` <- as.numeric(sub(",", "", total_balance$`Amount  Balance`))
+sum(total_balance$`Amount  Balance`, na.rm = TRUE)
+
+#Part15:How much money was made by Procedure Type “Consultation”?
+hospital_tbl%>%
+  group_by(Procedure)%>%
+  summarise(total = sum(as.numeric(`Total  Charges`), na.rm = TRUE))%>%
+  filter(Procedure == "Consultation")
+
+#Part16:Is there a relation between Age and Total Charges paid?
+plot(Filter_infants$Age, Filter_infants$`Total  Charges`)
+cor.test(as.numeric(Filter_infants$Age), as.numeric(Filter_infants$`Total  Charges`), na.action=na.exclude)
+#no correlation
+
+
+#Part17:Which Age group had highest number of visits?
+Filter_infants$Age <- as.numeric(Filter_infants$Age)
+Filter_infants$Age <- round(Filter_infants$Age,-1)
+Filter_infants$Age
+Filter_infants%>%
+  group_by(Age)%>%
+  summarise(count_age_group = n())%>%
+  arrange(desc(count_age_group))%>%
+  print
+#ppl n their 30s had highest no. of visits
+
+
+#Part18:What is the total cost earned by Procedure Type X Ray and
+#Scalling together?
+Filter_infants%>%
+  group_by(Procedure)%>%
+  summarise(total_procedure= sum(as.numeric(`Total  Charges`),na.rm=TRUE))%>%
+  filter(Procedure == "X Ray" | Procedure == "Scalling")%>%
+  summarise(sum(total_procedure),na.rm=TRUE)%>%
+  print
+
+write.csv(hospital_tbl,"~/Assignments/R_Assignments/Hajra-Tanveer_Islamabad_r_assignment/CleanDataset.csv")
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