Albab-A-Khan_ISB_R_Assessment2

Albab-Ahmad-Khan_ISB_R_Assessment2/Albab-Ahmad-Khan_Islamabad_R_Assignment2.R

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+library (dplyr)
+library(tidyr)
+library(lubridate)
+
+# Question 1
+# Please remove the dots in the names, so it may become easier for you to work through it.
+hospitaldata <- read.csv("C:/Users/albab.ahmad/Desktop/Assessment 2/Albab-Ahmad-Khan_Rawalpindi_R_Assignment2/hospitaldata.csv")
+df = hospitaldata
+View(df)
+#names(df) <- gsub(x= "\\.", " ", names(df), fixed = TRUE)
+names(df) <- gsub(x= names(df), pattern = "\\.", replace = "")
+names(df)
+
+# Question 2
+# Which day of the week is expected to have most visits?
+xx <- tbl_df(df)
+df <- separate(df, Date, into = c("Day", "Date"), sep = ",", extra = "merge")
+new <- df %>% count(Day) %>%  slice(which.max(n))
+new
+
+# Question 3
+# What is the average age of patients?
+ages <- hospitaldata$Age
+gsub("-", "NA", ages) 
+df1= as.numeric(ages)
+class(df1)
+mean(df1, na.rm = TRUE)
+
+# Question 4
+# How many children were entertained? (Make a Bracket of Age from 1-12)
+four <- filter(df, df1< 12)
+count(four, na.rm = TRUE)
+
+# Question 5
+# Which gender type had what kind of procedure in abundance? i.e. Female visit mostly because of Gynae Problem
+df$Sex <- gsub("-", "", df$Sex)
+df$Sex <- as.character(Map({function (a) toupper(a)}, df$Sex))
+df %>%
+  filter(Sex != "") %>% 
+  group_by(Sex, Specialty)  %>%  
+  summarise(n=n()) %>%  
+  slice(which.max(n)) %>%  
+  arrange(desc(n))
+
+# Question 6 
+# Which Doctor is earning highest?
+View(df)
+df$TotalCharges <- as.numeric(df$TotalCharges)
+df %>%
+  filter(ConsultingDoctor != "") %>%
+  group_by(ConsultingDoctor)  %>%  
+  summarise(sum= sum(TotalCharges, na.rm = TRUE)) %>%  
+  slice(which.max(sum)) %>%  
+  arrange(desc(sum))
+
+# Question 7
+# Which procedure type earns more money?
+df %>%
+  filter(Procedure != "") %>%
+  group_by(Procedure)  %>%  
+  summarise(sum= sum(TotalCharges, na.rm = TRUE)) %>%  
+  slice(which.max(sum)) %>%  
+  arrange(desc(sum))
+
+# Question 8
+# Which time of the day has highest frequency of visits by hour?
+  gsub(x= df$Time, pattern = "-", replacement  = "")
+  #filter(df$Time != "") %>%
+  fulltime <- as.POSIXct(parse_date_time(df$Time, "%H:%M%p"))
+  hour(fulltime)
+
+  df %>% 
+    group_by(hour(fulltime)) %>% 
+    summarise(cnt = n()) %>% 
+    slice(which.max(cnt)) 
+
+#Question 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).
+  gsub(x= df$Time, pattern = "-", replacement  = "")
+  filter(df$Time != "") %>%
+  filter(is.na(df$Time)) %>%
+  fulltime <- as.POSIXct(parse_date_time(df$Time, "%H:%M%p"))
+  a <- hour(fulltime)
+
+  check <- function()
+  {
+    if ( findInterval(a, c(6:12))){ 
+      print("Morning")
+    }else if ( findInterval(a, c(12:16))) {
+      print ("Afternoon")
+    } else if ( findInterval(a, c(16:19))) {
+      print("Evening")
+    } else 
+      print("Night")
+  }
+check(24)
+check(1)
+
+# Question 10.
+#  How many patients are repeated visitors?
+  df %>%
+    group_by(id)  %>%  
+    summarise(n=n()) %>% 
+    filter(n>1) %>% 
+    count()
+
+# Question 11.
+# Give us the id of repeated visitors.
+x <- df %>%
+  group_by(id)  %>%  
+  summarise(n=n()) %>% 
+  filter(n>1) 
+  x$id
+
+# Question 12
+#  Which patients visited again for the same problem?
+  df %>%
+    group_by(id, Specialty) %>%
+    summarise(n=n()) %>%
+    filter(n>1)
+View(df)
+df$Age <- as.numeric(df$Age)
+
+#Question 13
+# What is the median age for Females and Males?
+  df %>%
+    filter(Sex != "") %>%
+    group_by(Sex) %>%        
+    summarise(Median = median(Age, na.rm=TRUE))
+
+# Question 14
+# What is the total amount in balance?
+df$AmountBalance <- as.character (df$AmountBalance)
+df$AmountBalance <- gsub(x= df$AmountBalance, pattern = "-", replacement = "")
+df$AmountBalance <-  gsub(x= df$AmountBalance, pattern = ",", replacement = "" )
+df$AmountBalance <- as.numeric(df$AmountBalance)
+sum(df$AmountBalance, na.rm=TRUE)
+
+#Question 15
+#How much money was made by Procedure Type "Consultation"?
+df$TotalCharges <- as.numeric(df$TotalCharges)
+df %>%
+    filter(Procedure == "Consultation") %>%
+    summarise(sum=sum(TotalCharges, na.rm = TRUE ))
+
+#Question 16
+# Is there a relation between Age and Total Charges paid?
+df$Age <- as.numeric(df$Age)
+df$TotalCharges <- as.numeric(df$TotalCharges)
+cor.test(x= df$Age, y= df$TotalCharges)
+
+#Question 17
+# Which Age group had highest number of visits?
+df %>%
+  group_by(Age) %>%
+  filter(Age != "NA") %>%
+  summarise(n=n()) %>%
+  slice(which.max(n))
+
+
+#Question 18
+#What is the total cost earned by Procedure Type X Ray and Scalling together?
+df %>%
+  filter(Procedure == 'X Ray'|  Procedure == 'Scalling' ) %>%
+  summarise(s=sum(TotalCharges, na.rm= TRUE))
+
+write.csv(df, file = "CleanDataset.csv")