+
+
+
+
+
+
+zawarkhan_khi_R_Assignment2.R
+Zawar.Khan
+Mon Mar 27 15:38:31 2017
+ +#install.packages("lubridate")
+#install.packages("varhandle")
+#install.packages("data.table")
+#install.packages("plyr")
+#install.packages("reshape2")
+#install.packages("dplyr")
+
+library(lubridate)##
+## Attaching package: 'lubridate'## The following object is masked from 'package:base':
+##
+## datelibrary(varhandle)
+library(data.table)##
+## Attaching package: 'data.table'## The following objects are masked from 'package:lubridate':
+##
+## hour, isoweek, mday, minute, month, quarter, second, wday,
+## week, yday, yearlibrary(reshape2)##
+## Attaching package: 'reshape2'## The following objects are masked from 'package:data.table':
+##
+## dcast, meltlibrary(plyr)##
+## Attaching package: 'plyr'## The following object is masked from 'package:lubridate':
+##
+## herelibrary(dplyr)## -------------------------------------------------------------------------## data.table + dplyr code now lives in dtplyr.
+## Please library(dtplyr)!## -------------------------------------------------------------------------##
+## Attaching package: 'dplyr'## The following objects are masked from 'package:plyr':
+##
+## arrange, count, desc, failwith, id, mutate, rename, summarise,
+## summarize## The following objects are masked from 'package:data.table':
+##
+## between, first, last## The following objects are masked from 'package:lubridate':
+##
+## intersect, setdiff, union## The following objects are masked from 'package:stats':
+##
+## filter, lag## The following objects are masked from 'package:base':
+##
+## intersect, setdiff, setequal, unionds <- read.csv("D:/Python_R_Ass2/hospitaldata.csv",header=TRUE, sep=",")
+
+#Q1
+names(ds) <- gsub( ".", "", names(ds), fixed = TRUE)
+summary(ds)## Date id Time
+## Monday, January 02, 2017 : 11 Min. : 1.00 : 20
+## Wednesday, February 08, 2017: 7 1st Qu.: 37.25 1:00PM : 9
+## Friday, March 03, 2017 : 6 Median : 80.50 1:30PM : 9
+## Monday, February 06, 2017 : 6 Mean : 77.42 12:00PM: 9
+## Monday, January 09, 2017 : 6 3rd Qu.:118.00 3:00PM : 9
+## Thursday, January 26, 2017 : 6 Max. :155.00 - : 8
+## (Other) :180 (Other):158
+## Age Sex ConsultingDoctor Specialty
+## 30 : 20 : 12 Dr Alaf Khan :70 Dentist :103
+## : 19 -: 2 Nursing Staff :41 : 41
+## 26 : 11 f: 1 Dr Qurat ul Ain :22 M/o : 15
+## 40 : 11 F:102 Dr Riffat Naheed:14 Psychotherapist : 14
+## - : 9 M:105 Dr Ali :12 Gynae : 13
+## 17 : 9 Dr Fakiha :12 Child Specialist: 11
+## (Other):143 (Other) :51 (Other) : 25
+## Procedure TotalCharges AmountReceived AmountBalance
+## Consultation:84 500 :36 Min. : 50 : 4
+## X Ray :15 1000 :35 1st Qu.: 500 - :211
+## Injection :12 1500 :18 Median : 1000 14,000.00: 1
+## Pharmacy :11 :16 Mean : 2778 22,000.00: 1
+## Extraction :10 2000 :16 3rd Qu.: 2000 3,000.00 : 2
+## Crown : 7 300 :16 Max. :38000 500 : 1
+## (Other) :83 (Other):85 NA's :19 90,000.00: 2
+## AmountReceivedBy AmountinHospital ReceptionistName
+## : 24 Min. : 50 Haris :96
+## 150 Mrs Shamsa, 300 Dr Ammad : 1 1st Qu.: 300 Saima :45
+## Brig Farrukh : 7 Median : 500 Fiza :25
+## Dilshad : 1 Mean : 2212 Mona :22
+## Dr Ammad :125 3rd Qu.: 1600 :17
+## Dr Saniya : 4 Max. :38000 Sohaib : 6
+## Mrs Shamsa : 60 NA's :30 (Other):11
+## NextApt
+## :205
+## 2/16/2017: 2
+## 2/6/2017 : 2
+## 1/16/2017: 1
+## 1/19/2017: 1
+## 1/20/2017: 1
+## (Other) : 10#=======================================================
+#Q2
+date_in<-as.character(ds$Date)
+date_in<-strsplit(date_in,",")
+week<-list()
+for(i in 1:length(date_in)){
+ week[i]<-date_in[[i]][1]
+}
+week<-unlist(week,recursive=FALSE)
+max_week<-max(table(week))
+max_week## [1] 51#=======================================================
+#Q3 Average age of Patient
+ds$Age<- as.character(ds$Age)
+ds$Age<-gsub("-","0",ds$Age)
+ds$Age<-gsub("M","",ds$Age)
+ds$Age[ds$Age==""]<-"0"
+ds$Age<- as.double(ds$Age)
+ds$Age[is.na(ds$Age)] <- 0
+mean(as.numeric(ds$Age),na.rm=TRUE)## [1] 28.46396#ds$Age[ds$Age==" "] <- as.numeric(NA)
+#=======================================================
+#Q4 No of Children entertained
+sum(ds$Age >= 1 & ds$Age <= 12,na.rm = TRUE)## [1] 24#=========================================================
+#Q6 which doctor is earning the highest
+ds$ConsultingDoctor <- as.character(ds$ConsultingDoctor)
+ds$TotalCharges <- as.character(ds$TotalCharges)
+ds$TotalCharges[ds$TotalCharges=="Cancelled"]<-"0"
+ds$TotalCharges[ds$TotalCharges==""]<-"0"
+ds$TotalCharges[ds$TotalCharges=="nan"]<-"0"
+ds$TotalCharges<-as.double(ds$TotalCharges)
+aggregate(ds$TotalCharges, by=list(Category=ds$ConsultingDoctor), FUN=sum)## Category x
+## 1 Brig Asif 2800
+## 2 Brig Farrukh 3750
+## 3 Col Ulfat Ellahi 1000
+## 4 Dr Alaf Khan 513050
+## 5 Dr Ali 26100
+## 6 Dr Ammad 1400
+## 7 Dr Ammara 1500
+## 8 Dr Fakiha 22600
+## 9 Dr Irfan 11000
+## 10 Dr Kinza Alam 76700
+## 11 Dr Mehwish 1000
+## 12 Dr Mumtaz 1000
+## 13 Dr Paul 1500
+## 14 Dr Qurat ul Ain 20900
+## 15 Dr Riffat Naheed 18800
+## 16 Dr Saad 52000
+## 17 Dr Saad Riaz 5700
+## 18 Dr Saima Shams 1500
+## 19 Dr Saniya 4000
+## 20 Dr Shireen 3200
+## 21 Dr Waqar Azeem 6000
+## 22 Dr Zubair 1700
+## 23 Nursing Staff 9150#===========================================================================
+#Q5 which gender have what kind of procedure in abundance
+ds$Sex <- as.character(ds$Sex)
+ds$Sex <- gsub( "-", "NA", ds$Sex)
+ds$Sex <- gsub( " ", "NA", ds$Sex)
+ds$Sex <- gsub( ",", "NA", ds$Sex)
+ds$Sex<-gsub("f","F",ds$Sex)
+ds$Procedure <- as.character(ds$Procedure)
+ds$Sex <- gsub( "-", "NA", ds$Sex)
+ds$Sex <- gsub( " ", "NA", ds$Sex)
+ds$Sex <- gsub( ",", "NA", ds$Sex)
+counts1 <- ddply(ds, .(ds$Procedure[ds$Sex=='M'], ds$Procedure), nrow)## Warning in cbind(`ds$Procedure` = structure(c(6L, 23L, 8L, 8L, 8L, 6L,
+## 8L, : number of rows of result is not a multiple of vector length (arg 2)counts2 <- ddply(ds, .(ds$Procedure[ds$Sex=='F'], ds$Procedure), nrow)## Warning in cbind(`ds$Procedure` = structure(c(6L, 23L, 8L, 8L, 8L, 6L,
+## 8L, : number of rows of result is not a multiple of vector length (arg 2)names(counts1) <- c("Gender", "Procedure", "Freq")
+names(counts2) <- c("Gender", "Procedure", "Freq")
+counts1## Gender Procedure Freq
+## 1 <NA> Consultation 1
+## 2 Consultation+X Ray 1
+## 3 <NA> Consultation 1
+## 4 8 Unit Bridge+2 R.C.T X Ray 1
+## 5 <NA> Consultation 1
+## 6 BSR Consultation+X Ray 1
+## 7 <NA> 1
+## 8 <NA> 4 Unit Bridge 1
+## 9 <NA> Cancelled 1
+## 10 Consultation Consultation 32
+## 11 Consultation Consultation + USG 1
+## 12 <NA> Consultation+Retain 1
+## 13 <NA> Consultation+USG 1
+## 14 Consultation Consultation+X Ray 4
+## 15 Consultation Crown 3
+## 16 Consultation Dressing 3
+## 17 <NA> Er Retain 1
+## 18 Consultation Extraction 3
+## 19 Consultation Filling + X Rays 1
+## 20 <NA> Injection 3
+## 21 Consultation Laboratory Test 1
+## 22 <NA> Medicine 1
+## 23 <NA> Operation 1
+## 24 Consultation Pharmacy 5
+## 25 Consultation R.C.T 3
+## 26 Consultation RCT (4 teeth) Bridge (9 teeth) 1
+## 27 Consultation Scalling 3
+## 28 <NA> Scalling+Polishing 1
+## 29 <NA> Stiches 1
+## 30 <NA> USG 2
+## 31 <NA> USG Abdomen 1
+## 32 Consultation X Ray 6
+## 33 Consultation + Dressing C Section 1
+## 34 <NA> Consultation 1
+## 35 <NA> Injection 1
+## 36 <NA> Consultation 1
+## 37 Consultation + Nebulize Pharmacy 1
+## 38 <NA> Operation 1
+## 39 Consultation+ER Retain R.P.D + Crown 1
+## 40 Consultation+Retain Denture+Scalling+Filling 1
+## 41 <NA> Injection 1
+## 42 Consultation+X Ray Consultation 4
+## 43 <NA> Consultation + Nebulize 1
+## 44 Consultation+X Ray Filling 1
+## 45 Consultation+X Ray Pharmacy 1
+## 46 <NA> R.C.T+Scalling+Crown 1
+## 47 Consultation+X Ray RCT (4 teeth) Bridge (9 teeth) 1
+## 48 Crown 1
+## 49 Crown Consultation 9
+## 50 <NA> R.C.T 1
+## 51 Crown R.P.D + Crown 1
+## 52 Dressing 1
+## 53 Dressing C Section 1
+## 54 <NA> Consultation 1
+## 55 <NA> Consultation+x Ray 1
+## 56 <NA> Extraction 1
+## 57 Dressing Filling 1
+## 58 <NA> Injection 2
+## 59 Dressing Pharmacy 2
+## 60 <NA> R.C.T+Crown 1
+## 61 Er Retain Consultation 2
+## 62 <NA> Consultation 1
+## 63 Extraction Crown 1
+## 64 Extraction X Ray 2
+## 65 Filling Consultation 1
+## 66 Filling Filling 1
+## 67 <NA> Injection 1
+## 68 <NA> X Ray 1
+## 69 <NA> 1
+## 70 <NA> 8 Unit Bridge+2 R.C.T 1
+## 71 Injection Consultation 4
+## 72 Injection Consultation+ER Retain 1
+## 73 <NA> Coupety 1
+## 74 Injection Crown 1
+## 75 <NA> Dressing 1
+## 76 Injection Extraction 1
+## 77 <NA> Injection 1
+## 78 Injection Pharmacy 1
+## 79 <NA> R.C.T+Scalling+Crown 1
+## 80 Injection Scalling 1
+## 81 <NA> USG KUB 1
+## 82 Injection X Ray 2
+## 83 Laboratory Test Consultation 3
+## 84 Laboratory Test Consultation + X Ray 1
+## 85 Laboratory Test Extraction 1
+## 86 <NA> Scalling 1
+## 87 Operation 22 Unit Bridge 1
+## 88 Operation Consultation 1
+## 89 <NA> Orthodontics 1
+## 90 <NA> USG 1
+## 91 Pop Laboratory Test 1
+## 92 <NA> R.C.T 1
+## 93 <NA> Consultation 1
+## 94 <NA> Dressing 1
+## 95 <NA> Injection 1
+## 96 R.C.T Laboratory Test 1
+## 97 R.C.T Orthodontics 1
+## 98 R.C.T RCT 1
+## 99 R.C.T+Scalling+Crown Consultation 2
+## 100 RCT Consultation + Dressing 1
+## 101 <NA> Crown 1
+## 102 <NA> 22 Unit Bridge 1
+## 103 RCT (4 teeth) Bridge (9 teeth) Consultation 1
+## 104 RCT (4 teeth) Bridge (9 teeth) Laboratory Test 1
+## 105 <NA> Orthodontics 1
+## 106 Scalling Consultation 1
+## 107 Scalling Consultation+Denture 1
+## 108 <NA> Extraction 1
+## 109 Scalling Polishing 1
+## 110 <NA> X Ray 2
+## 111 Scalling+Polishing Consultation 1
+## 112 <NA> Injection 1
+## 113 <NA> BSR 1
+## 114 Stiches Consultation 1
+## 115 USG Consultation 1
+## 116 <NA> Extraction 1
+## 117 <NA> Consultation 1
+## 118 USG Abdomen Extraction 1
+## 119 USG KUB Consultation 1
+## 120 <NA> Crown 1
+## 121 <NA> 4 Unit Bridge 1
+## 122 X Ray Consultation 11
+## 123 X Ray Consultation+ECG 1
+## 124 <NA> Dressing 1
+## 125 <NA> Extraction 1
+## 126 <NA> Filling 1
+## 127 <NA> Injection 1
+## 128 X Ray Laboratory Test 1
+## 129 X Ray Pharmacy 1
+## 130 <NA> Pop 1
+## 131 X Ray Scalling 1
+## 132 <NA> USG 1
+## 133 <NA> X Ray 1counts2## Gender Procedure Freq
+## 1 Consultation 2
+## 2 <NA> Consultation+USG 1
+## 3 <NA> Dressing 1
+## 4 <NA> Er Retain 1
+## 5 <NA> R.C.T 1
+## 6 X Ray 1
+## 7 22 Unit Bridge Consultation 2
+## 8 <NA> Injection 1
+## 9 22 Unit Bridge R.P.D + Crown 1
+## 10 4 Unit Bridge Pharmacy 1
+## 11 <NA> R.C.T+Crown 1
+## 12 <NA> R.C.T+Scalling+Crown 1
+## 13 4 Unit Bridge Scalling 1
+## 14 C Section C Section 1
+## 15 C Section Consultation 1
+## 16 <NA> Coupety 1
+## 17 <NA> Extraction 2
+## 18 <NA> Injection 1
+## 19 Consultation 3
+## 20 <NA> 4 Unit Bridge 2
+## 21 <NA> BSR 1
+## 22 Consultation C Section 1
+## 23 <NA> Cancelled 1
+## 24 Consultation Consultation 42
+## 25 Consultation Consultation + X Ray 1
+## 26 Consultation Consultation + USG 1
+## 27 <NA> Consultation+x Ray 1
+## 28 Consultation Consultation+X Ray 2
+## 29 Consultation Crown 3
+## 30 Consultation Denture+Scalling+Filling 1
+## 31 Consultation Dressing 3
+## 32 <NA> Extraction 1
+## 33 Consultation Filling 2
+## 34 Consultation Filling + X Rays 1
+## 35 <NA> Injection 4
+## 36 Consultation Laboratory Test 4
+## 37 <NA> Operation 2
+## 38 Consultation Orthodontics 2
+## 39 Consultation Pharmacy 4
+## 40 <NA> Pop 1
+## 41 <NA> R.C.T 1
+## 42 <NA> R.C.T+Scalling+Crown 1
+## 43 Consultation R.P.D + Crown 1
+## 44 Consultation RCT 1
+## 45 <NA> Scalling 1
+## 46 <NA> Scalling+Polishing 1
+## 47 <NA> USG 3
+## 48 <NA> USG Abdomen 1
+## 49 <NA> USG KUB 1
+## 50 Consultation X Ray 6
+## 51 <NA> Consultation 1
+## 52 Consultation + X Ray Consultation + Dressing 1
+## 53 Consultation + USG Consultation 1
+## 54 <NA> Crown 1
+## 55 Consultation+Denture Consultation 1
+## 56 <NA> Consultation+Retain 1
+## 57 <NA> Injection 1
+## 58 Consultation+ECG Scalling 1
+## 59 <NA> X Ray 1
+## 60 Consultation+USG Extraction 1
+## 61 <NA> Stiches 1
+## 62 Consultation+x Ray Extraction 1
+## 63 <NA> Injection 1
+## 64 Consultation+X Ray Consultation 2
+## 65 <NA> Dressing 1
+## 66 Consultation+X Ray Pharmacy 1
+## 67 <NA> Consultation 1
+## 68 Coupety Filling 1
+## 69 Crown Extraction 1
+## 70 <NA> Medicine 1
+## 71 Denture+Scalling+Filling Pharmacy 1
+## 72 <NA> X Ray 1
+## 73 <NA> 1
+## 74 <NA> 22 Unit Bridge 1
+## 75 Extraction Consultation 6
+## 76 Extraction Consultation+X Ray 1
+## 77 <NA> Extraction 1
+## 78 <NA> Injection 1
+## 79 Extraction Pharmacy 2
+## 80 Extraction Polishing 1
+## 81 <NA> Scalling 2
+## 82 Extraction X Ray 1
+## 83 Filling Consultation 3
+## 84 <NA> Consultation + Nebulize 1
+## 85 <NA> Injection 1
+## 86 Filling + X Rays Consultation 1
+## 87 <NA> X Ray 1
+## 88 Injection Consultation 2
+## 89 <NA> Consultation+X Ray 1
+## 90 Injection R.C.T 1
+## 91 Injection Scalling 1
+## 92 <NA> X Ray 1
+## 93 Laboratory Test Consultation 4
+## 94 <NA> R.C.T 1
+## 95 <NA> 8 Unit Bridge+2 R.C.T 1
+## 96 Orthodontics Consultation 3
+## 97 <NA> Extraction 1
+## 98 <NA> Orthodontics 1
+## 99 Pharmacy Consultation 1
+## 100 <NA> Filling 1
+## 101 Polishing Consultation 1
+## 102 <NA> Consultation+X Ray 1
+## 103 R.C.T 22 Unit Bridge 1
+## 104 R.C.T Crown 1
+## 105 <NA> Injection 1
+## 106 <NA> X Ray 1
+## 107 R.C.T+Crown Consultation+ECG 1
+## 108 <NA> Dressing 1
+## 109 <NA> Injection 1
+## 110 R.C.T+Scalling+Crown Pharmacy 1
+## 111 <NA> Consultation 3
+## 112 R.P.D + Crown Consultation+Denture 1
+## 113 R.P.D + Crown Extraction 1
+## 114 <NA> Consultation 1
+## 115 Scalling Laboratory Test 1
+## 116 Scalling Pharmacy 1
+## 117 <NA> R.C.T 1
+## 118 Scalling RCT (4 teeth) Bridge (9 teeth) 1
+## 119 <NA> USG 1
+## 120 USG Consultation 3
+## 121 USG Consultation+ER Retain 1
+## 122 <NA> Extraction 1
+## 123 USG X Ray 1
+## 124 X Ray Consultation 3
+## 125 <NA> Consultation+X Ray 1
+## 126 X Ray Crown 2
+## 127 X Ray RCT (4 teeth) Bridge (9 teeth) 1
+## 128 <NA> X Ray 1counts11 <- ds$Procedure[ds$Sex=='M']
+counts22 <- ds$Procedure[ds$Sex=='F']
+cat("Male:","Consultaion has",max(table(counts11)))## Male: Consultaion has 37cat("Female:","Consultaion has",max(table(counts22)))## Female: Consultaion has 46#===========================================================================
+#Q7
+#ds$Procedure <- unfactor(ds$Procedure)
+#ds$TotalCharges <- unfactor(ds$TotalCharges)
+#ds$TotalCharges[is.na(ds$TotalCharges)] <- 0
+k<-aggregate(ds$TotalCharges, by=list(Category=ds$Procedure), FUN=sum)
+k## Category x
+## 1 21000
+## 2 22 Unit Bridge 69500
+## 3 4 Unit Bridge 11000
+## 4 8 Unit Bridge+2 R.C.T 30000
+## 5 BSR 50
+## 6 C Section 65000
+## 7 Cancelled 0
+## 8 Consultation 83950
+## 9 Consultation + X Ray 3000
+## 10 Consultation + Dressing 5000
+## 11 Consultation + Nebulize 1150
+## 12 Consultation + USG 1500
+## 13 Consultation+Denture 1500
+## 14 Consultation+ECG 1300
+## 15 Consultation+ER Retain 2800
+## 16 Consultation+Retain 3500
+## 17 Consultation+USG 1500
+## 18 Consultation+x Ray 650
+## 19 Consultation+X Ray 4750
+## 20 Coupety 300
+## 21 Crown 20000
+## 22 Denture+Scalling+Filling 5500
+## 23 Dressing 2900
+## 24 Er Retain 300
+## 25 Extraction 14600
+## 26 Filling 6500
+## 27 Filling + X Rays 2600
+## 28 Injection 1800
+## 29 Laboratory Test 0
+## 30 Medicine 100
+## 31 Operation 50000
+## 32 Orthodontics 240000
+## 33 Pharmacy 900
+## 34 Polishing 500
+## 35 Pop 3700
+## 36 R.C.T 15500
+## 37 R.C.T+Crown 8000
+## 38 R.C.T+Scalling+Crown 9500
+## 39 R.P.D + Crown 11000
+## 40 RCT 3000
+## 41 RCT (4 teeth) Bridge (9 teeth) 48000
+## 42 Scalling 16500
+## 43 Scalling+Polishing 4000
+## 44 Stiches 700
+## 45 USG 5500
+## 46 USG Abdomen 1000
+## 47 USG KUB 1000
+## 48 X Ray 5800#==========================================================================
+#Q8 Which time of the day has highest frequency of visits by hour
+ds$Time<-as.POSIXct(ds$Time,format="%H:%M %p")
+time_hr<-hour(ds$Time)
+table(time_hr)## time_hr
+## 1 2 3 4 5 6 7 8 9 10 11 12
+## 29 20 20 15 16 23 14 8 7 10 11 20#============================================================
+#Q9Create a bracket of time by Morning, Afternoon, Evening, Night
+time_hr<-hour(ds$Time)
+List1 <- assign("list", NULL, envir = .GlobalEnv)
+List1[time_hr >=06 & time_hr <= 12] <- "Morning"
+List1[time_hr > 12 & time_hr <= 16] <- "Afternoon"
+List1[time_hr > 16 & time_hr <= 19] <- "Evening"
+List1[time_hr > 19 & time_hr < 06] <- "Night "
+ds <- mutate(ds, List1)
+ds$List1## [1] NA "Morning" "Morning" NA NA NA NA
+## [8] NA NA NA NA NA NA NA
+## [15] "Morning" "Morning" "Morning" "Morning" "Morning" "Morning" NA
+## [22] NA "Morning" NA NA NA "Morning" NA
+## [29] "Morning" NA NA NA NA NA NA
+## [36] "Morning" NA NA NA NA NA "Morning"
+## [43] NA NA "Morning" NA "Morning" NA "Morning"
+## [50] "Morning" NA NA "Morning" "Morning" "Morning" "Morning"
+## [57] NA NA "Morning" "Morning" "Morning" NA NA
+## [64] NA "Morning" NA NA NA "Morning" NA
+## [71] NA "Morning" NA NA NA NA NA
+## [78] NA NA NA NA "Morning" NA NA
+## [85] NA NA NA NA "Morning" "Morning" NA
+## [92] NA NA NA NA "Morning" NA "Morning"
+## [99] "Morning" NA NA NA NA "Morning" "Morning"
+## [106] NA NA NA "Morning" NA NA "Morning"
+## [113] "Morning" NA NA NA "Morning" "Morning" NA
+## [120] NA "Morning" "Morning" "Morning" "Morning" "Morning" NA
+## [127] NA NA "Morning" "Morning" "Morning" "Morning" "Morning"
+## [134] NA NA "Morning" "Morning" "Morning" "Morning" NA
+## [141] "Morning" NA NA NA "Morning" "Morning" NA
+## [148] "Morning" NA NA "Morning" "Morning" "Morning" "Morning"
+## [155] NA NA NA NA "Morning" "Morning" NA
+## [162] "Morning" "Morning" "Morning" NA NA NA NA
+## [169] NA NA NA NA "Morning" NA NA
+## [176] "Morning" "Morning" NA "Morning" "Morning" NA NA
+## [183] "Morning" NA "Morning" NA "Morning" "Morning" "Morning"
+## [190] NA "Morning" NA "Morning" "Morning" NA NA
+## [197] NA NA NA NA NA "Morning" NA
+## [204] NA NA "Morning" NA "Morning" "Morning" "Morning"
+## [211] NA "Morning" "Morning" "Morning" "Morning" "Morning" NA
+## [218] NA NA "Morning" "Morning" "Morning"#==========================================================
+#Q10
+ds$id <- as.double(ds$id)
+ds$id## [1] 101 150 58 75 97 101 26 149 20 72 54 149 120 120 20 40 134
+## [18] 86 114 155 45 4 38 130 97 50 78 1 48 79 116 45 67 36
+## [35] 17 84 1 57 119 145 92 63 63 63 45 145 70 88 40 42 7
+## [52] 106 22 88 52 17 17 136 27 71 12 127 82 103 31 1 1 1
+## [69] 131 101 145 144 37 135 59 130 104 98 102 59 1 73 116 125 1
+## [86] 1 1 129 85 147 1 140 39 124 8 51 152 21 115 109 153 62
+## [103] 111 142 117 140 100 133 44 35 150 118 114 49 126 141 17 12 60
+## [120] 140 41 87 132 132 13 109 109 153 43 5 14 123 137 91 23 154
+## [137] 112 81 15 112 9 2 113 4 19 118 94 64 29 66 107 108 30
+## [154] 94 55 132 68 80 99 94 151 53 11 94 64 100 16 6 33 89
+## [171] 13 47 80 128 93 143 56 96 65 96 90 151 139 107 28 46 25
+## [188] 24 140 46 114 3 138 107 34 133 46 74 46 83 61 122 95 69
+## [205] 146 46 32 122 148 122 10 76 1 25 77 121 122 1 18 110 122
+## [222] 105num<-table(ds$id)
+num=num[num>1]
+length(num)## [1] 37#========================================================================
+#Q11
+ds$id <- as.double(ds$id)
+ds$id## [1] 101 150 58 75 97 101 26 149 20 72 54 149 120 120 20 40 134
+## [18] 86 114 155 45 4 38 130 97 50 78 1 48 79 116 45 67 36
+## [35] 17 84 1 57 119 145 92 63 63 63 45 145 70 88 40 42 7
+## [52] 106 22 88 52 17 17 136 27 71 12 127 82 103 31 1 1 1
+## [69] 131 101 145 144 37 135 59 130 104 98 102 59 1 73 116 125 1
+## [86] 1 1 129 85 147 1 140 39 124 8 51 152 21 115 109 153 62
+## [103] 111 142 117 140 100 133 44 35 150 118 114 49 126 141 17 12 60
+## [120] 140 41 87 132 132 13 109 109 153 43 5 14 123 137 91 23 154
+## [137] 112 81 15 112 9 2 113 4 19 118 94 64 29 66 107 108 30
+## [154] 94 55 132 68 80 99 94 151 53 11 94 64 100 16 6 33 89
+## [171] 13 47 80 128 93 143 56 96 65 96 90 151 139 107 28 46 25
+## [188] 24 140 46 114 3 138 107 34 133 46 74 46 83 61 122 95 69
+## [205] 146 46 32 122 148 122 10 76 1 25 77 121 122 1 18 110 122
+## [222] 105num<-table(ds$id)
+num=num[num>1]
+names(num)## [1] "1" "4" "12" "13" "17" "20" "25" "40" "45" "46" "59"
+## [12] "63" "64" "80" "88" "94" "96" "97" "100" "101" "107" "109"
+## [23] "112" "114" "116" "118" "120" "122" "130" "132" "133" "140" "145"
+## [34] "149" "150" "151" "153"#=======================================================================
+#Q12//
+countering1<-count(ds,id,Procedure)
+countering1<-countering1$id[countering1$n>1]
+countering1## [1] 1 12 13 17 17 20 25 45 46 63 80 94 97 101 109 112 114
+## [18] 116 122 130 140 145 151 153#========================================================================
+#Q13
+Male<-median(ds$Age[ds$Sex=="M"],na.rm=TRUE)
+Female<-median(ds$Age[ds$Sex=="F"],na.rm=TRUE)
+Male## [1] 27Female## [1] 30#=========================================================================
+#Q14
+ds$AmountBalance<- as.character(ds$AmountBalance)
+ds$AmountBalance<-gsub("-","0",ds$AmountBalance)
+ds$AmountBalance<-gsub(",","",ds$AmountBalance)
+ds$AmountBalance<-gsub(" ","",ds$AmountBalance)
+ds$AmountBalance[ds$AmountBalance==""]<-"0"
+ds$AmountBalance<- as.double(ds$AmountBalance)
+sum<-sum(ds$AmountBalance)
+sum## [1] 222500#==================================================
+#Q15
+#ds$Procedure <- unfactor(ds$Procedure)
+#ds$TotalCharges <- unfactor(ds$TotalCharges)
+money<-sum(ds$TotalCharges[ds$Procedure=="Consultation"],na.rm=TRUE)
+money## [1] 83950#==================================================
+#Q16
+#ds$TotalCharges <-as.double(ds$TotalCharges)
+ds$Age<-as.double(ds$Age)
+ds$Age[is.na(ds$Age)] <- 0
+ds$TotalCharges[is.na(ds$TotalCharges)] <- 0
+unique(ds$Age)## [1] 40 26 30 27 43 28 2 32 76 75 36 42 23 48 25 50 60 0 57 39 6 5 9
+## [24] 29 45 34 52 21 58 33 10 19 53 55 47 49 31 7 8 17 54 35 80 70 20 13
+## [47] 18 14 24 3 38 22 65 64 78 56print(cor(ds$Age,ds$TotalCharges))## [1] 0.06921013#===================================================
+#Q17 Age group had highest number of visits
+#ds$Age<-as.double(ds$Age)
+a<-names(which.max(table(ds$Age[ds$Age!=0])))
+a## [1] "30"hist(ds$Age)
#====================================================
+#Q18 total cost earned by Procedure Type X Ray and Scalling together
+#ds$TotalCharges<-unfactor(ds$TotalCharges)
+#ds$TotalCharges[is.na(ds$TotalCharges)] <- 0
+ds$Procedure<-as.character(ds$Procedure)
+sum(ds$TotalCharges[ds$Procedure=="X Ray"|ds$Procedure=="Scalling"])## [1] 22300#==================================================
+write.csv(ds,file = "update_hospitaldata.csv")
+#==================================================