library(dplyr)
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
Stu_Rollno=c(1:226)
Stu_name=c('A','B','C','A','B','B','C','G','F','F','F','G','G', 'F', 'F','A','B','A','B','C','G','F','F','F','G','G', 'F', 'F','A','B','A','B','C','G','F','F','F','G','G', 'F', 'F','A','B','A','B','C','G','F','F','F','G','G', 'F', 'F','A','B','A','B','C','G','F','F','F','G','G', 'F', 'F','A','B','A','B','C','G','F','F','F','G','G', 'F', 'F','A','B','A','B','C','G','F','F','F','G','G', 'F', 'F','A','B','A','B','C','G','F','F','F','G','G', 'F', 'F','A','B','A','B','C','G','F','F','F','G','G', 'F', 'F','A','B','A','B','C','G','F','F','F','G','G', 'F', 'F','A','B','A','B','C','G','F','F','F','G','G', 'F', 'F','A','B','A','B','C','G','F','F','F','G','G', 'F', 'F','A','B','C','G','F','F','F','G','G', 'F', 'F','A','B','C','G','F','F','F','G','G', 'F', 'F','A','B','C','G','F','F','F','G','G', 'F', 'F','F','A', 'B', 'C', 'G', 'F', 'F', 'F', 'G', 'G', 'F', 'F','A', 'B', 'C', 'G', 'F', 'F', 'F', 'G', 'G', 'F', 'F','A', 'B', 'C', 'G', 'F', 'F', 'F', 'G', 'G', 'F','G', 'F')
Stu_stop<-c("Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Periyar nagar","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam",
"Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram",
"Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri")
print("The Total Students Bus Allocation Details")
## [1] "The Total Students Bus Allocation Details"
df<-data.frame(Stu_Rollno,Stu_name,Stu_stop)
print(df)
## Stu_Rollno Stu_name Stu_stop
## 1 1 A Periyar nagar
## 2 2 B Periyar nagar
## 3 3 C Periyar nagar
## 4 4 A Periyar nagar
## 5 5 B Periyar nagar
## 6 6 B Periyar nagar
## 7 7 C Periyar nagar
## 8 8 G Periyar nagar
## 9 9 F Periyar nagar
## 10 10 F Periyar nagar
## 11 11 F Periyar nagar
## 12 12 G Periyar nagar
## 13 13 G Periyar nagar
## 14 14 F Periyar nagar
## 15 15 F Periyar nagar
## 16 16 A Periyar nagar
## 17 17 B Periyar nagar
## 18 18 A Periyar nagar
## 19 19 B Periyar nagar
## 20 20 C Periyar nagar
## 21 21 G Periyar nagar
## 22 22 F Periyar nagar
## 23 23 F Periyar nagar
## 24 24 F Periyar nagar
## 25 25 G Periyar nagar
## 26 26 G Periyar nagar
## 27 27 F Periyar nagar
## 28 28 F Periyar nagar
## 29 29 A Periyar nagar
## 30 30 B Periyar nagar
## 31 31 A Periyar nagar
## 32 32 B Periyar nagar
## 33 33 C Periyar nagar
## 34 34 G Periyar nagar
## 35 35 F Periyar nagar
## 36 36 F Periyar nagar
## 37 37 F Periyar nagar
## 38 38 G Periyar nagar
## 39 39 G Periyar nagar
## 40 40 F Periyar nagar
## 41 41 F Periyar nagar
## 42 42 A Periyar nagar
## 43 43 B Periyar nagar
## 44 44 A Periyar nagar
## 45 45 B Periyar nagar
## 46 46 C Tambaram
## 47 47 G Tambaram
## 48 48 F Tambaram
## 49 49 F Tambaram
## 50 50 F Tambaram
## 51 51 G Tambaram
## 52 52 G Tambaram
## 53 53 F Tambaram
## 54 54 F Tambaram
## 55 55 A Tambaram
## 56 56 B Tambaram
## 57 57 A Tambaram
## 58 58 B Tambaram
## 59 59 C Tambaram
## 60 60 G Tambaram
## 61 61 F Tambaram
## 62 62 F Tambaram
## 63 63 F Tambaram
## 64 64 G Tambaram
## 65 65 G Tambaram
## 66 66 F Tambaram
## 67 67 F Tambaram
## 68 68 A Tambaram
## 69 69 B Tambaram
## 70 70 A Tambaram
## 71 71 B Tambaram
## 72 72 C Tambaram
## 73 73 G Tambaram
## 74 74 F Tambaram
## 75 75 F Tambaram
## 76 76 F Tambaram
## 77 77 G Tambaram
## 78 78 G Tambaram
## 79 79 F Tambaram
## 80 80 F Tambaram
## 81 81 A Tambaram
## 82 82 B Tambaram
## 83 83 A Tambaram
## 84 84 B Tambaram
## 85 85 C Tambaram
## 86 86 G Arakkonam
## 87 87 F Arakkonam
## 88 88 F Arakkonam
## 89 89 F Arakkonam
## 90 90 G Arakkonam
## 91 91 G Arakkonam
## 92 92 F Arakkonam
## 93 93 F Arakkonam
## 94 94 A Arakkonam
## 95 95 B Arakkonam
## 96 96 A Arakkonam
## 97 97 B Arakkonam
## 98 98 C Arakkonam
## 99 99 G Arakkonam
## 100 100 F Arakkonam
## 101 101 F Arakkonam
## 102 102 F Arakkonam
## 103 103 G Arakkonam
## 104 104 G Arakkonam
## 105 105 F Arakkonam
## 106 106 F Arakkonam
## 107 107 A Arakkonam
## 108 108 B Arakkonam
## 109 109 A Arakkonam
## 110 110 B Arakkonam
## 111 111 C Arakkonam
## 112 112 G Arakkonam
## 113 113 F Arakkonam
## 114 114 F Arakkonam
## 115 115 F Arakkonam
## 116 116 G Arakkonam
## 117 117 G Arakkonam
## 118 118 F Arakkonam
## 119 119 F Arakkonam
## 120 120 A Arakkonam
## 121 121 B Arakkonam
## 122 122 A Arakkonam
## 123 123 B Arakkonam
## 124 124 C Arakkonam
## 125 125 G Arakkonam
## 126 126 F Arakkonam
## 127 127 F Arakkonam
## 128 128 F Arakkonam
## 129 129 G Arakkonam
## 130 130 G Arakkonam
## 131 131 F Arakkonam
## 132 132 F Arakkonam
## 133 133 A Arakkonam
## 134 134 B Arakkonam
## 135 135 A Arakkonam
## 136 136 B Kanchipuram
## 137 137 C Kanchipuram
## 138 138 G Kanchipuram
## 139 139 F Kanchipuram
## 140 140 F Kanchipuram
## 141 141 F Kanchipuram
## 142 142 G Kanchipuram
## 143 143 G Kanchipuram
## 144 144 F Kanchipuram
## 145 145 F Kanchipuram
## 146 146 A Kanchipuram
## 147 147 B Kanchipuram
## 148 148 A Kanchipuram
## 149 149 B Kanchipuram
## 150 150 C Kanchipuram
## 151 151 G Kanchipuram
## 152 152 F Kanchipuram
## 153 153 F Kanchipuram
## 154 154 F Kanchipuram
## 155 155 G Kanchipuram
## 156 156 G Kanchipuram
## 157 157 F Kanchipuram
## 158 158 F Kanchipuram
## 159 159 A Kanchipuram
## 160 160 B Kanchipuram
## 161 161 C Kanchipuram
## 162 162 G Kanchipuram
## 163 163 F Kanchipuram
## 164 164 F Kanchipuram
## 165 165 F Kanchipuram
## 166 166 G Kanchipuram
## 167 167 G Kanchipuram
## 168 168 F Kanchipuram
## 169 169 F Kanchipuram
## 170 170 A Kanchipuram
## 171 171 B Kanchipuram
## 172 172 C Kanchipuram
## 173 173 G Kanchipuram
## 174 174 F Kanchipuram
## 175 175 F Kanchipuram
## 176 176 F Kanchipuram
## 177 177 G Kanchipuram
## 178 178 G Kanchipuram
## 179 179 F Kanchipuram
## 180 180 F Kanchipuram
## 181 181 A Kanchipuram
## 182 182 B Ponneri
## 183 183 C Ponneri
## 184 184 G Ponneri
## 185 185 F Ponneri
## 186 186 F Ponneri
## 187 187 F Ponneri
## 188 188 G Ponneri
## 189 189 G Ponneri
## 190 190 F Ponneri
## 191 191 F Ponneri
## 192 192 F Ponneri
## 193 193 A Ponneri
## 194 194 B Ponneri
## 195 195 C Ponneri
## 196 196 G Ponneri
## 197 197 F Ponneri
## 198 198 F Ponneri
## 199 199 F Ponneri
## 200 200 G Ponneri
## 201 201 G Ponneri
## 202 202 F Ponneri
## 203 203 F Ponneri
## 204 204 A Ponneri
## 205 205 B Ponneri
## 206 206 C Ponneri
## 207 207 G Ponneri
## 208 208 F Ponneri
## 209 209 F Ponneri
## 210 210 F Ponneri
## 211 211 G Ponneri
## 212 212 G Ponneri
## 213 213 F Ponneri
## 214 214 F Ponneri
## 215 215 A Ponneri
## 216 216 B Ponneri
## 217 217 C Ponneri
## 218 218 G Ponneri
## 219 219 F Ponneri
## 220 220 F Ponneri
## 221 221 F Ponneri
## 222 222 G Ponneri
## 223 223 G Ponneri
## 224 224 F Ponneri
## 225 225 G Ponneri
## 226 226 F Ponneri
a=(df %>% count(Stu_stop))
print(a)
## Stu_stop n
## 1 Arakkonam 50
## 2 Kanchipuram 46
## 3 Periyar nagar 45
## 4 Ponneri 45
## 5 Tambaram 40
H<-c(50,46,45,45,40)
N<-c("Arakkonam","Kanchipuram","Periyarngr","Ponneri","Tambaram")
barplot(H,names.arg=N)
print(barplot)
## function (height, ...)
## UseMethod("barplot")
## <bytecode: 0x000001c811ecd7a8>
## <environment: namespace:graphics>
b=((a$n)/30)
c<-c(30,30,30,30,30)
Buses_required<-ceiling(b)
print("The Total Bus Required is allocated")
## [1] "The Total Bus Required is allocated"
df1 <- data.frame(a,b,Buses_required)
print(df1)
## Stu_stop n b Buses_required
## 1 Arakkonam 50 1.666667 2
## 2 Kanchipuram 46 1.533333 2
## 3 Periyar nagar 45 1.500000 2
## 4 Ponneri 45 1.500000 2
## 5 Tambaram 40 1.333333 2
area<-c("Arakkonam","Kanchipuram","Periyarngr","Ponneri","Tambaram")
km<-c(30,40,50,50,50)
bus_km<-data.frame(area,km,Buses_required)
Fuel_price<-c(100)
Milage<-c(10)
as.integer(Fuel_price)
## [1] 100
as.integer(Milage)
## [1] 10
dff<-data.frame(area,km,Buses_required,Fuel_price,Milage)
Fuel_needed=((dff$km)/10)
as.integer(Fuel_needed)
## [1] 3 4 5 5 5
df<-data.frame(area,km,Buses_required,Fuel_price,Milage,Fuel_needed)
Fuel_cost=((df$Fuel_needed)*100)
print("The Fuel Required is calculated(in ltrs)")
## [1] "The Fuel Required is calculated(in ltrs)"
data<-data.frame(area,km,Buses_required,Fuel_price,Milage,Fuel_needed,Fuel_cost)
Tot_Fuel_cost<-(data$Buses_required)*(data$Fuel_cost)
data<-data.frame(area,km,Buses_required,Fuel_price,Milage,Fuel_needed,Fuel_cost,Tot_Fuel_cost)
print(data)
## area km Buses_required Fuel_price Milage Fuel_needed Fuel_cost
## 1 Arakkonam 30 2 100 10 3 300
## 2 Kanchipuram 40 2 100 10 4 400
## 3 Periyarngr 50 2 100 10 5 500
## 4 Ponneri 50 2 100 10 5 500
## 5 Tambaram 50 2 100 10 5 500
## Tot_Fuel_cost
## 1 600
## 2 800
## 3 1000
## 4 1000
## 5 1000
z=sum(data$Fuel_needed)
cat("The Total Litres of fuel required",z)
## The Total Litres of fuel required 22
y=sum(data$Tot_Fuel_cost)
cat(". The Total Fuel .cost",y)
## . The Total Fuel .cost 4400
print("Today's Bus Required is allocated")
## [1] "Today's Bus Required is allocated"
Stu_Rollno2=c(1:129)
Stu_name2=c('A','B','C','G','F','F','F','G','G', 'F', 'F','C','G','F','F','F', 'F', 'F','C','G','F','F','F', 'F', 'F','C','G','F','F','F', 'F', 'F','C','G','F','F','F','G','G', 'F','G','F','F','G','F','F','F','G','G', 'F','G','F','F','F','G','G', 'F','F','G','G', 'F','G','F','F','F','G','G', 'F','G','F','F','F','G','G', 'F', 'F','C','G','F','F','F','G','G', 'F', 'F','C','G','F','F','F','G','G', 'F', 'F', 'F','A', 'B', 'C', 'G', 'F', 'F', 'F', 'G', 'G', 'F', 'F','A', 'B', 'C', 'G', 'F', 'F', 'F', 'G', 'G', 'F', 'F','A', 'B', 'C', 'G', 'F', 'F', 'F', 'G', 'G', 'F','G', 'F')
Stu_stop2<-c("Periyar nagar","Periyar nagar", "Periyar nagar", "Periyar nagar", "Periyar nagar", "Periyar nagar", "Periyar nagar", "Periyar nagar", "Periyar nagar", "Periyar nagar", "Periyar nagar", "Periyar nagar", "Periyar nagar", "Periyar nagar", "Periyar nagar", "Periyar nagar", "Periyar nagar", "Periyar nagar", "Periyar nagar", "Periyar nagar", "Periyar nagar", "Periyar nagar",
"Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam", "Arakkonam",
"Kanchipuram","Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram", "Kanchipuram",
"Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri", "Ponneri",
"Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram","Tambaram")
print("The Total Students Bus Details")
## [1] "The Total Students Bus Details"
df<-data.frame(Stu_Rollno2,Stu_name2,Stu_stop2)
print(df)
## Stu_Rollno2 Stu_name2 Stu_stop2
## 1 1 A Periyar nagar
## 2 2 B Periyar nagar
## 3 3 C Periyar nagar
## 4 4 G Periyar nagar
## 5 5 F Periyar nagar
## 6 6 F Periyar nagar
## 7 7 F Periyar nagar
## 8 8 G Periyar nagar
## 9 9 G Periyar nagar
## 10 10 F Periyar nagar
## 11 11 F Periyar nagar
## 12 12 C Periyar nagar
## 13 13 G Periyar nagar
## 14 14 F Periyar nagar
## 15 15 F Periyar nagar
## 16 16 F Periyar nagar
## 17 17 F Periyar nagar
## 18 18 F Periyar nagar
## 19 19 C Periyar nagar
## 20 20 G Periyar nagar
## 21 21 F Periyar nagar
## 22 22 F Periyar nagar
## 23 23 F Arakkonam
## 24 24 F Arakkonam
## 25 25 F Arakkonam
## 26 26 C Arakkonam
## 27 27 G Arakkonam
## 28 28 F Arakkonam
## 29 29 F Arakkonam
## 30 30 F Arakkonam
## 31 31 F Arakkonam
## 32 32 F Arakkonam
## 33 33 C Arakkonam
## 34 34 G Arakkonam
## 35 35 F Arakkonam
## 36 36 F Arakkonam
## 37 37 F Arakkonam
## 38 38 G Arakkonam
## 39 39 G Arakkonam
## 40 40 F Arakkonam
## 41 41 G Arakkonam
## 42 42 F Arakkonam
## 43 43 F Arakkonam
## 44 44 G Arakkonam
## 45 45 F Arakkonam
## 46 46 F Arakkonam
## 47 47 F Arakkonam
## 48 48 G Arakkonam
## 49 49 G Kanchipuram
## 50 50 F Kanchipuram
## 51 51 G Kanchipuram
## 52 52 F Kanchipuram
## 53 53 F Kanchipuram
## 54 54 F Kanchipuram
## 55 55 G Kanchipuram
## 56 56 G Kanchipuram
## 57 57 F Kanchipuram
## 58 58 F Kanchipuram
## 59 59 G Kanchipuram
## 60 60 G Kanchipuram
## 61 61 F Kanchipuram
## 62 62 G Kanchipuram
## 63 63 F Kanchipuram
## 64 64 F Kanchipuram
## 65 65 F Kanchipuram
## 66 66 G Kanchipuram
## 67 67 G Kanchipuram
## 68 68 F Kanchipuram
## 69 69 G Kanchipuram
## 70 70 F Kanchipuram
## 71 71 F Kanchipuram
## 72 72 F Kanchipuram
## 73 73 G Kanchipuram
## 74 74 G Kanchipuram
## 75 75 F Kanchipuram
## 76 76 F Kanchipuram
## 77 77 C Kanchipuram
## 78 78 G Kanchipuram
## 79 79 F Ponneri
## 80 80 F Ponneri
## 81 81 F Ponneri
## 82 82 G Ponneri
## 83 83 G Ponneri
## 84 84 F Ponneri
## 85 85 F Ponneri
## 86 86 C Ponneri
## 87 87 G Ponneri
## 88 88 F Ponneri
## 89 89 F Ponneri
## 90 90 F Ponneri
## 91 91 G Ponneri
## 92 92 G Ponneri
## 93 93 F Ponneri
## 94 94 F Ponneri
## 95 95 F Ponneri
## 96 96 A Ponneri
## 97 97 B Ponneri
## 98 98 C Ponneri
## 99 99 G Ponneri
## 100 100 F Ponneri
## 101 101 F Ponneri
## 102 102 F Ponneri
## 103 103 G Ponneri
## 104 104 G Ponneri
## 105 105 F Tambaram
## 106 106 F Tambaram
## 107 107 A Tambaram
## 108 108 B Tambaram
## 109 109 C Tambaram
## 110 110 G Tambaram
## 111 111 F Tambaram
## 112 112 F Tambaram
## 113 113 F Tambaram
## 114 114 G Tambaram
## 115 115 G Tambaram
## 116 116 F Tambaram
## 117 117 F Tambaram
## 118 118 A Tambaram
## 119 119 B Tambaram
## 120 120 C Tambaram
## 121 121 G Tambaram
## 122 122 F Tambaram
## 123 123 F Tambaram
## 124 124 F Tambaram
## 125 125 G Tambaram
## 126 126 G Tambaram
## 127 127 F Tambaram
## 128 128 G Tambaram
## 129 129 F Tambaram
a=(df %>% count(Stu_stop2))
print(a)
## Stu_stop2 n
## 1 Arakkonam 26
## 2 Kanchipuram 30
## 3 Periyar nagar 22
## 4 Ponneri 26
## 5 Tambaram 25
H1<-c(26,30,22,26,25)
N1<-c("Arakkonam","Kanchipuram","Periyarngr","Ponneri","Tambaram")
barplot(H1,names.arg=N1)
print(barplot)
## function (height, ...)
## UseMethod("barplot")
## <bytecode: 0x000001c811ecd7a8>
## <environment: namespace:graphics>
b=((a$n)/30)
c<-c(30,30,30,30,30)
Buses_required2<-ceiling(b)
print("The no of Bus Required is allocated")
## [1] "The no of Bus Required is allocated"
df1 <- data.frame(a,b,Buses_required2)
print(df1)
## Stu_stop2 n b Buses_required2
## 1 Arakkonam 26 0.8666667 1
## 2 Kanchipuram 30 1.0000000 1
## 3 Periyar nagar 22 0.7333333 1
## 4 Ponneri 26 0.8666667 1
## 5 Tambaram 25 0.8333333 1
area<-c("Arakkonam","Kanchipuram","Periyar_nagar","Ponneri","Tambaram")
km<-c(30,40,50,50,50)
bus_km<-data.frame(area,km,Buses_required2)
as.integer(Fuel_price)
## [1] 100
as.integer(Milage)
## [1] 10
dfff<-data.frame(area,km,Buses_required2,Fuel_price,Milage)
Fuel_needed2=((dfff$km)/10)
as.integer(Fuel_needed2)
## [1] 3 4 5 5 5
df<-data.frame(area,km,Buses_required2,Fuel_price,Milage,Fuel_needed2)
Fuel_cost2=((df$Fuel_needed2)*100)
print("The Fuel Required is calculated(in ltrs)")
## [1] "The Fuel Required is calculated(in ltrs)"
data<-data.frame(area,km,Buses_required2,Fuel_price,Milage,Fuel_needed,Fuel_cost2)
print(data)
## area km Buses_required2 Fuel_price Milage Fuel_needed Fuel_cost2
## 1 Arakkonam 30 1 100 10 3 300
## 2 Kanchipuram 40 1 100 10 4 400
## 3 Periyar_nagar 50 1 100 10 5 500
## 4 Ponneri 50 1 100 10 5 500
## 5 Tambaram 50 1 100 10 5 500
Tot_Fuel_cost1<-(data$Buses_required2)*(data$Fuel_cost2)
df<-data.frame(area,km,Buses_required2,Fuel_price,Milage,Fuel_needed2,Fuel_cost2,Tot_Fuel_cost1)
print(df)
## area km Buses_required2 Fuel_price Milage Fuel_needed2 Fuel_cost2
## 1 Arakkonam 30 1 100 10 3 300
## 2 Kanchipuram 40 1 100 10 4 400
## 3 Periyar_nagar 50 1 100 10 5 500
## 4 Ponneri 50 1 100 10 5 500
## 5 Tambaram 50 1 100 10 5 500
## Tot_Fuel_cost1
## 1 300
## 2 400
## 3 500
## 4 500
## 5 500
z2=sum(df$Fuel_needed)
cat("The Total Litres of fuel required",z2)
## The Total Litres of fuel required 22
y2=sum(df$Fuel_cost)
cat("The Total Fuel cost",y2)
## The Total Fuel cost 2200
mm=z-z2
cat("The Reduced fuel through the allocation is",mm)
## The Reduced fuel through the allocation is 0
mmm=y-y2
cat("The Reduced fuel through the allocation is",mmm)
## The Reduced fuel through the allocation is 2200
No comments:
Post a Comment
This "MONEY MINDED" blog is to improve your financial status and marketing knowledge. So always follow money minded and support to make all the post from money minded to become viral.
Don't hesitate to comment your doubts and opinions.we are waiting to reply your comments.