This presentation uses an exploratory dataset analysis on cars. This contains two files. The first file, cars_multi, contains information for the mpg, cylinders, displacement, horsepower, weight, acceleration, model, origin, and name of the car. The second file, cars_price, contains the price of every car in the dataframe according to their ID. For our purposes, these two dataframes must be merged into one.
Introduction
The Dataframe in Use
The merged dataframe can be created as such:
cars = read.csv('~/Downloads/cars_multi.csv', header=TRUE)
carsPrice = read.csv('~/Downloads/cars_price.csv', header=TRUE)
carsData <- merge(cars,carsPrice, by= "ID")
carsData
## ID mpg cylinders displacement horsepower weight acceleration model origin ## 1 1 18.0 8 307.0 130 3504 12.0 70 1 ## 2 2 15.0 8 350.0 165 3693 11.5 70 1 ## 3 3 18.0 8 318.0 150 3436 11.0 70 1 ## 4 4 16.0 8 304.0 150 3433 12.0 70 1 ## 5 5 17.0 8 302.0 140 3449 10.5 70 1 ## 6 6 15.0 8 429.0 198 4341 10.0 70 1 ## 7 7 14.0 8 454.0 220 4354 9.0 70 1 ## 8 8 14.0 8 440.0 215 4312 8.5 70 1 ## 9 9 14.0 8 455.0 225 4425 10.0 70 1 ## 10 10 15.0 8 390.0 190 3850 8.5 70 1 ## 11 11 15.0 8 383.0 170 3563 10.0 70 1 ## 12 12 14.0 8 340.0 160 3609 8.0 70 1 ## 13 13 15.0 8 400.0 150 3761 9.5 70 1 ## 14 14 14.0 8 455.0 225 3086 10.0 70 1 ## 15 15 24.0 4 113.0 95 2372 15.0 70 3 ## 16 16 22.0 6 198.0 95 2833 15.5 70 1 ## 17 17 18.0 6 199.0 97 2774 15.5 70 1 ## 18 18 21.0 6 200.0 85 2587 16.0 70 1 ## 19 19 27.0 4 97.0 88 2130 14.5 70 3 ## 20 20 26.0 4 97.0 46 1835 20.5 70 2 ## 21 21 25.0 4 110.0 87 2672 17.5 70 2 ## 22 22 24.0 4 107.0 90 2430 14.5 70 2 ## 23 23 25.0 4 104.0 95 2375 17.5 70 2 ## 24 24 26.0 4 121.0 113 2234 12.5 70 2 ## 25 25 21.0 6 199.0 90 2648 15.0 70 1 ## 26 26 10.0 8 360.0 215 4615 14.0 70 1 ## 27 27 10.0 8 307.0 200 4376 15.0 70 1 ## 28 28 11.0 8 318.0 210 4382 13.5 70 1 ## 29 29 9.0 8 304.0 193 4732 18.5 70 1 ## 30 30 27.0 4 97.0 88 2130 14.5 71 3 ## 31 31 28.0 4 140.0 90 2264 15.5 71 1 ## 32 32 25.0 4 113.0 95 2228 14.0 71 3 ## 33 33 25.0 4 98.0 ? 2046 19.0 71 1 ## 34 34 19.0 6 232.0 100 2634 13.0 71 1 ## 35 35 16.0 6 225.0 105 3439 15.5 71 1 ## 36 36 17.0 6 250.0 100 3329 15.5 71 1 ## 37 37 19.0 6 250.0 88 3302 15.5 71 1 ## 38 38 18.0 6 232.0 100 3288 15.5 71 1 ## 39 39 14.0 8 350.0 165 4209 12.0 71 1 ## 40 40 14.0 8 400.0 175 4464 11.5 71 1 ## 41 41 14.0 8 351.0 153 4154 13.5 71 1 ## 42 42 14.0 8 318.0 150 4096 13.0 71 1 ## 43 43 12.0 8 383.0 180 4955 11.5 71 1 ## 44 44 13.0 8 400.0 170 4746 12.0 71 1 ## 45 45 13.0 8 400.0 175 5140 12.0 71 1 ## 46 46 18.0 6 258.0 110 2962 13.5 71 1 ## 47 47 22.0 4 140.0 72 2408 19.0 71 1 ## 48 48 19.0 6 250.0 100 3282 15.0 71 1 ## 49 49 18.0 6 250.0 88 3139 14.5 71 1 ## 50 50 23.0 4 122.0 86 2220 14.0 71 1 ## 51 51 28.0 4 116.0 90 2123 14.0 71 2 ## 52 52 30.0 4 79.0 70 2074 19.5 71 2 ## 53 53 30.0 4 88.0 76 2065 14.5 71 2 ## 54 54 31.0 4 71.0 65 1773 19.0 71 3 ## 55 55 35.0 4 72.0 69 1613 18.0 71 3 ## 56 56 27.0 4 97.0 60 1834 19.0 71 2 ## 57 57 26.0 4 91.0 70 1955 20.5 71 1 ## 58 58 24.0 4 113.0 95 2278 15.5 72 3 ## 59 59 25.0 4 97.5 80 2126 17.0 72 1 ## 60 60 23.0 4 97.0 54 2254 23.5 72 2 ## 61 61 20.0 4 140.0 90 2408 19.5 72 1 ## 62 62 21.0 4 122.0 86 2226 16.5 72 1 ## 63 63 13.0 8 350.0 165 4274 12.0 72 1 ## 64 64 14.0 8 400.0 175 4385 12.0 72 1 ## 65 65 15.0 8 318.0 150 4135 13.5 72 1 ## 66 66 14.0 8 351.0 153 4129 13.0 72 1 ## 67 67 17.0 8 304.0 150 3672 11.5 72 1 ## 68 68 11.0 8 429.0 208 4633 11.0 72 1 ## 69 69 13.0 8 350.0 155 4502 13.5 72 1 ## 70 70 12.0 8 350.0 160 4456 13.5 72 1 ## 71 71 13.0 8 400.0 190 4422 12.5 72 1 ## 72 72 19.0 3 70.0 97 2330 13.5 72 3 ## 73 73 15.0 8 304.0 150 3892 12.5 72 1 ## 74 74 13.0 8 307.0 130 4098 14.0 72 1 ## 75 75 13.0 8 302.0 140 4294 16.0 72 1 ## 76 76 14.0 8 318.0 150 4077 14.0 72 1 ## 77 77 18.0 4 121.0 112 2933 14.5 72 2 ## 78 78 22.0 4 121.0 76 2511 18.0 72 2 ## 79 79 21.0 4 120.0 87 2979 19.5 72 2 ## 80 80 26.0 4 96.0 69 2189 18.0 72 2 ## 81 81 22.0 4 122.0 86 2395 16.0 72 1 ## 82 82 28.0 4 97.0 92 2288 17.0 72 3 ## 83 83 23.0 4 120.0 97 2506 14.5 72 3 ## 84 84 28.0 4 98.0 80 2164 15.0 72 1 ## 85 85 27.0 4 97.0 88 2100 16.5 72 3 ## 86 86 13.0 8 350.0 175 4100 13.0 73 1 ## 87 87 14.0 8 304.0 150 3672 11.5 73 1 ## 88 88 13.0 8 350.0 145 3988 13.0 73 1 ## 89 89 14.0 8 302.0 137 4042 14.5 73 1 ## 90 90 15.0 8 318.0 150 3777 12.5 73 1 ## 91 91 12.0 8 429.0 198 4952 11.5 73 1 ## 92 92 13.0 8 400.0 150 4464 12.0 73 1 ## 93 93 13.0 8 351.0 158 4363 13.0 73 1 ## 94 94 14.0 8 318.0 150 4237 14.5 73 1 ## 95 95 13.0 8 440.0 215 4735 11.0 73 1 ## 96 96 12.0 8 455.0 225 4951 11.0 73 1 ## 97 97 13.0 8 360.0 175 3821 11.0 73 1 ## 98 98 18.0 6 225.0 105 3121 16.5 73 1 ## 99 99 16.0 6 250.0 100 3278 18.0 73 1 ## 100 100 18.0 6 232.0 100 2945 16.0 73 1 ## 101 101 18.0 6 250.0 88 3021 16.5 73 1 ## 102 102 23.0 6 198.0 95 2904 16.0 73 1 ## 103 103 26.0 4 97.0 46 1950 21.0 73 2 ## 104 104 11.0 8 400.0 150 4997 14.0 73 1 ## 105 105 12.0 8 400.0 167 4906 12.5 73 1 ## 106 106 13.0 8 360.0 170 4654 13.0 73 1 ## 107 107 12.0 8 350.0 180 4499 12.5 73 1 ## 108 108 18.0 6 232.0 100 2789 15.0 73 1 ## 109 109 20.0 4 97.0 88 2279 19.0 73 3 ## 110 110 21.0 4 140.0 72 2401 19.5 73 1 ## 111 111 22.0 4 108.0 94 2379 16.5 73 3 ## 112 112 18.0 3 70.0 90 2124 13.5 73 3 ## 113 113 19.0 4 122.0 85 2310 18.5 73 1 ## 114 114 21.0 6 155.0 107 2472 14.0 73 1 ## 115 115 26.0 4 98.0 90 2265 15.5 73 2 ## 116 116 15.0 8 350.0 145 4082 13.0 73 1 ## 117 117 16.0 8 400.0 230 4278 9.5 73 1 ## 118 118 29.0 4 68.0 49 1867 19.5 73 2 ## 119 119 24.0 4 116.0 75 2158 15.5 73 2 ## 120 120 20.0 4 114.0 91 2582 14.0 73 2 ## 121 121 19.0 4 121.0 112 2868 15.5 73 2 ## 122 122 15.0 8 318.0 150 3399 11.0 73 1 ## 123 123 24.0 4 121.0 110 2660 14.0 73 2 ## 124 124 20.0 6 156.0 122 2807 13.5 73 3 ## 125 125 11.0 8 350.0 180 3664 11.0 73 1 ## 126 126 20.0 6 198.0 95 3102 16.5 74 1 ## 127 127 21.0 6 200.0 ? 2875 17.0 74 1 ## 128 128 19.0 6 232.0 100 2901 16.0 74 1 ## 129 129 15.0 6 250.0 100 3336 17.0 74 1 ## 130 130 31.0 4 79.0 67 1950 19.0 74 3 ## 131 131 26.0 4 122.0 80 2451 16.5 74 1 ## 132 132 32.0 4 71.0 65 1836 21.0 74 3 ## 133 133 25.0 4 140.0 75 2542 17.0 74 1 ## 134 134 16.0 6 250.0 100 3781 17.0 74 1 ## 135 135 16.0 6 258.0 110 3632 18.0 74 1 ## 136 136 18.0 6 225.0 105 3613 16.5 74 1 ## 137 137 16.0 8 302.0 140 4141 14.0 74 1 ## 138 138 13.0 8 350.0 150 4699 14.5 74 1 ## 139 139 14.0 8 318.0 150 4457 13.5 74 1 ## 140 140 14.0 8 302.0 140 4638 16.0 74 1 ## 141 141 14.0 8 304.0 150 4257 15.5 74 1 ## 142 142 29.0 4 98.0 83 2219 16.5 74 2 ## 143 143 26.0 4 79.0 67 1963 15.5 74 2 ## 144 144 26.0 4 97.0 78 2300 14.5 74 2 ## 145 145 31.0 4 76.0 52 1649 16.5 74 3 ## 146 146 32.0 4 83.0 61 2003 19.0 74 3 ## 147 147 28.0 4 90.0 75 2125 14.5 74 1 ## 148 148 24.0 4 90.0 75 2108 15.5 74 2 ## 149 149 26.0 4 116.0 75 2246 14.0 74 2 ## 150 150 24.0 4 120.0 97 2489 15.0 74 3 ## 151 151 26.0 4 108.0 93 2391 15.5 74 3 ## 152 152 31.0 4 79.0 67 2000 16.0 74 2 ## 153 153 19.0 6 225.0 95 3264 16.0 75 1 ## 154 154 18.0 6 250.0 105 3459 16.0 75 1 ## 155 155 15.0 6 250.0 72 3432 21.0 75 1 ## 156 156 15.0 6 250.0 72 3158 19.5 75 1 ## 157 157 16.0 8 400.0 170 4668 11.5 75 1 ## 158 158 15.0 8 350.0 145 4440 14.0 75 1 ## 159 159 16.0 8 318.0 150 4498 14.5 75 1 ## 160 160 14.0 8 351.0 148 4657 13.5 75 1 ## 161 161 17.0 6 231.0 110 3907 21.0 75 1 ## 162 162 16.0 6 250.0 105 3897 18.5 75 1 ## 163 163 15.0 6 258.0 110 3730 19.0 75 1 ## 164 164 18.0 6 225.0 95 3785 19.0 75 1 ## 165 165 21.0 6 231.0 110 3039 15.0 75 1 ## 166 166 20.0 8 262.0 110 3221 13.5 75 1 ## 167 167 13.0 8 302.0 129 3169 12.0 75 1 ## 168 168 29.0 4 97.0 75 2171 16.0 75 3 ## 169 169 23.0 4 140.0 83 2639 17.0 75 1 ## 170 170 20.0 6 232.0 100 2914 16.0 75 1 ## 171 171 23.0 4 140.0 78 2592 18.5 75 1 ## 172 172 24.0 4 134.0 96 2702 13.5 75 3 ## 173 173 25.0 4 90.0 71 2223 16.5 75 2 ## 174 174 24.0 4 119.0 97 2545 17.0 75 3 ## 175 175 18.0 6 171.0 97 2984 14.5 75 1 ## 176 176 29.0 4 90.0 70 1937 14.0 75 2 ## 177 177 19.0 6 232.0 90 3211 17.0 75 1 ## 178 178 23.0 4 115.0 95 2694 15.0 75 2 ## 179 179 23.0 4 120.0 88 2957 17.0 75 2 ## 180 180 22.0 4 121.0 98 2945 14.5 75 2 ## 181 181 25.0 4 121.0 115 2671 13.5 75 2 ## 182 182 33.0 4 91.0 53 1795 17.5 75 3 ## 183 183 28.0 4 107.0 86 2464 15.5 76 2 ## 184 184 25.0 4 116.0 81 2220 16.9 76 2 ## 185 185 25.0 4 140.0 92 2572 14.9 76 1 ## 186 186 26.0 4 98.0 79 2255 17.7 76 1 ## 187 187 27.0 4 101.0 83 2202 15.3 76 2 ## 188 188 17.5 8 305.0 140 4215 13.0 76 1 ## 189 189 16.0 8 318.0 150 4190 13.0 76 1 ## 190 190 15.5 8 304.0 120 3962 13.9 76 1 ## 191 191 14.5 8 351.0 152 4215 12.8 76 1 ## 192 192 22.0 6 225.0 100 3233 15.4 76 1 ## 193 193 22.0 6 250.0 105 3353 14.5 76 1 ## 194 194 24.0 6 200.0 81 3012 17.6 76 1 ## 195 195 22.5 6 232.0 90 3085 17.6 76 1 ## 196 196 29.0 4 85.0 52 2035 22.2 76 1 ## 197 197 24.5 4 98.0 60 2164 22.1 76 1 ## 198 198 29.0 4 90.0 70 1937 14.2 76 2 ## 199 199 33.0 4 91.0 53 1795 17.4 76 3 ## 200 200 20.0 6 225.0 100 3651 17.7 76 1 ## 201 201 18.0 6 250.0 78 3574 21.0 76 1 ## 202 202 18.5 6 250.0 110 3645 16.2 76 1 ## 203 203 17.5 6 258.0 95 3193 17.8 76 1 ## 204 204 29.5 4 97.0 71 1825 12.2 76 2 ## 205 205 32.0 4 85.0 70 1990 17.0 76 3 ## 206 206 28.0 4 97.0 75 2155 16.4 76 3 ## 207 207 26.5 4 140.0 72 2565 13.6 76 1 ## 208 208 20.0 4 130.0 102 3150 15.7 76 2 ## 209 209 13.0 8 318.0 150 3940 13.2 76 1 ## 210 210 19.0 4 120.0 88 3270 21.9 76 2 ## 211 211 19.0 6 156.0 108 2930 15.5 76 3 ## 212 212 16.5 6 168.0 120 3820 16.7 76 2 ## 213 213 16.5 8 350.0 180 4380 12.1 76 1 ## 214 214 13.0 8 350.0 145 4055 12.0 76 1 ## 215 215 13.0 8 302.0 130 3870 15.0 76 1 ## 216 216 13.0 8 318.0 150 3755 14.0 76 1 ## 217 217 31.5 4 98.0 68 2045 18.5 77 3 ## 218 218 30.0 4 111.0 80 2155 14.8 77 1 ## 219 219 36.0 4 79.0 58 1825 18.6 77 2 ## 220 220 25.5 4 122.0 96 2300 15.5 77 1 ## 221 221 33.5 4 85.0 70 1945 16.8 77 3 ## 222 222 17.5 8 305.0 145 3880 12.5 77 1 ## 223 223 17.0 8 260.0 110 4060 19.0 77 1 ## 224 224 15.5 8 318.0 145 4140 13.7 77 1 ## 225 225 15.0 8 302.0 130 4295 14.9 77 1 ## 226 226 17.5 6 250.0 110 3520 16.4 77 1 ## 227 227 20.5 6 231.0 105 3425 16.9 77 1 ## 228 228 19.0 6 225.0 100 3630 17.7 77 1 ## 229 229 18.5 6 250.0 98 3525 19.0 77 1 ## 230 230 16.0 8 400.0 180 4220 11.1 77 1 ## 231 231 15.5 8 350.0 170 4165 11.4 77 1 ## 232 232 15.5 8 400.0 190 4325 12.2 77 1 ## 233 233 16.0 8 351.0 149 4335 14.5 77 1 ## 234 234 29.0 4 97.0 78 1940 14.5 77 2 ## 235 235 24.5 4 151.0 88 2740 16.0 77 1 ## 236 236 26.0 4 97.0 75 2265 18.2 77 3 ## 237 237 25.5 4 140.0 89 2755 15.8 77 1 ## 238 238 30.5 4 98.0 63 2051 17.0 77 1 ## 239 239 33.5 4 98.0 83 2075 15.9 77 1 ## 240 240 30.0 4 97.0 67 1985 16.4 77 3 ## 241 241 30.5 4 97.0 78 2190 14.1 77 2 ## 242 242 22.0 6 146.0 97 2815 14.5 77 3 ## 243 243 21.5 4 121.0 110 2600 12.8 77 2 ## 244 244 21.5 3 80.0 110 2720 13.5 77 3 ## 245 245 43.1 4 90.0 48 1985 21.5 78 2 ## 246 246 36.1 4 98.0 66 1800 14.4 78 1 ## 247 247 32.8 4 78.0 52 1985 19.4 78 3 ## 248 248 39.4 4 85.0 70 2070 18.6 78 3 ## 249 249 36.1 4 91.0 60 1800 16.4 78 3 ## 250 250 19.9 8 260.0 110 3365 15.5 78 1 ## 251 251 19.4 8 318.0 140 3735 13.2 78 1 ## 252 252 20.2 8 302.0 139 3570 12.8 78 1 ## 253 253 19.2 6 231.0 105 3535 19.2 78 1 ## 254 254 20.5 6 200.0 95 3155 18.2 78 1 ## 255 255 20.2 6 200.0 85 2965 15.8 78 1 ## 256 256 25.1 4 140.0 88 2720 15.4 78 1 ## 257 257 20.5 6 225.0 100 3430 17.2 78 1 ## 258 258 19.4 6 232.0 90 3210 17.2 78 1 ## 259 259 20.6 6 231.0 105 3380 15.8 78 1 ## 260 260 20.8 6 200.0 85 3070 16.7 78 1 ## 261 261 18.6 6 225.0 110 3620 18.7 78 1 ## 262 262 18.1 6 258.0 120 3410 15.1 78 1 ## 263 263 19.2 8 305.0 145 3425 13.2 78 1 ## 264 264 17.7 6 231.0 165 3445 13.4 78 1 ## 265 265 18.1 8 302.0 139 3205 11.2 78 1 ## 266 266 17.5 8 318.0 140 4080 13.7 78 1 ## 267 267 30.0 4 98.0 68 2155 16.5 78 1 ## 268 268 27.5 4 134.0 95 2560 14.2 78 3 ## 269 269 27.2 4 119.0 97 2300 14.7 78 3 ## 270 270 30.9 4 105.0 75 2230 14.5 78 1 ## 271 271 21.1 4 134.0 95 2515 14.8 78 3 ## 272 272 23.2 4 156.0 105 2745 16.7 78 1 ## 273 273 23.8 4 151.0 85 2855 17.6 78 1 ## 274 274 23.9 4 119.0 97 2405 14.9 78 3 ## 275 275 20.3 5 131.0 103 2830 15.9 78 2 ## 276 276 17.0 6 163.0 125 3140 13.6 78 2 ## 277 277 21.6 4 121.0 115 2795 15.7 78 2 ## 278 278 16.2 6 163.0 133 3410 15.8 78 2 ## 279 279 31.5 4 89.0 71 1990 14.9 78 2 ## 280 280 29.5 4 98.0 68 2135 16.6 78 3 ## 281 281 21.5 6 231.0 115 3245 15.4 79 1 ## 282 282 19.8 6 200.0 85 2990 18.2 79 1 ## 283 283 22.3 4 140.0 88 2890 17.3 79 1 ## 284 284 20.2 6 232.0 90 3265 18.2 79 1 ## 285 285 20.6 6 225.0 110 3360 16.6 79 1 ## 286 286 17.0 8 305.0 130 3840 15.4 79 1 ## 287 287 17.6 8 302.0 129 3725 13.4 79 1 ## 288 288 16.5 8 351.0 138 3955 13.2 79 1 ## 289 289 18.2 8 318.0 135 3830 15.2 79 1 ## 290 290 16.9 8 350.0 155 4360 14.9 79 1 ## 291 291 15.5 8 351.0 142 4054 14.3 79 1 ## 292 292 19.2 8 267.0 125 3605 15.0 79 1 ## 293 293 18.5 8 360.0 150 3940 13.0 79 1 ## 294 294 31.9 4 89.0 71 1925 14.0 79 2 ## 295 295 34.1 4 86.0 65 1975 15.2 79 3 ## 296 296 35.7 4 98.0 80 1915 14.4 79 1 ## 297 297 27.4 4 121.0 80 2670 15.0 79 1 ## 298 298 25.4 5 183.0 77 3530 20.1 79 2 ## 299 299 23.0 8 350.0 125 3900 17.4 79 1 ## 300 300 27.2 4 141.0 71 3190 24.8 79 2 ## 301 301 23.9 8 260.0 90 3420 22.2 79 1 ## 302 302 34.2 4 105.0 70 2200 13.2 79 1 ## 303 303 34.5 4 105.0 70 2150 14.9 79 1 ## 304 304 31.8 4 85.0 65 2020 19.2 79 3 ## 305 305 37.3 4 91.0 69 2130 14.7 79 2 ## 306 306 28.4 4 151.0 90 2670 16.0 79 1 ## 307 307 28.8 6 173.0 115 2595 11.3 79 1 ## 308 308 26.8 6 173.0 115 2700 12.9 79 1 ## 309 309 33.5 4 151.0 90 2556 13.2 79 1 ## 310 310 41.5 4 98.0 76 2144 14.7 80 2 ## 311 311 38.1 4 89.0 60 1968 18.8 80 3 ## 312 312 32.1 4 98.0 70 2120 15.5 80 1 ## 313 313 37.2 4 86.0 65 2019 16.4 80 3 ## 314 314 28.0 4 151.0 90 2678 16.5 80 1 ## 315 315 26.4 4 140.0 88 2870 18.1 80 1 ## 316 316 24.3 4 151.0 90 3003 20.1 80 1 ## 317 317 19.1 6 225.0 90 3381 18.7 80 1 ## 318 318 34.3 4 97.0 78 2188 15.8 80 2 ## 319 319 29.8 4 134.0 90 2711 15.5 80 3 ## 320 320 31.3 4 120.0 75 2542 17.5 80 3 ## 321 321 37.0 4 119.0 92 2434 15.0 80 3 ## 322 322 32.2 4 108.0 75 2265 15.2 80 3 ## 323 323 46.6 4 86.0 65 2110 17.9 80 3 ## 324 324 27.9 4 156.0 105 2800 14.4 80 1 ## 325 325 40.8 4 85.0 65 2110 19.2 80 3 ## 326 326 44.3 4 90.0 48 2085 21.7 80 2 ## 327 327 43.4 4 90.0 48 2335 23.7 80 2 ## 328 328 36.4 5 121.0 67 2950 19.9 80 2 ## 329 329 30.0 4 146.0 67 3250 21.8 80 2 ## 330 330 44.6 4 91.0 67 1850 13.8 80 3 ## 331 331 40.9 4 85.0 ? 1835 17.3 80 2 ## 332 332 33.8 4 97.0 67 2145 18.0 80 3 ## 333 333 29.8 4 89.0 62 1845 15.3 80 2 ## 334 334 32.7 6 168.0 132 2910 11.4 80 3 ## 335 335 23.7 3 70.0 100 2420 12.5 80 3 ## 336 336 35.0 4 122.0 88 2500 15.1 80 2 ## 337 337 23.6 4 140.0 ? 2905 14.3 80 1 ## 338 338 32.4 4 107.0 72 2290 17.0 80 3 ## 339 339 27.2 4 135.0 84 2490 15.7 81 1 ## 340 340 26.6 4 151.0 84 2635 16.4 81 1 ## 341 341 25.8 4 156.0 92 2620 14.4 81 1 ## 342 342 23.5 6 173.0 110 2725 12.6 81 1 ## 343 343 30.0 4 135.0 84 2385 12.9 81 1 ## 344 344 39.1 4 79.0 58 1755 16.9 81 3 ## 345 345 39.0 4 86.0 64 1875 16.4 81 1 ## 346 346 35.1 4 81.0 60 1760 16.1 81 3 ## 347 347 32.3 4 97.0 67 2065 17.8 81 3 ## 348 348 37.0 4 85.0 65 1975 19.4 81 3 ## 349 349 37.7 4 89.0 62 2050 17.3 81 3 ## 350 350 34.1 4 91.0 68 1985 16.0 81 3 ## 351 351 34.7 4 105.0 63 2215 14.9 81 1 ## 352 352 34.4 4 98.0 65 2045 16.2 81 1 ## 353 353 29.9 4 98.0 65 2380 20.7 81 1 ## 354 354 33.0 4 105.0 74 2190 14.2 81 2 ## 355 355 34.5 4 100.0 ? 2320 15.8 81 2 ## 356 356 33.7 4 107.0 75 2210 14.4 81 3 ## 357 357 32.4 4 108.0 75 2350 16.8 81 3 ## 358 358 32.9 4 119.0 100 2615 14.8 81 3 ## 359 359 31.6 4 120.0 74 2635 18.3 81 3 ## 360 360 28.1 4 141.0 80 3230 20.4 81 2 ## 361 361 30.7 6 145.0 76 3160 19.6 81 2 ## 362 362 25.4 6 168.0 116 2900 12.6 81 3 ## 363 363 24.2 6 146.0 120 2930 13.8 81 3 ## 364 364 22.4 6 231.0 110 3415 15.8 81 1 ## 365 365 26.6 8 350.0 105 3725 19.0 81 1 ## 366 366 20.2 6 200.0 88 3060 17.1 81 1 ## 367 367 17.6 6 225.0 85 3465 16.6 81 1 ## 368 368 28.0 4 112.0 88 2605 19.6 82 1 ## 369 369 27.0 4 112.0 88 2640 18.6 82 1 ## 370 370 34.0 4 112.0 88 2395 18.0 82 1 ## 371 371 31.0 4 112.0 85 2575 16.2 82 1 ## 372 372 29.0 4 135.0 84 2525 16.0 82 1 ## 373 373 27.0 4 151.0 90 2735 18.0 82 1 ## 374 374 24.0 4 140.0 92 2865 16.4 82 1 ## 375 375 23.0 4 151.0 ? 3035 20.5 82 1 ## 376 376 36.0 4 105.0 74 1980 15.3 82 2 ## 377 377 37.0 4 91.0 68 2025 18.2 82 3 ## 378 378 31.0 4 91.0 68 1970 17.6 82 3 ## 379 379 38.0 4 105.0 63 2125 14.7 82 1 ## 380 380 36.0 4 98.0 70 2125 17.3 82 1 ## 381 381 36.0 4 120.0 88 2160 14.5 82 3 ## 382 382 36.0 4 107.0 75 2205 14.5 82 3 ## 383 383 34.0 4 108.0 70 2245 16.9 82 3 ## 384 384 38.0 4 91.0 67 1965 15.0 82 3 ## 385 385 32.0 4 91.0 67 1965 15.7 82 3 ## 386 386 38.0 4 91.0 67 1995 16.2 82 3 ## 387 387 25.0 6 181.0 110 2945 16.4 82 1 ## 388 388 38.0 6 262.0 85 3015 17.0 82 1 ## 389 389 26.0 4 156.0 92 2585 14.5 82 1 ## 390 390 22.0 6 232.0 112 2835 14.7 82 1 ## 391 391 32.0 4 144.0 96 2665 13.9 82 3 ## 392 392 36.0 4 135.0 84 2370 13.0 82 1 ## 393 393 27.0 4 151.0 90 2950 17.3 82 1 ## 394 394 27.0 4 140.0 86 2790 15.6 82 1 ## 395 395 44.0 4 97.0 52 2130 24.6 82 2 ## 396 396 32.0 4 135.0 84 2295 11.6 82 1 ## 397 397 28.0 4 120.0 79 2625 18.6 82 1 ## 398 398 31.0 4 119.0 82 2720 19.4 82 1 ## car_name price ## 1 chevrolet chevelle malibu 25561.591 ## 2 buick skylark 320 24221.423 ## 3 plymouth satellite 27240.844 ## 4 amc rebel sst 33684.969 ## 5 ford torino 20000.000 ## 6 ford galaxie 500 30000.000 ## 7 chevrolet impala 35764.335 ## 8 plymouth fury iii 25899.466 ## 9 pontiac catalina 32882.537 ## 10 amc ambassador dpl 32617.059 ## 11 dodge challenger se 30000.000 ## 12 plymouth 'cuda 340 33034.923 ## 13 chevrolet monte carlo 30000.000 ## 14 buick estate wagon (sw) 26608.328 ## 15 toyota corona mark ii 36927.067 ## 16 plymouth duster 12561.103 ## 17 amc hornet 24260.622 ## 18 ford maverick 14228.304 ## 19 datsun pl510 15802.239 ## 20 volkswagen 1131 deluxe sedan 27471.292 ## 21 peugeot 504 40000.000 ## 22 audi 100 ls 35897.440 ## 23 saab 99e 16905.843 ## 24 bmw 2002 15047.989 ## 25 amc gremlin 14045.895 ## 26 ford f250 25797.485 ## 27 chevy c20 40000.000 ## 28 dodge d200 24928.420 ## 29 hi 1200d 45072.569 ## 30 datsun pl510 16992.082 ## 31 chevrolet vega 2300 13206.433 ## 32 toyota corona 27078.798 ## 33 ford pinto 26417.435 ## 34 amc gremlin 30000.000 ## 35 plymouth satellite custom 44534.971 ## 36 chevrolet chevelle malibu 40000.000 ## 37 ford torino 500 30000.000 ## 38 amc matador 33970.666 ## 39 chevrolet impala 40000.000 ## 40 pontiac catalina brougham 33793.723 ## 41 ford galaxie 500 30000.000 ## 42 plymouth fury iii 15358.863 ## 43 dodge monaco (sw) 23414.417 ## 44 ford country squire (sw) 44211.912 ## 45 pontiac safari (sw) 20000.000 ## 46 amc hornet sportabout (sw) 33328.427 ## 47 chevrolet vega (sw) 20000.000 ## 48 pontiac firebird 20000.000 ## 49 ford mustang 40000.000 ## 50 mercury capri 2000 27435.396 ## 51 opel 1900 20000.000 ## 52 peugeot 304 36587.119 ## 53 fiat 124b 23790.829 ## 54 toyota corolla 1200 30000.000 ## 55 datsun 1200 40000.000 ## 56 volkswagen model 111 30000.000 ## 57 plymouth cricket 40000.000 ## 58 toyota corona hardtop 40000.000 ## 59 dodge colt hardtop 20000.000 ## 60 volkswagen type 3 26196.505 ## 61 chevrolet vega 33019.208 ## 62 ford pinto runabout 36453.301 ## 63 chevrolet impala 40000.000 ## 64 pontiac catalina 26062.794 ## 65 plymouth fury iii 34663.839 ## 66 ford galaxie 500 20000.000 ## 67 amc ambassador sst 20000.000 ## 68 mercury marquis 16223.268 ## 69 buick lesabre custom 5975.710 ## 70 oldsmobile delta 88 royale 40000.000 ## 71 chrysler newport royal 33048.801 ## 72 mazda rx2 coupe 25558.031 ## 73 amc matador (sw) 1598.073 ## 74 chevrolet chevelle concours (sw) 20000.000 ## 75 ford gran torino (sw) 30000.000 ## 76 plymouth satellite custom (sw) 26693.718 ## 77 volvo 145e (sw) 30000.000 ## 78 volkswagen 411 (sw) 40000.000 ## 79 peugeot 504 (sw) 16035.297 ## 80 renault 12 (sw) 44239.249 ## 81 ford pinto (sw) 20000.000 ## 82 datsun 510 (sw) 36556.744 ## 83 toyouta corona mark ii (sw) 30000.000 ## 84 dodge colt (sw) 20000.000 ## 85 toyota corolla 1600 (sw) 35088.029 ## 86 buick century 350 20000.000 ## 87 amc matador 30000.000 ## 88 chevrolet malibu 24364.522 ## 89 ford gran torino 50306.153 ## 90 dodge coronet custom 30000.000 ## 91 mercury marquis brougham 30000.000 ## 92 chevrolet caprice classic 35052.192 ## 93 ford ltd 36489.401 ## 94 plymouth fury gran sedan 53745.938 ## 95 chrysler new yorker brougham 40000.000 ## 96 buick electra 225 custom 26260.635 ## 97 amc ambassador brougham 40000.000 ## 98 plymouth valiant 23283.525 ## 99 chevrolet nova custom 30000.000 ## 100 amc hornet 30000.000 ## 101 ford maverick 33726.808 ## 102 plymouth duster 25211.028 ## 103 volkswagen super beetle 35994.526 ## 104 chevrolet impala 24794.074 ## 105 ford country 20000.000 ## 106 plymouth custom suburb 34078.914 ## 107 oldsmobile vista cruiser 34538.974 ## 108 amc gremlin 17410.015 ## 109 toyota carina 40000.000 ## 110 chevrolet vega 43478.058 ## 111 datsun 610 20000.000 ## 112 maxda rx3 47897.350 ## 113 ford pinto 40000.000 ## 114 mercury capri v6 30000.000 ## 115 fiat 124 sport coupe 20000.000 ## 116 chevrolet monte carlo s 26355.640 ## 117 pontiac grand prix 27104.012 ## 118 fiat 128 30000.000 ## 119 opel manta 30000.000 ## 120 audi 100ls 36717.904 ## 121 volvo 144ea 30000.000 ## 122 dodge dart custom 40000.000 ## 123 saab 99le 30000.000 ## 124 toyota mark ii 30000.000 ## 125 oldsmobile omega 9006.649 ## 126 plymouth duster 20000.000 ## 127 ford maverick 36836.739 ## 128 amc hornet 30000.000 ## 129 chevrolet nova 34166.890 ## 130 datsun b210 30000.000 ## 131 ford pinto 40000.000 ## 132 toyota corolla 1200 50430.443 ## 133 chevrolet vega 30000.000 ## 134 chevrolet chevelle malibu classic 20000.000 ## 135 amc matador 35815.107 ## 136 plymouth satellite sebring 30000.000 ## 137 ford gran torino 27027.841 ## 138 buick century luxus (sw) 20000.000 ## 139 dodge coronet custom (sw) 30000.000 ## 140 ford gran torino (sw) 43956.273 ## 141 amc matador (sw) 30000.000 ## 142 audi fox 27392.704 ## 143 volkswagen dasher 40000.000 ## 144 opel manta 10064.418 ## 145 toyota corona 20000.000 ## 146 datsun 710 22599.021 ## 147 dodge colt 30000.000 ## 148 fiat 128 36359.772 ## 149 fiat 124 tc 24285.003 ## 150 honda civic 30000.000 ## 151 subaru 26414.508 ## 152 fiat x1.9 8068.232 ## 153 plymouth valiant custom 20000.000 ## 154 chevrolet nova 35725.202 ## 155 mercury monarch 12388.960 ## 156 ford maverick 30000.000 ## 157 pontiac catalina 40000.000 ## 158 chevrolet bel air 8844.147 ## 159 plymouth grand fury 7250.279 ## 160 ford ltd 40000.000 ## 161 buick century 43913.818 ## 162 chevroelt chevelle malibu 16545.010 ## 163 amc matador 25349.777 ## 164 plymouth fury 30000.000 ## 165 buick skyhawk 34085.806 ## 166 chevrolet monza 2+2 30000.000 ## 167 ford mustang ii 34458.387 ## 168 toyota corolla 30000.000 ## 169 ford pinto 16968.556 ## 170 amc gremlin 22601.178 ## 171 pontiac astro 30000.000 ## 172 toyota corona 5579.396 ## 173 volkswagen dasher 34295.657 ## 174 datsun 710 24359.886 ## 175 ford pinto 40000.000 ## 176 volkswagen rabbit 23555.606 ## 177 amc pacer 25780.198 ## 178 audi 100ls 16577.463 ## 179 peugeot 504 30000.000 ## 180 volvo 244dl 40000.000 ## 181 saab 99le 17080.979 ## 182 honda civic cvcc 25436.922 ## 183 fiat 131 37495.996 ## 184 opel 1900 23325.547 ## 185 capri ii 30000.000 ## 186 dodge colt 33128.294 ## 187 renault 12tl 30000.000 ## 188 chevrolet chevelle malibu classic 25546.687 ## 189 dodge coronet brougham 20000.000 ## 190 amc matador 20000.000 ## 191 ford gran torino 47075.035 ## 192 plymouth valiant 40000.000 ## 193 chevrolet nova 44633.994 ## 194 ford maverick 50179.779 ## 195 amc hornet 13136.848 ## 196 chevrolet chevette 40000.000 ## 197 chevrolet woody 30000.000 ## 198 vw rabbit 20000.000 ## 199 honda civic 40000.000 ## 200 dodge aspen se 30000.000 ## 201 ford granada ghia 26411.473 ## 202 pontiac ventura sj 26090.279 ## 203 amc pacer d/l 30000.000 ## 204 volkswagen rabbit 23640.679 ## 205 datsun b-210 34072.299 ## 206 toyota corolla 22682.074 ## 207 ford pinto 40000.000 ## 208 volvo 245 40000.000 ## 209 plymouth volare premier v8 22781.281 ## 210 peugeot 504 26121.736 ## 211 toyota mark ii 14501.049 ## 212 mercedes-benz 280s 24937.676 ## 213 cadillac seville 16557.225 ## 214 chevy c10 30000.000 ## 215 ford f108 20000.000 ## 216 dodge d100 20000.000 ## 217 honda accord cvcc 16288.278 ## 218 buick opel isuzu deluxe 25530.810 ## 219 renault 5 gtl 20000.000 ## 220 plymouth arrow gs 30000.000 ## 221 datsun f-10 hatchback 30000.000 ## 222 chevrolet caprice classic 30000.000 ## 223 oldsmobile cutlass supreme 30000.000 ## 224 dodge monaco brougham 40000.000 ## 225 mercury cougar brougham 20000.000 ## 226 chevrolet concours 20000.000 ## 227 buick skylark 30000.000 ## 228 plymouth volare custom 26631.006 ## 229 ford granada 36453.916 ## 230 pontiac grand prix lj 16330.963 ## 231 chevrolet monte carlo landau 40000.000 ## 232 chrysler cordoba 20000.000 ## 233 ford thunderbird 40000.000 ## 234 volkswagen rabbit custom 44398.390 ## 235 pontiac sunbird coupe 22768.363 ## 236 toyota corolla liftback 24051.712 ## 237 ford mustang ii 2+2 30000.000 ## 238 chevrolet chevette 40000.000 ## 239 dodge colt m/m 36578.745 ## 240 subaru dl 32735.658 ## 241 volkswagen dasher 20000.000 ## 242 datsun 810 42883.256 ## 243 bmw 320i 23927.442 ## 244 mazda rx-4 23761.784 ## 245 volkswagen rabbit custom diesel 30000.000 ## 246 ford fiesta 30000.000 ## 247 mazda glc deluxe 32914.193 ## 248 datsun b210 gx 40000.000 ## 249 honda civic cvcc 30000.000 ## 250 oldsmobile cutlass salon brougham 30000.000 ## 251 dodge diplomat 40000.000 ## 252 mercury monarch ghia 34088.830 ## 253 pontiac phoenix lj 30000.000 ## 254 chevrolet malibu 20000.000 ## 255 ford fairmont (auto) 30000.000 ## 256 ford fairmont (man) 40000.000 ## 257 plymouth volare 30000.000 ## 258 amc concord 30000.000 ## 259 buick century special 40000.000 ## 260 mercury zephyr 33560.688 ## 261 dodge aspen 33043.991 ## 262 amc concord d/l 25625.972 ## 263 chevrolet monte carlo landau 50024.689 ## 264 buick regal sport coupe (turbo) 20000.000 ## 265 ford futura 35375.464 ## 266 dodge magnum xe 26331.123 ## 267 chevrolet chevette 49295.848 ## 268 toyota corona 30000.000 ## 269 datsun 510 35110.420 ## 270 dodge omni 24166.911 ## 271 toyota celica gt liftback 14511.795 ## 272 plymouth sapporo 36338.235 ## 273 oldsmobile starfire sx 30000.000 ## 274 datsun 200-sx 47709.821 ## 275 audi 5000 43261.830 ## 276 volvo 264gl 44815.879 ## 277 saab 99gle 47597.903 ## 278 peugeot 604sl 23051.895 ## 279 volkswagen scirocco 30000.000 ## 280 honda accord lx 20000.000 ## 281 pontiac lemans v6 20000.000 ## 282 mercury zephyr 6 37443.856 ## 283 ford fairmont 4 20000.000 ## 284 amc concord dl 6 12840.579 ## 285 dodge aspen 6 26927.116 ## 286 chevrolet caprice classic 30000.000 ## 287 ford ltd landau 52480.068 ## 288 mercury grand marquis 13073.585 ## 289 dodge st. regis 8766.445 ## 290 buick estate wagon (sw) 24606.122 ## 291 ford country squire (sw) 25696.089 ## 292 chevrolet malibu classic (sw) 26157.235 ## 293 chrysler lebaron town @ country (sw) 14944.488 ## 294 vw rabbit custom 40000.000 ## 295 maxda glc deluxe 20000.000 ## 296 dodge colt hatchback custom 44271.593 ## 297 amc spirit dl 40000.000 ## 298 mercedes benz 300d 20000.000 ## 299 cadillac eldorado 44274.407 ## 300 peugeot 504 24639.374 ## 301 oldsmobile cutlass salon brougham 33062.120 ## 302 plymouth horizon 30000.000 ## 303 plymouth horizon tc3 22906.701 ## 304 datsun 210 30000.000 ## 305 fiat strada custom 30000.000 ## 306 buick skylark limited 33322.520 ## 307 chevrolet citation 30000.000 ## 308 oldsmobile omega brougham 45923.536 ## 309 pontiac phoenix 49548.623 ## 310 vw rabbit 48911.314 ## 311 toyota corolla tercel 20000.000 ## 312 chevrolet chevette 8400.697 ## 313 datsun 310 34035.285 ## 314 chevrolet citation 34799.282 ## 315 ford fairmont 17032.345 ## 316 amc concord 30000.000 ## 317 dodge aspen 30000.000 ## 318 audi 4000 40000.000 ## 319 toyota corona liftback 40000.000 ## 320 mazda 626 27206.138 ## 321 datsun 510 hatchback 47697.077 ## 322 toyota corolla 30000.000 ## 323 mazda glc 30000.000 ## 324 dodge colt 52035.834 ## 325 datsun 210 26407.844 ## 326 vw rabbit c (diesel) 51239.144 ## 327 vw dasher (diesel) 40000.000 ## 328 audi 5000s (diesel) 44494.544 ## 329 mercedes-benz 240d 20000.000 ## 330 honda civic 1500 gl 20000.000 ## 331 renault lecar deluxe 32650.652 ## 332 subaru dl 35335.983 ## 333 vokswagen rabbit 30000.000 ## 334 datsun 280-zx 25944.325 ## 335 mazda rx-7 gs 44730.246 ## 336 triumph tr7 coupe 30000.000 ## 337 ford mustang cobra 24749.737 ## 338 honda accord 40000.000 ## 339 plymouth reliant 43221.372 ## 340 buick skylark 20000.000 ## 341 dodge aries wagon (sw) 11460.906 ## 342 chevrolet citation 40000.000 ## 343 plymouth reliant 33838.413 ## 344 toyota starlet 30000.000 ## 345 plymouth champ 24040.393 ## 346 honda civic 1300 26717.101 ## 347 subaru 13900.615 ## 348 datsun 210 mpg 17268.170 ## 349 toyota tercel 50475.688 ## 350 mazda glc 4 49150.576 ## 351 plymouth horizon 4 30000.000 ## 352 ford escort 4w 20000.000 ## 353 ford escort 2h 20000.000 ## 354 volkswagen jetta 30000.000 ## 355 renault 18i 30000.000 ## 356 honda prelude 20000.000 ## 357 toyota corolla 30000.000 ## 358 datsun 200sx 30000.000 ## 359 mazda 626 40000.000 ## 360 peugeot 505s turbo diesel 20000.000 ## 361 volvo diesel 40000.000 ## 362 toyota cressida 30000.000 ## 363 datsun 810 maxima 32646.400 ## 364 buick century 25571.469 ## 365 oldsmobile cutlass ls 30000.000 ## 366 ford granada gl 30000.000 ## 367 chrysler lebaron salon 23723.775 ## 368 chevrolet cavalier 27234.664 ## 369 chevrolet cavalier wagon 42666.914 ## 370 chevrolet cavalier 2-door 40000.000 ## 371 pontiac j2000 se hatchback 27074.395 ## 372 dodge aries se 20000.000 ## 373 pontiac phoenix 33111.138 ## 374 ford fairmont futura 51186.915 ## 375 amc concord dl 37179.288 ## 376 volkswagen rabbit l 33472.791 ## 377 mazda glc custom l 44607.866 ## 378 mazda glc custom 34686.423 ## 379 plymouth horizon miser 48111.102 ## 380 mercury lynx l 30000.000 ## 381 nissan stanza xe 34612.009 ## 382 honda accord 30000.000 ## 383 toyota corolla 30000.000 ## 384 honda civic 30000.000 ## 385 honda civic (auto) 30000.000 ## 386 datsun 310 gx 30000.000 ## 387 buick century limited 25289.834 ## 388 oldsmobile cutlass ciera (diesel) 9944.306 ## 389 chrysler lebaron medallion 34986.218 ## 390 ford granada l 22973.019 ## 391 toyota celica gt 20000.000 ## 392 dodge charger 2.2 17421.627 ## 393 chevrolet camaro 12550.000 ## 394 ford mustang gl 13432.500 ## 395 vw pickup 37000.000 ## 396 dodge rampage 47800.000 ## 397 ford ranger 46000.000 ## 398 chevy s-10 9000.000
Five Number Summary of Weight
The following gives the mean, median, and five number summary of all of the weight values from the dataset:
mean(carsData$weight)
## [1] 2970.425
median(carsData$weight)
## [1] 2803.5
fivenum(carsData$weight)
## [1] 1613.0 2223.0 2803.5 3609.0 5140.0
Does Weight have any Outliers?
IQR <- IQR(carsData$weight) IQR
## [1] 1384.25
Upperfence <- 3609.0 + 1.5*(IQR) Upperfence
## [1] 5685.375
Lowerfence <- 2223.0 - 1.5*(IQR) Lowerfence
## [1] 146.625
Both the upper and lower fence are outside the range of the data, so there are no outliers.
Compare Displacement to mpg, filtered by number of cylinders
## `geom_smooth()` using formula = 'y ~ x'
Weight Compared to Acceleration
## `geom_smooth()` using formula = 'y ~ x'
Price by Model
Horsepower, Weight, and mpg Viewed in a 3D Graph
Conclusions
From the previous slides, we obtain the following conclusions about the data:
- The weight of cars is relatively consistent, given that there are no outliers.
- Displacement and mpg have an inverse relation, and a higher number of cylinders generally results in higher displacement and lower mpg.
- Weight and acceleration have an inverse relationship, though there are many points on the graph that do not follow the linear regression, so there are likely other factors that determine acceleration.
- There is unlikely to be a relationship between price and model.
- A higher weight is associated with higher horsepower but a lower mpg.