Question: Improving Road Safety by Profiling Different Accident Types In this assignment, analyze previous accident data and identify factors that differentiate the accident types. Accident types
Improving Road Safety by Profiling Different Accident Types
In this assignment, analyze previous accident data and identify factors that differentiate the accident types. Accident types can include being hit in the back, sideswiped, pedestrian crossing collision, and so on.
- Collect data from the Department of Transportation (DOT). The data should include variables such as time variables, (hour by daytime or nighttime), rush hour, and weekday.In environment variables, you should have weather, light, speed limit, road type, location, pavement condition, and presence of the signal.Gather the data and continue to Step 2.
- Scrape, clean, and manipulate the data so that it is usable. Save the data set in an Excelor CSV format.
| Crashes, by Time of Day and Day of Week, 2020 [All Crashes] | |||||||||
| Crashed by Time of Day | Day of the Week | ||||||||
| Sunday | Monday | Tuesday | Wednesday | Thursday | Friday | Saturday | Total | ||
| Total | Midnight to 2:59 A.M. | 58,248 | 28,416 | 23,284 | 28,339 | 25,212 | 30,662 | 47,195 | 241,356 |
| 3 A.M. to 5:59 A.M. | 35,795 | 25,426 | 27,975 | 26,562 | 30,208 | 31,531 | 29,762 | 207,259 | |
| 6 A.M. to 8:59 A.M. | 37,150 | 95,429 | 106,499 | 105,611 | 106,388 | 94,327 | 45,983 | 591,387 | |
| 9 A.M. to 11:59 A.M. | 62,740 | 101,312 | 106,446 | 106,155 | 106,843 | 115,482 | 95,273 | 694,251 | |
| 12 P.M. to 2:59 P.M. | 108,951 | 136,645 | 134,652 | 152,845 | 147,298 | 170,136 | 133,612 | 984,139 | |
| 3 P.M. to 5:59 P.M | 115,116 | 180,133 | 199,863 | 202,011 | 218,378 | 222,448 | 136,450 | 1,274,399 | |
| 6 P.M. to 8:59 P.M | 105,543 | 103,887 | 111,023 | 119,077 | 118,310 | 140,317 | 120,405 | 818,562 | |
| 9 P.M. to 11:59 P.M. | 55,548 | 53,888 | 45,833 | 53,337 | 67,162 | 79,321 | 84,125 | 439,214 | |
| Unkown | 64 | 33 | 41 | 37 | 34 | 48 | 56 | 313 | |
| Total | 579,155 | 725,169 | 755,616 | 793,974 | 819,833 | 884,272 | 692,861 | 5,250,880 | |
| *Note: Totals may not equal the sum of components from source due to independent rounding | |||||||||
| Crashes, by Weather Condition and Light Condition, 2020 [All Crashes] | |||||||||
| Crashes by Weather Condition | Light Condition | ||||||||
| Daylight | Lighted | Dark | Dawn/Dusk | Other | Unknown | Total | |||
| Total | Normal | 3,087,152 | 724,961 | 529,830 | 181,779 | 878 | - | 4,524,600 | |
| Rain | 347,933 | 112,644 | 82,146 | 26,166 | 499 | - | 569,388 | ||
| Snow/Sleet | 63,673 | 21,367 | 27,427 | 7,062 | - | - | 119,529 | ||
| Other | 15,122 | 5,643 | 9,420 | 4,337 | - | - | 34,522 | ||
| Unknown | 1,184 | 529 | 699 | 104 | 2 | - | 2,518 | ||
| Total | 3,515,064 | 865,144 | 649,522 | 219,448 | 1,379 | - | 5,250,557 | ||
| *Note: Totals may not equal the sum of components from source due to independent rounding | |||||||||
| **Includes fatal crashes for which light condition was unknown per source | |||||||||
| Crashes, by First Harmful Event, 2020 | |||||||||
| First Harmful Event | Total Number | ||||||||
| Collision with Motor Vechicle in Transport | Angle | 11,239,608 | |||||||
| Read End | 1,457,155 | ||||||||
| Sideswipe | 622,222 | ||||||||
| Head On | 112,729 | ||||||||
| Other/Unknown | 53,036 | ||||||||
| SubTotal | 13,484,750 | ||||||||
| Collision with Fixed Object | Pole/Post | 193,630 | |||||||
| Culvert/Curb/Ditch | 217,699 | ||||||||
| Shrubbery/Tree | 101,942 | ||||||||
| Guard Rail | 94,262 | ||||||||
| Embankment | 44,813 | ||||||||
| Bridge | 14,630 | ||||||||
| Other/Unknown | 250,276 | ||||||||
| SubTotal | 917,252 | ||||||||
| Collision with Object Not Fixed | Parked Motor | 302,659 | |||||||
| Animal | 255,879 | ||||||||
| Pedestrian | 56,222 | ||||||||
| Pedalcyclist | 42,774 | ||||||||
| Train | 779 | ||||||||
| Other/Unknown | 74,429 | ||||||||
| SubTotal | 732,742 | ||||||||
| Non- collision | Rollover | 83,874 | |||||||
| Other/Unknown | 32,148 | ||||||||
| SubTotal | 116,022 | ||||||||
| TOTAL | TOTAL | 15,250,766 | |||||||
| *Includes fatal crashes where the most harmful event was unknown or there was a harmful event, but the details were not reported per source. | |||||||||
| **Note: Totals may not equal sum of components due to independent rounding from source | |||||||||
| Vehicles Involved in Crashes, by Relation to Junction, Traffic Control Device, and Crash Severity [All Crashes]; 2020 | |||||||||
| Relation to Junction | Traffic Control Device | ||||||||
| None | Traffic Signal | Stop Sign | Other/Unknown | Total | |||||
| Nonjunction | 2,767,659 | 9,163 | 1,093 | 837,345 | 3,615,260 | ||||
| Junction | Intersection | 553,516 | 1,008,406 | 427,077 | 236,369 | 2,225,368 | |||
| Intersection-Related | 443,540 | 1,197,977 | 200,431 | 244,565 | 2,086,513 | ||||
| Other Unknown | 899,401 | 39,708 | 34,609 | 243,770 | 1,217,488 | ||||
| Total: | 4,664,116 | 2,255,254 | 663,210 | 1,562,049 | 9,144,629 | ||||
| *Note: Totals may not equal the sum of components from source due to independent rounding | |||||||||
| Vehicles Involved in Crashes, by Number of Lanes, Trafficway Flow, and Crash Severity [All Crashes], 2020 | |||||||||
| Number of Lanes | Trafficway Flow | Total | |||||||
| Not Divided | Divided | One-Way | Entrance/Exit Ramps | Unknown | |||||
| One Lane | 8,355 | 30,340 | 30,254 | 80,352 | 3,672 | 152,973 | |||
| Two Lanes | 2,011,814 | 712,201 | 69,703 | 61,817 | 87,463 | 2,942,998 | |||
| Three Lanes | 348,314 | 729,486 | 43,837 | 16,157 | 18,812 | 1,156,606 | |||
| Four Lanes | 405,819 | 484,668 | 16,376 | 9,199 | 26,277 | 942,339 | |||
| More than Four | 642,638 | 384,509 | 4,363 | 2,014 | 19,097 | 1,052,621 | |||
| Unknown | 623,652 | 518,523 | 428,322 | 51,228 | 1,436,934 | 3,058,659 | |||
| Total | 4,040,592 | 2,859,727 | 592,855 | 220,767 | 1,592,255 | 9,306,196 | |||
| *Note: Totals may not equal the sum of components from source due to independent rounding | |||||||||
| 2020 Traffic Fatalities, by State and Percentage Change from 2019 | |||||||||
| State | Fatalities | State | Fatalities | ||||||
| 2019 | 2020 | Percentage Change | 2019 | 2020 | Percentage Change | ||||
| AL | 930 | 934 | 0% | NE | 248 | 233 | -6% | ||
| AK | 67 | 64 | -5% | NV | 304 | 317 | 4% | ||
| AZ | 979 | 1,054 | 7% | NH | 101 | 104 | 3% | ||
| AR | 511 | 638 | 20% | NJ | 558 | 584 | 4% | ||
| CA | 3,719 | 3,847 | 3% | NM | 425 | 398 | -7% | ||
| CO | 597 | 622 | 4% | NY | 934 | 1,046 | 11% | ||
| CT | 249 | 295 | 16% | NC | 1,457 | 1,538 | 5% | ||
| DE | 132 | 116 | -14% | ND | 100 | 100 | 0% | ||
| DC | 23 | 36 | 36% | OH | 1,153 | 1,230 | 6% | ||
| FL | 3,185 | 3,331 | 4% | OK | 640 | 652 | 2% | ||
| GA | 1,492 | 1,664 | 10% | OR | 493 | 508 | 3% | ||
| HI | 108 | 85 | -27% | PA | 1,059 | 1,129 | 6% | ||
| ID | 224 | 214 | -5% | RI | 57 | 67 | 15% | ||
| IL | 1,009 | 1,194 | 15% | SC | 1,006 | 1,064 | 5% | ||
| IN | 810 | 897 | 10% | SD | 102 | 141 | 28% | ||
| IA | 336 | 337 | 0% | TN | 1,136 | 1,217 | 7% | ||
| KS | 410 | 426 | 4% | TX | 3,619 | 3,874 | 7% | ||
| KY | 732 | 780 | 6% | UT | 248 | 276 | 10% | ||
| LA | 727 | 828 | 12% | VT | 47 | 62 | 24% | ||
| ME | 157 | 164 | 4% | VA | 831 | 850 | 2% | ||
| MD | 535 | 587 | 9% | WA | 538 | 560 | 4% | ||
| MA | 336 | 343 | 2% | WV | 260 | 267 | 3% | ||
| MI | 986 | 1,084 | 9% | WI | 567 | 614 | 8% | ||
| MN | 364 | 394 | 8% | WY | 147 | 127 | -16% | ||
| MS | 642 | 752 | 15% | ||||||
| MO | 881 | 987 | 11% | USA TOTAL | 36355 | 38844 | 6% | ||
| MT | 184 | 213 | 14% | PR | 289 | 242 | -19% | ||
| *Note: Totals may not equal the sum of components from source due to independent rounding |
In a separate document, prepare responses to the following questions in one to two:
- Describe the steps you took to make the data usable. Explain the purpose of each step.
- Which aspects of this task were difficult? Explain.
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