Car crashes (NY state)¶

Project Description¶

For this project, I will be observing the reasons for crashes in New York State. Through the datasets seen below, I will be answering question such as: What are the most common reason for crashes? How do certain attributes (type of vehicle, what combination of vehicle, amount of people in the car, and/or which borough) affects the rate of crashes?  This data's purpose is to help educate younger, novice drivers and experienced drivers to be more alert in someparts of their driving to create a safer environment.

Explaining the data¶

There is one dataset for this project. The data is quite recent (2021), showcasing both vehicles in the crash, the borough, and the reason for the accident which are the most important information. There are many undected reasons for car crashes, and finding patterns, such as one borough having a high accident rate, could stem from needing to change

How will the data be used?¶

Through the various characteristics car accidents in New York, we can evaluate trends of causes in vehicle accidents. This will ultimately lead to a better education for drivers, as there are many reasons and variables affecting the accidents.
In [6]:
import pandas as pd

df = pd.read_csv("Motor_Vehicle_Collisions.csv")

dataframe = pd.DataFrame(df)

/var/folders/xf/q51vqvcd7tldds39hdqsmqsw0000gn/T/ipykernel_29637/2179601569.py:3: DtypeWarning: Columns (3) have mixed types. Specify dtype option on import or set low_memory=False.
  df = pd.read_csv("Motor_Vehicle_Collisions.csv")
In [8]:
dataframe
Out[8]:
CRASH DATE CRASH TIME BOROUGH ZIP CODE LATITUDE LONGITUDE LOCATION ON STREET NAME CROSS STREET NAME OFF STREET NAME ... CONTRIBUTING FACTOR VEHICLE 2 CONTRIBUTING FACTOR VEHICLE 3 CONTRIBUTING FACTOR VEHICLE 4 CONTRIBUTING FACTOR VEHICLE 5 COLLISION_ID VEHICLE TYPE CODE 1 VEHICLE TYPE CODE 2 VEHICLE TYPE CODE 3 VEHICLE TYPE CODE 4 VEHICLE TYPE CODE 5
0 09/11/2021 2:39 NaN NaN NaN NaN NaN WHITESTONE EXPRESSWAY 20 AVENUE NaN ... Unspecified NaN NaN NaN 4455765 Sedan Sedan NaN NaN NaN
1 03/26/2022 11:45 NaN NaN NaN NaN NaN QUEENSBORO BRIDGE UPPER NaN NaN ... NaN NaN NaN NaN 4513547 Sedan NaN NaN NaN NaN
2 06/29/2022 6:55 NaN NaN NaN NaN NaN THROGS NECK BRIDGE NaN NaN ... Unspecified NaN NaN NaN 4541903 Sedan Pick-up Truck NaN NaN NaN
3 09/11/2021 9:35 BROOKLYN 11208.0 40.667202 -73.866500 (40.667202, -73.8665) NaN NaN 1211 LORING AVENUE ... NaN NaN NaN NaN 4456314 Sedan NaN NaN NaN NaN
4 12/14/2021 8:13 BROOKLYN 11233.0 40.683304 -73.917274 (40.683304, -73.917274) SARATOGA AVENUE DECATUR STREET NaN ... NaN NaN NaN NaN 4486609 NaN NaN NaN NaN NaN
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
1971216 02/09/2023 20:00 BROOKLYN 11237.0 40.707684 -73.928860 (40.707684, -73.92886) NaN NaN 89 PORTER AVENUE ... Unspecified NaN NaN NaN 4607751 Motorcycle NaN NaN NaN NaN
1971217 02/21/2023 12:08 BRONX 10457.0 40.844177 -73.902920 (40.844177, -73.90292) WEBSTER AVENUE EAST 174 STREET NaN ... Unsafe Speed NaN NaN NaN 4607512 Sedan Bike NaN NaN NaN
1971218 01/27/2023 20:13 QUEENS 11373.0 40.734135 -73.869180 (40.734135, -73.86918) 92 STREET 59 AVENUE NaN ... NaN NaN NaN NaN 4607965 NaN NaN NaN NaN NaN
1971219 02/16/2023 8:30 QUEENS 11101.0 40.755928 -73.919280 (40.755928, -73.91928) 34 AVENUE 42 STREET NaN ... Unspecified NaN NaN NaN 4607996 Sedan NaN NaN NaN NaN
1971220 02/21/2023 12:25 NaN NaN NaN NaN NaN NaN NaN 59-11 Arnold Avenue ... Unspecified NaN NaN NaN 4607592 Dump Sedan NaN NaN NaN

1971221 rows × 29 columns

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