NYPD Motor Vehicle Collisions

JohnSnowLabs

Files Size Format Created Updated License Source
2 1GB csv zip 1 week ago John Snow Labs Standard License John Snow Labs City of New York
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Data Files

File Description Size Last changed Download Other formats
nypd-motor-vehicle-collisions-csv [csv] 163MB nypd-motor-vehicle-collisions-csv [csv] nypd-motor-vehicle-collisions-csv [json] (852MB)
nypd-motor-vehicle-collisions_zip [zip] Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 104MB nypd-motor-vehicle-collisions_zip [zip]

nypd-motor-vehicle-collisions-csv  

This is a preview version. There might be more data in the original version.

Field information

Field Name Order Type (Format) Description
Date 1 date (%Y-%m-%d) Collision Date
Time 2 time (%H:%M:%S) Time Of Collision
Borough 3 string Borough
ZIP_Code 4 integer ZIP Code
Latitude 5 number Latitude Location
Longitude 6 number Latitude Location
On_Street_Name 7 string On Street Name
Cross_Street_Name 8 string Cross Street Name
Off_Street_Name 9 string Off Street Name
Number_Of_Persons_Injured 10 integer Number Of Persons Injured
Number_Of_Persons_Killed 11 integer Number_OfPersons Killed
Number_Of_Pedestrians_Injured 12 integer Number Of Pedestrians Injured
Number_Of_Pedestrians_Killed 13 integer Number Of Persons Killed
Number_Of_Cyclist_Injured 14 integer Number Of Cyclist Injured
Number_Of_Cyclist_Killed 15 integer Number Of Cyclist Killed
Number_Of_Motorist_Injured 16 integer Number Of Motorist Injured
Number_Of_Motorist_Killed 17 integer Number Of Motorist Killed
Contributing_Facto_Vehicle_1 18 string Contributing Facto Vehicle 1
Contributing_Facto_Vehicle_2 19 string Contributing Facto Vehicle 2
Contributing_Facto_Vehicle_3 20 string Contributing Facto Vehicle 3
Contributing_Facto_Vehicle_4 21 string Contributing Facto Vehicle 4
Contributing_Facto_Vehicle_5 22 string Contributing Facto Vehicle 5
Unique_Key 23 integer Unique Key
Vehicle_Type_Code_1 24 string Vehicle Type Code
Vehicle_Type_Code_2 25 string Vehicle Type Code 2
Vehicle_Type_Code_3 26 string Vehicle Type Code 3
Vehicle_Type_Code_4 27 string Vehicle Type Code 4
Vehicle_Type_Code_5 28 string Vehicle Type Code 5

nypd-motor-vehicle-collisions_zip  

This is a preview version. There might be more data in the original version.

Read me

Import into your tool

If you are using R here's how to get the data you want quickly loaded:

install.packages("jsonlite")
library("jsonlite")

json_file <- "http://datahub.io/JohnSnowLabs/nypd-motor-vehicle-collisions/datapackage.json"
json_data <- fromJSON(paste(readLines(json_file), collapse=""))

# access csv file by the index starting from 1
path_to_file = json_data$resources$path[1][1]
data <- read.csv(url(path_to_file))
print(data)

In order to work with Data Packages in Pandas you need to install the Frictionless Data data package library and the pandas extension:

pip install datapackage
pip install jsontableschema-pandas

To get the data run following code:

import datapackage

data_url = "http://datahub.io/JohnSnowLabs/nypd-motor-vehicle-collisions/datapackage.json"

# to load Data Package into storage
storage = datapackage.push_datapackage(data_url, 'pandas')

# data frames available (corresponding to data files in original dataset)
storage.buckets

# you can access datasets inside storage, e.g. the first one:
storage[storage.buckets[0]]

For Python, first install the `datapackage` library (all the datasets on DataHub are Data Packages):

pip install datapackage

To get Data Package into your Python environment, run following code:

from datapackage import Package

package = Package('http://datahub.io/JohnSnowLabs/nypd-motor-vehicle-collisions/datapackage.json')

# get list of resources:
resources = package.descriptor['resources']
resourceList = [resources[x]['name'] for x in range(0, len(resources))]
print(resourceList)

data = package.resources[0].read()
print(data)

If you are using JavaScript, please, follow instructions below:

Install data.js module using npm:

  $ npm install data.js

Once the package is installed, use the following code snippet:

const {Dataset} = require('data.js')

const path = 'http://datahub.io/JohnSnowLabs/nypd-motor-vehicle-collisions/datapackage.json'

// We're using self-invoking function here as we want to use async-await syntax:
(async () => {
  const dataset = await Dataset.load(path)

  // Get the first data file in this dataset
  const file = dataset.resources[0]
  // Get a raw stream
  const stream = await file.stream()
  // entire file as a buffer (be careful with large files!)
  const buffer = await file.buffer
})()

Install the datapackage library created specially for Ruby language using gem:

gem install datapackage

Now get the dataset and read the data:

require 'datapackage'

path = 'http://datahub.io/JohnSnowLabs/nypd-motor-vehicle-collisions/datapackage.json'

package = DataPackage::Package.new(path)
# So package variable contains metadata. You can see it:
puts package

# Read data itself:
resource = package.resources[0]
data = resource.read
puts data
Datapackage.json