Motor Vehicle Safety Data

JohnSnowLabs

Files Size Format Created Updated License Source
2 41kB csv zip 2 weeks ago John Snow Labs Standard License John Snow Labs Bureau of Transportation Statistics
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Data Files

File Description Size Last changed Download Other formats
motor-vehicle-safety-data-csv [csv] 2kB motor-vehicle-safety-data-csv [csv] motor-vehicle-safety-data-csv [json] (9kB)
motor-vehicle-safety-data_zip [zip] Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 6kB motor-vehicle-safety-data_zip [zip]

motor-vehicle-safety-data-csv  

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

Field information

Field Name Order Type (Format) Description
Year 1 date (%Y-%m-%d) Year of data
Fatalities 2 integer Number of fatalities. Fatalities data prior to 1975 have been adjusted to reflect the Fatality Analysis Reporting System's definition of a fatal crash as one that involves a motor vehicle on a trafficway, which results in the death of a vehicle occupant or a nonmotorist within 30 days of the crash.
Injured_Persons 3 integer Number of injured persons
Crashes 4 integer Crashes are the rounded sum of fatal crashes, an actual count from the Fatality Analysis Reporting System, and injury crashes and property damage only crashes, which are estimates from the National Automotive Sampling System-General Estimates System.
Vehicle_Miles_In_Millions 5 integer Distance covered by vehicles
Fatalities_Rates_Per_100_Million_Vehicle_Miles 6 number Rate of fatalities per 100 million vehicle miles
Injured_Persons_Rates_Per_100_Million_Vehicle_Miles 7 integer Rate of injured persons per 100 million vehicle miles
Crashes_Rates_Per_100_Million_Vehicle_Miles 8 integer Rate of crashes per 100 million vehicle miles

motor-vehicle-safety-data_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/motor-vehicle-safety-data/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/motor-vehicle-safety-data/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/motor-vehicle-safety-data/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/motor-vehicle-safety-data/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/motor-vehicle-safety-data/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