Motor Vehicle Safety Data

JohnSnowLabs

Files Size Format Created Updated License Source
2 39kB csv zip 3 years ago John Snow Labs Standard License John Snow Labs Bureau of Transportation Statistics
The dataset contains information on the motor vehicle fatalities on U.S. roads with number of fatalities, crashes, number of injured persons and miles covered by vehicles. National Transportation... read more
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Data Files

Download files in this dataset

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

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

Integrate this dataset into your favourite tool

Use our data-cli tool designed for data wranglers:

data get https://datahub.io/JohnSnowLabs/motor-vehicle-safety-data
data info JohnSnowLabs/motor-vehicle-safety-data
tree JohnSnowLabs/motor-vehicle-safety-data
# Get a list of dataset's resources
curl -L -s https://datahub.io/JohnSnowLabs/motor-vehicle-safety-data/datapackage.json | grep path

# Get resources

curl -L https://datahub.io/JohnSnowLabs/motor-vehicle-safety-data/r/0.csv

curl -L https://datahub.io/JohnSnowLabs/motor-vehicle-safety-data/r/1.zip

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

install.packages("jsonlite", repos="https://cran.rstudio.com/")
library("jsonlite")

json_file <- 'https://datahub.io/JohnSnowLabs/motor-vehicle-safety-data/datapackage.json'
json_data <- fromJSON(paste(readLines(json_file), collapse=""))

# get list of all resources:
print(json_data$resources$name)

# print all tabular data(if exists any)
for(i in 1:length(json_data$resources$datahub$type)){
  if(json_data$resources$datahub$type[i]=='derived/csv'){
    path_to_file = json_data$resources$path[i]
    data <- read.csv(url(path_to_file))
    print(data)
  }
}

Note: You might need to run the script with root permissions if you are running on Linux machine

Install the Frictionless Data data package library and the pandas itself:

pip install datapackage
pip install pandas

Now you can use the datapackage in the Pandas:

import datapackage
import pandas as pd

data_url = 'https://datahub.io/JohnSnowLabs/motor-vehicle-safety-data/datapackage.json'

# to load Data Package into storage
package = datapackage.Package(data_url)

# to load only tabular data
resources = package.resources
for resource in resources:
    if resource.tabular:
        data = pd.read_csv(resource.descriptor['path'])
        print (data)

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('https://datahub.io/JohnSnowLabs/motor-vehicle-safety-data/datapackage.json')

# print list of all resources:
print(package.resource_names)

# print processed tabular data (if exists any)
for resource in package.resources:
    if resource.descriptor['datahub']['type'] == 'derived/csv':
        print(resource.read())

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 = 'https://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 list of all resources:
  for (const id in dataset.resources) {
    console.log(dataset.resources[id]._descriptor.name)
  }
  // get all tabular data(if exists any)
  for (const id in dataset.resources) {
    if (dataset.resources[id]._descriptor.format === "csv") {
      const file = dataset.resources[id]
      // Get a raw stream
      const stream = await file.stream()
      // entire file as a buffer (be careful with large files!)
      const buffer = await file.buffer
      // print data
      stream.pipe(process.stdout)
    }
  }
})()

Read me

The dataset contains information on the motor vehicle fatalities on U.S. roads with number of fatalities, crashes, number of injured persons and miles covered by vehicles. National Transportation Statistics presents statistics on the U.S. transportation system, including its physical components, safety record, economic performance, the human and natural environment, and national security. Transportation's safety record, giving data on accidents, crashes, fatalities, and injuries for each transportation mode and hazardous materials. Compiled and published by the U.S. Department of Transportation's Bureau of Transportation Statistics (BTS), National Transportation Statistics presents information on the U.S. transportation system, including its physical components, safety record, economic performance, energy use, and environmental impacts.
Datapackage.json