Energy Consumed In Transit Modes Of Transportation

JohnSnowLabs

Files Size Format Created Updated License Source
2 43kB csv zip 3 months ago John Snow Labs Standard License John Snow Labs Bureau of Transportation Statistics
Download

Data Files

File Description Size Last changed Download
energy-consumed-in-transit-modes-of-transportation-csv 2kB csv (2kB) , json (11kB)
energy-consumed-in-transit-modes-of-transportation_zip Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 5kB zip (5kB)

energy-consumed-in-transit-modes-of-transportation-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
Number_Of_Vehicles_In_Millions 2 integer Number of transit vehicle in millions
Vehicle_Miles_Travelled_In_Millions 3 integer Distance travelled by transit vehicle in million miles
Electric_Power_Consumed_In_Million_Kilowatthours 4 integer Electrical energy consumed by transit vehice in million kilowatthours
Primary_Diesel_Energy_Consumed_In_Thousand_Gallons 5 integer Primary energy as diesel consumed by transit vehicle in thouand gallons
Primary_Gasoline_Energy_Consumed_In_Thousand_Gallons 6 integer Primary energy as gasoline consumed by transit vehicle in thousand gallons
Primary_Compressed_Natural_Gas_Energy_Consumed_In_Thousand_Gallons 7 integer Primary energy as compressed natural gas consumed by transit vehicle in thousand gallons

Import into your tool

Data-cli or just data is the program to get and post your data with the datahub.
Use data with the datahub.io almost like you use git with the github. Here are installation instructions.

data get https://datahub.io/JohnSnowLabs/energy-consumed-in-transit-modes-of-transportation
tree JohnSnowLabs/energy-consumed-in-transit-modes-of-transportation
# Get a list of dataset's resources
curl -L -s https://datahub.io/JohnSnowLabs/energy-consumed-in-transit-modes-of-transportation/datapackage.json | grep path

# Get resources

curl -L https://datahub.io/JohnSnowLabs/energy-consumed-in-transit-modes-of-transportation/r/0.csv

curl -L https://datahub.io/JohnSnowLabs/energy-consumed-in-transit-modes-of-transportation/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/energy-consumed-in-transit-modes-of-transportation/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/energy-consumed-in-transit-modes-of-transportation/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/energy-consumed-in-transit-modes-of-transportation/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/energy-consumed-in-transit-modes-of-transportation/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)
    }
  }
})()
Datapackage.json