US Natural Gas Prices

JohnSnowLabs

Files Size Format Created Updated License Source
2 386kB csv zip 3 months ago John Snow Labs Standard License John Snow Labs U.S. Energy Information Administration
Download

Data Files

File Description Size Last changed Download
us-natural-gas-prices-csv 32kB csv (32kB) , json (268kB)
us-natural-gas-prices_zip Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 41kB zip (41kB)

us-natural-gas-prices-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) Month and year of data compilation
Wellhead_Price 2 number Price of natural gas calculated by dividing the total reported value at the wellhead by the total quantity produced as reported by the appropriate agencies of individual producing States and the U.S. Bureau of Ocean Energy Management, Regulation and Enforcement. The price includes all costs prior to shipment from the lease, including gathering and compression costs, in addition to State production, severance, and similar charges. The Wellhead Price estimate has been discontinued as of January 2013. Prices are calculated in "Dollars per Thousand Cubic Feet".
Natural_Gas_Imports_Price 3 number Natural Gas received in the Continental United States (including Alaska) from a foreign country. Prices are calculated in "Dollars per Thousand Cubic Feet".
Pipeline_Imports_Price 4 number Price of natural gas imported by pipeline. Prices are calculated in "Dollars per Thousand Cubic Feet".
LNG_Imports_Price 5 number Price of imported LNG (Liquified Natural Gas). Prices are calculated in "Dollars per Thousand Cubic Feet".
Natural_Gas_Exports_Price 6 number Natural Gas deliveries out of the Continental United States and Alaska to foreign countries. Prices are calculated in "Dollars per Thousand Cubic Feet".
Pipeline_Exports_Price 7 number Price of natural gas exported by pipeline. Prices are calculated in "Dollars per Thousand Cubic Feet".
Liquefied_Gas_Exports_Price 8 number Price of exported LNG (Liquified Natural Gas). Prices are calculated in "Dollars per Thousand Cubic Feet".
Citygate_Price 9 number City gate price of natural gas in U.S. Citygate is a point or measuring station at which a distributing gas utility receives gas from a natural gas pipeline company or transmission system. Prices are calculated in "Dollars per Thousand Cubic Feet".
Price_of_Gas_Delivered_to_Residential_Consumers 10 number The price of gas used in private dwellings, including apartments, for heating, cooking, water heating, and other household uses. Prices are calculated in "Dollars per Thousand Cubic Feet".
Percent_Total_Residential_Sales 11 number U.S. Natural Gas percentage of Total Residential Sales
Price_of_Gas_Sold_to_Commercial_Consumers 12 number The price of gas used by nonmanufacturing establishments or agencies primarily engaged in the sale of goods or services such as hotels, restaurants, wholesale and retail stores and other service enterprises; and gas used by local, State and Federal agencies engaged in nonmanufacturing activities. Prices are calculated in "Dollars per Thousand Cubic Feet".
Percent_Commercial_Deliveries 13 number Percent of Commercial Natural Gas Deliveries in U.S. Total Represented by the Price (%).
Industrial_Price 14 number The price of natural gas used for heat, power, or chemical feedstock by manufacturing establishments or those engaged in mining or other mineral extraction as well as consumers in agriculture, forestry, fisheries and construction. Prices are calculated in "Dollars per Thousand Cubic Feet".
Percent_Industrial_Deliveries 15 number Percent of Industrial Natural Gas Deliveries in U.S. Total Represented by the Price (%)
Electric_Power_Price 16 number The price of gas used by electricity generators (regulated utilities and non-regulated power producers) whose line of business is the generation of power. Prices are calculated in "Dollars per Thousand Cubic Feet".

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/us-natural-gas-prices
tree JohnSnowLabs/us-natural-gas-prices
# Get a list of dataset's resources
curl -L -s https://datahub.io/JohnSnowLabs/us-natural-gas-prices/datapackage.json | grep path

# Get resources

curl -L https://datahub.io/JohnSnowLabs/us-natural-gas-prices/r/0.csv

curl -L https://datahub.io/JohnSnowLabs/us-natural-gas-prices/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/us-natural-gas-prices/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/us-natural-gas-prices/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/us-natural-gas-prices/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/us-natural-gas-prices/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