Natural gas

core

Files Size Format Created Updated License Source
3 1006kB csv zip 2 months ago EIA
Time series of major Natural Gas Prices including US Henry Hub. Data comes from U.S. Energy Information Administration EIA ## Data Dataset contains Monthly and Daily prices of Natural gas, starting from January 1997, including April 2016. Prices are in nominal dollars. License Public domain read more
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Data Files

File Description Size Last changed Download Other formats
natural-gas-daily [csv] 80kB natural-gas-daily [csv] natural-gas-daily [json] (80kB)
natural-gas-monthly [csv] 4kB natural-gas-monthly [csv] natural-gas-monthly [json] (4kB)
natural-gas_zip [zip] Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 76kB natural-gas_zip [zip]

natural-gas-daily  

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)
Price 2 string

natural-gas-monthly  

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)
Price 2 string

natural-gas_zip  

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

Read me

Time series of major Natural Gas Prices including US Henry Hub. Data comes from U.S. Energy Information Administration EIA

## Data

Dataset contains Monthly and Daily prices of Natural gas, starting from January 1997, including April 2016. Prices are in nominal dollars.

License

  • Public domain and use of EIA content

U.S. government publications are in the public domain and are not subject to copyright protection. One may use and/or distribute any of data, files, databases, reports, graphs, charts, and other information products that are on website. For more information please visit: Copyrights and Reuse

Import into your tool

In order to use Data Package in R follow instructions below:

install.packages("devtools")
library(devtools)
install_github("hadley/readr")
install_github("ropenscilabs/jsonvalidate")
install_github("ropenscilabs/datapkg")

#Load client
library(datapkg)

#Get Data Package
datapackage <- datapkg_read("https://pkgstore.datahub.io/core/natural-gas/latest")

#Package info
print(datapackage)

#Open actual data in RStudio Viewer
View(datapackage$data$"natural-gas-daily")
View(datapackage$data$"natural-gas-monthly")
View(datapackage$data$"natural-gas_zip")

Tested with Python 3.5.2

To generate Pandas data frames based on JSON Table Schema descriptors we have to install jsontableschema-pandas plugin. To load resources from a data package as Pandas data frames use datapackage.push_datapackage function. Storage works as a container for Pandas data frames.

In order to work with Data Packages in Pandas you need to install our packages:

$ pip install datapackage
$ pip install jsontableschema-pandas

To get Data Package run following code:

import datapackage

data_url = "https://pkgstore.datahub.io/core/natural-gas/latest/datapackage.json"

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

# to see datasets in this package
storage.buckets

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

In order to work with Data Packages in Python you need to install our packages:

$ pip install datapackage

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

import datapackage

dp = datapackage.DataPackage('https://pkgstore.datahub.io/core/natural-gas/latest/datapackage.json')

# see metadata
print(dp.descriptor)

# get list of csv files
csvList = [dp.resources[x].descriptor['name'] for x in range(0,len(dp.resources))]
print(csvList) # ["resource name", ...]

# access csv file by the index starting 0
print(dp.resources[0].data)

To use this dataset in JavaScript, please, follow instructions below:

Install data.js module using npm:

  $ npm install data.js

Once the package is installed, use code snippet below:

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

  const path = 'https://pkgstore.datahub.io/core/natural-gas/latest/datapackage.json'

  const dataset = Dataset.load(path)

  // get a data file in this dataset
  const file = dataset.resources[0]
  const data = file.stream()

In order to work with Data Packages in SQL you need to install our packages:

$ pip install datapackage
$ pip install jsontableschema-sql
$ pip install sqlalchemy

To import Data Package to your SQLite Database, run following code:

import datapackage
from sqlalchemy import create_engine

data_url = 'https://pkgstore.datahub.io/core/natural-gas/latest/datapackage.json'
engine = create_engine('sqlite:///:memory:')

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

# to see datasets in this package
storage.buckets

# to execute sql command (assuming data is in "data" folder, name of resource is data and file name is data.csv)
storage._Storage__connection.execute('select * from data__data___data limit 1;').fetchall()

# description of the table columns
storage.describe('data__data___data')
Datapackage.json