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Natural gas prices

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core

Files Size Format Created Updated License Source
3 143kB csv zip 1 year ago 10 hours ago Open Data Commons Public Domain Dedication and License v1.0 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 to current year. Prices are in nominal dollars. Prpeartion You will need Python read more
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Data Files

Download files in this dataset

File Description Size Last changed Download
daily 674kB csv (674kB) , json (541kB)
monthly 31kB csv (31kB) , json (25kB)
natural-gas_zip Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 96kB zip (96kB)

daily  

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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 number (default)

monthly  

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

Field information

Field Name Order Type (Format) Description
Month 1 yearmonth (default)
Price 2 number (default)

Integrate this dataset into your favourite tool

Use our data-cli tool designed for data wranglers:

data get https://datahub.io/core/natural-gas
data info core/natural-gas
tree core/natural-gas
# Get a list of dataset's resources
curl -L -s https://datahub.io/core/natural-gas/datapackage.json | grep path

# Get resources

curl -L https://datahub.io/core/natural-gas/r/0.csv

curl -L https://datahub.io/core/natural-gas/r/1.csv

curl -L https://datahub.io/core/natural-gas/r/2.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/core/natural-gas/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/core/natural-gas/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/core/natural-gas/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/core/natural-gas/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

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 to current year. Prices are in nominal dollars.

Prpeartion

You will need Python 3.6 or greater and dataflows library to run the script

To update the data run the process script locally:

# Install dataflows
pip install dataflows

# Run the script
python natural_gas_flow.py

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

Datapackage.json

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