Science Score: 44.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
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  • Scientific vocabulary similarity
    Low similarity (14.6%) to scientific vocabulary
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Repository

Basic Info
  • Host: GitHub
  • Owner: drofphilosophe
  • License: apache-2.0
  • Language: R
  • Default Branch: main
  • Size: 1.13 MB
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Created almost 4 years ago · Last pushed about 1 year ago
Metadata Files
Readme License Citation

README.md

United States Electricity Data

This is a repository of code to download, compile and clean high-frequency electricty generation and emissions data for the United States.

License

   Copyright 2022 James Archsmith and Paige Weber

   Licensed under the Apache License, Version 2.0 (the "License");
   you may not use this file except in compliance with the License.
   You may obtain a copy of the License at

       http://www.apache.org/licenses/LICENSE-2.0

   Unless required by applicable law or agreed to in writing, software
   distributed under the License is distributed on an "AS IS" BASIS,
   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
   See the License for the specific language governing permissions and
   limitations under the License.
 

Using this package

Code in this package will download and clean up data from many sources. The code is designed to run in a custom Anaconda (https://www.anaconda.com/) environment defined by the configuration file USElecData_conda.yaml. To use the code in this repository you should do the following: 1. Install Anaconda on your system. It is available at https://www.anaconda.com 2. Clone this repository 3. Navigate to the root directory and this repo and create an Anaconda environment using the command

conda env create -f USElecData_conda.yaml

  1. Activate the USElecData Anaconda environment using the command

conda activate USElecData

  1. Initialize the configuration of your environment using the command

Windows: USElecData init --output-path=<path_to_ouput_data>

Mac/Linux: ./USElecData.sh init --output-path=<path_to_ouput_data>

This will create a local configuration file and set environment variables within your enviroment that scripts will use later. The <path_to_output_data> is a folder where you would like the data to be stored on your local system. Anticiapte serveral hundred gigabytes. During this process you will be prompted to enter an API key for Data.gov. This is required to access some US government data APIs. If you don't currently have an API key, the script will provide a link for you to sign up for one.

  1. De/Reactivate your the USElecData Anaconda environment using the commands

conda deactivate

conda activate USElecData

  1. Download all the original source data with the command

Windows: USElecData source all

Mac/Linux: ./USElecData.sh source all

  1. Build all output data files

Windows: USElecData build all

Mac/Linux: ./USElecData.sh build all

Running outside Anaconda or in a different environment

It is strongly recommended you run all the code in this repository in the Anaconda environment defined by USElecData_conda.yaml. This provides a clean and consistent environment for all of the code, handles package management and enables several features that will hopefully streamline the build process. The code has only been tested against that environment. It will possibly run outside the enviroment (with some work), but you may encounter unforseen errors.

At a minimum you will need to put the file src/lib/USElecDataClass.py somewhere in your path (one possibility is to add src/lib to your PYTHONPATH environment variable).

Legacy Instructions

Initially this data repository needed to be built through a series of manual steps. These instructions cover those steps.

After pulling the repo, you should create a local configuration file by editing ./config_local_template.yaml to point to the local path where you will store source, intermediate, and output data. Save this file as ./config_local.yaml. DO NOT MAKE YOUR DATA PATH A SUBDIRECTORY OF YOUR LOCAL CODE REPOSITORY. You should then run each of the Python/R scripts in the order described in the Markdown file in each subfolder of the src directory. The src folders should be loaded an cleaned in the following order: 1. tz-info 2. EIA-Form860 3. EIA-Form923 4. EPA-CEMS

Owner

  • Name: James Archsmith
  • Login: drofphilosophe
  • Kind: user

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Archsmith"
  given-names: "James"
  orcid: "https://orcid.org/0000-0002-6052-0302"
- family-names: "Weber"
  given-names: "Paige"
title: "US Electricity Data"
version: 0.1.0
date-released: 2022-04-12
license: APache-2.0
identifiers:
 - description: "US Electricity Data Practitioners Guide"
   type: url
   value: "https://econjim.com/WP202201"
 - description: "US Electricity Data Code Repository"
   type: url
   value: "https://github.com/drofphilosophe/USElecData"
keywords:
 - Electrity
 - Emissions
 
url: "https://github.com/drofphilosophe/USElecData"

preferred-citation:
  authors:
   - family-names: Archsmith
     given-names: "James E."
   - family-names: Weber
     given-names: Paige
  title: "US Electricity Data Pratictioners Guide"
  type: Article
  year: 2022

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