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Citation:
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Citation Information:
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Title: Coal Power Plants
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Geospatial Data Presentation Form: vector digital data
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Description:
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Abstract: The dataset began as an Excel file containing multiple sheets related to coal and natural gas power plants. Each sheet was read and processed using Pandas, a data manipulation library in Python. The data was categorized based on the energy source code into coal and natural gas datasets. From these datasets, subsets focusing on operating and retired power plants were created. Key attributes, such as 'Entity ID', 'Plant Name', and 'Capacity', were selected, and their data types were adjusted for consistency. Notably, 'Planned Retirement Year' in the operating subset and equivalent fields in the retired subset were filled with 'NA' for missing values, and all column names were standardized. These subsets were then aggregated by 'Plant ID', applying specific rules like 'first' for categorical fields and 'sum' for numerical fields. The aggregated datasets were merged based on shared attributes like 'Entity ID' and 'Plant ID', forming a comprehensive dataset. This merged data was then converted into a GeoDataFrame using GeoPandas, assigning geographic point locations based on 'Latitude' and 'Longitude'. The geospatial data was exported as a GeoPackage file, suitable for importing into ArcGIS Pro as feature classes. The resulting spatial layers offer insights into the distribution, capacity, and operational status of power plants across different energy types.
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Purpose: This geospatial dataset provides a detailed overview of coal power plants grouped by Plant ID, derived from the EIA-860M form data, and processed for spatial analysis.
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Keywords:
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Theme:
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Theme Keyword Thesaurus: None
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Theme Keyword: coal
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Theme Keyword: power plant
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Theme Keyword: generator
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Theme Keyword: eia
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Access Constraints: None
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Use Constraints: USE LIMITATION: This project was funded by the United States Department of Energy, National Energy Technology Laboratory, in part, through a site support contract. Neither the United States Government nor any agency thereof, nor any of their employees, nor the support contractor, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.
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Data Set Credit: Original Data: U.S. Energy Information Administration's EIA-860M data
Original Data Source Weblink: https://www.eia.gov/electricity/data/eia860m/
Original Data Release Date: September 2023
Source Use Restrictions: This dataset is publicly available and can be freely used, with proper citation to the U.S. Energy Information Administration's EIA-860M as the original data source.
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Native Data Set Environment: Esri ArcGIS 13.2.0.49743