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Regional Growth and Cultural Tourism Development Scenarios Associated with the Bears Ears National Monument Cultural Center

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DataCite Commons2025-03-20 更新2025-04-16 收录
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<b>Overview</b><br>The Jupyter notebook (Bears_Ears_Economic_Impact.pynb) includes all Python code to process data and create all figures reported in the manuscript. The code can also be accessed via Google Colab here (https://colab.research.google.com/drive/19QptKut-FHMs0OIG6N9O7_C9qr_pSZC8?usp=sharing). All code is heavily commented and should be interpretable.<br><br><b>Bureau of Labor Statistics Data and Analyses<br></b>All Bureau of Labor Statistics data were acquired from the agency’s Quarterly Census on Employment and Wages online data portal (https://www.bls.gov/cew/downloadable-data-files.htm). These data are provided in the ‘BLS.zip’ file. You can extract these data and place them in a local drive, access the files via the Python code provided, and proceed through the creation of the figures.<br><br><b>Economic Impact Data<br></b>Economic impact data, provided after the analyses for each scenario was run, are provided in both the ‘Economic_Impact_and_Tax_Revenues_Results.xlsx’ and ‘economic_indicators_data.csv’ files. The former is more interpretable for humans, the latter is called by the Python code provided to create the figures shown in the paper. The latter file will need to be placed in a local drive before executing the Python code which calls it.<br><br><b>Comments or Questions</b><br>Please direct any questions to Dr. Jordan W. Smith (jordan.smith@usu.edu).

<b>概述</b><br>本Jupyter笔记本(Bears_Ears_Economic_Impact.pynb)包含了用于处理数据并生成论文中所有图表的全部Python代码。该代码亦可通过以下Google Colab链接获取:https://colab.research.google.com/drive/19QptKut-FHMs0OIG6N9O7_C9qr_pSZC8?usp=sharing。所有代码均附带详细注释,具备良好的可解释性。<br><br><b>美国劳工统计局(Bureau of Labor Statistics, BLS)数据与分析</b><br>所有美国劳工统计局(BLS)数据均取自该机构的季度就业与工资普查(Quarterly Census on Employment and Wages)在线数据门户,访问链接为:https://www.bls.gov/cew/downloadable-data-files.htm。此类数据已打包至‘BLS.zip’压缩文件中。用户可将该压缩包内的数据解压至本地磁盘,通过本次提供的Python代码读取数据文件,进而完成图表的绘制流程。<br><br><b>经济影响数据</b><br>各场景分析运行完成后生成的经济影响数据,已分别存放于‘Economic_Impact_and_Tax_Revenues_Results.xlsx’与‘economic_indicators_data.csv’两个文件中。前者更便于人类直观解读,后者则会被本次提供的Python代码调用,用于生成论文中的对应图表。在运行调用该文件的Python代码前,需将后者存放至本地磁盘中。<br><br><b>意见与咨询</b><br>如有任何疑问,请联系乔丹·W·史密斯博士(邮箱:jordan.smith@usu.edu)。
提供机构:
ICPSR - Interuniversity Consortium for Political and Social Research
创建时间:
2025-03-20
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