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Homeland Infrastructure Foundation-Level Data: Electric Substations This feature class/shapefile represents electric power substations primarily associated with electric power transmission. In this layer, substations are considered facilities and equipment that switch, transform, or regulate electric power at voltages equal to, or greater than, 69 ...


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There's a number of places where you can read the UCC: Sales Leases And other places linked from the bottom of the wikipedia article. It's not completely clear to me if this is what you are looking for.


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This might be related to what you are looking for: CalTrans has a release of data on the Annual Average Daily Traffic (AADT) Volumes. More information could be found here.


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Pollen data In the United States, the National Allergy Bureau is the primary source of pollen measurements. Their network is comprised of approximately 80 monitoring stations which collect 24-hour samples of ambient pollen concentrations using either Burkard or Rotorod samplers. Simplified categories are presented on their website (e.g., "Weeds- Low ...


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https://api.carsxe.com/ The CarsXE API is a RESTful API with millions of vehicles and is updated daily. They provide 4 APIs: vehicle specifications, history, market value and ownership cost. The vehicle specifications API can return equipment data which would include all of the items you listed except images which would be returned from the photos data ...


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It depends what kind of text you're looking for. I can think of the following three sources for text data with years of publication: Project Gutenberg is a repository containing 60,000 books in the public domain. It includes a lot of literature classics. I don't think the original publication date is included but for many books it's not to hard to retrieve ...


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This is not an answer. If you visit https://sdmdataaccess.sc.egov.usda.gov/QueryHelp.aspx and download the "Table Column Descriptions Report (741K)" PDF, you will get a list of all tables (and column names) for your data. You can then go to https://sdmdataaccess.sc.egov.usda.gov/Query.aspx and make queries like SELECT * FROM chaashto. You will have to ...


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There is the Category:Bald men on Wikimedia Commons, right now with 525 images.


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It's not tagged, but one option would be to run the above algorithm on the NIST Mugshot dataset: https://www.nist.gov/srd/nist-special-database-18 The database consists of a total of 3248 images of variable size using PNG formatting with metadata TXT files corresponding to each per image. There are images of 1573 individuals (cases) 1495 male and 78 ...


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You could generate such a dataset using Python. A simple approach would be to generate a set of (x, y) coordinates, partition the set, then assign a distinct value for the z coordinate for each partition. An example with 100 points divided into 5 linearly separable partitions: from mpl_toolkits.mplot3d import Axes3D import matplotlib.pyplot as plt import ...


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For anyone else needing this information, it looks like Gaurav Sood compiled the relevant data and provided code to create the tables that link: DMA to county DMA to zip


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GS1 coordinates development of global trade code sets. Specifically I believe you want this GS1 code set, https://www.gs1.org/voc/PackagingMaterialTypeCode.


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This Scrabble dictionary shows you the validity of a word in real-time as you plug it in. I also like this site b/c they have 2 million words (and counting) in their database and let you vote and collaborate on their resources. Cheers :)


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There are several web applications the can calculate IRGF from latitude / longitude coordinates http://www.ngdc.noaa.gov/geomag-web/?model=igrf http://www.geomag.bgs.ac.uk/data_service/models_compass/igrf_form.shtml http://wdc.kugi.kyoto-u.ac.jp/igrf/point/index.html These sites are documented in the IGRF-12 online data products section of this paper: ...


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The easiest way to make your dataset eligible to be included in Dataset Search results is to upload it to a repository that adheres to metadata standards used by Dataset Search. There are many such repositories. You can try the following: https://zenodo.org https://figshare.com https://dataverse.harvard.edu https://www.kaggle.com/datasets https://data.world ...


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Alternative 1: This link from the page you shared contains historical minimum wage data for all 50 states and the Federal government. You could scrape the tables from this page using R like so: library(xml2) library(tidyverse) html <- xml2::read_html( "https://www.dol.gov/whd/state/stateMinWageHis.htm" ) html %>% rvest::html_table(fill = TRUE) ...


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