An Excel spreadsheet listing the information recorded on each of 18,686 costume designs can be viewed, downloaded, and explored. All the usual Excel sorting possibilities are available, and in addition a useful filter has been installed. For example, to find the number of designs that are Frieze Type #1, go to the top of the frieze type 2 column (column AS), click on the drop-down arrow and unselect every option box except True (i.e. True should be turned on, all other choices turned off). Then in the lower left corner, one reads “1111 of 18686 records found”.

Much more sophisticated exploration can be carried out by downloading the rich and flexible Access Database. The terms used for this database were described in detail in three sections of Deep Blue paper associated with this project. The database can be downloaded and explored.

HOW TO USE THE ACCESS DATABASE 1. Click on the Create Cohort and View Math Trait Data button, and select your cohort by clicking on the features of interest (for example: Apron and Blouse).

Note: Depending on how you exited on your previous visit to the database, there may be items to clear up before creating the cohorts.
a) (Usually unnecessary) Click on the small box near the top left corner to allow connection to Access. b) (Usually unnecessary) If an undesired window blocks part of the screen, click near the top of this window to minimize it. c) Make certain under Further Filtering that all four Exclude boxes are checked to get rid of stripes and circles, and circular buttons, and the D1 that is trivially associated with shoes.

1. Click on Filter Records to Form the Cohort button. Note the # of designs, # of pieces, and # of costumes beside Recalculate.

2. Click on Calculate Average Math Trait Frequency of Cohort button, and select the symmetry types of interest (for example: D1 and D2) .

3. To view the Stage 1 table, click on Create Stage 1 table. To edit and print this table, click on Create Excel (after table has been created). The same process works for Stages 2, 3.and 4 tables.

4. To view the matrix listing the math category impact numbers, move over to a button on the right side and click on View Matrix of Math Category Impact Numbers. To edit and print this matrix, click on Create Excel, use the Excel table as usual.

This dataset is designed to evaluate TabbyXL (version 1.1.0), a software platform for the rule-based transformation of spreadsheet data from arbitrary to relational tables, that is freely available at GitHub.

The dataset provides all required data to reproduce the performance evaluation including the program running and automatic performance evaluation of TabbyXL. The performance evaluation confirms the applicability of the implemented rulesets to process a bunch of different arbitrary tables of the same genre (government statistical websites). This demonstrates that TabbyXL can be used for developing programs for the transformation of spreadsheet data into the relational form.

README.md file included in this dataset provides a detail description of the data and steps to reproduce the experiment.

Excel spreadsheets by species (4 letter code is abbreviation for genus and species used in study, year 2010 or 2011 is year data collected, SH indicates data for Science Hub, date is date of file preparation). The data in a file are described in a read me file which is the first worksheet in each file. Each row in a species spreadsheet is for one plot (plant). The data themselves are in the data worksheet. One file includes a read me description of the column in the date set for chemical analysis. In this file one row is an herbicide treatment and sample for chemical analysis (if taken). This dataset is associated with the following publication: Olszyk , D., T. Pfleeger, T. Shiroyama, M. Blakely-Smith, E. Lee , and M. Plocher. Plant reproduction is altered by simulated herbicide drift toconstructed plant communities. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 36(10): 2799-2813, (2017).

Eccentric punching shear can occur in concrete slab-column connections when the connection is subjected to shear and unbalanced moments. Unbalanced moments occur in all floor slabs at the edge and corner columns. As such, this problem is of practical relevance. However, most punching experiments in the literature deal with concentric punching shear at internal columns. This paper presents a developed database of 128 experiments of flat slabs under eccentric punching shear, including a summary of the testing procedure of each reference and a description of the slab specimens. Additionally, a linear finite element analysis of all the specimens is included to determine the relevant sectional shear forces and moments. Finally, the ultimate shear stresses from the database experiments are compared to the shear capacities determined with ACI 318-19, Eurocode 2, and the Model Code 2010. The comparison shows that the Model Code 2010 is the most precise in the predictions with an average tested-to-predicted ratio of 0.82 and a coefficient of variation of 29.63%. It can be concluded that improvements to the current design methods for eccentric punching shear are necessary.

This excel spreadsheet is the result of merging at the port level of several of the in-house fisheries databases in combination with other demographic databases such as the U.S. census. The fisheries databases used include port listings, weighout (dealer) landings, permit information on homeports and owner cities of residence, dealer permit information, and logbook records. The database consoli...

Creating your own database is an excellent way for students to learn the trials and tribulations of data collection and management. Construction of three simple databases using a spreadsheet is described here and basic summary statistics are provided.

Nunes et al. Sports MDPI. Supplementary material 1. Database spreadsheet.

What is Blockchain? Blockchain seems complicated, and it definitely can be, but its core concept is really quite simple. A blockchain is a type of database. To be able to understand blockchain, it helps to first understand what a database actually is.

A database is a collection of information that is stored electronically on a computer system. Information, or data, in databases is typically structured in table format to allow for easier searching and filtering for specific information. What is the difference between someone using a spreadsheet to store information rather than a database?

Spreadsheets are designed for one person, or a small group of people, to store and access limited amounts of information. In contrast, a database is designed to house significantly larger amounts of information that can be accessed, filtered, and manipulated quickly and easily by any number of users at once.

Large databases achieve this by housing data on servers that are made of powerful computers. These servers can sometimes be built using hundreds or thousands of computers in order to have the computational power and storage capacity necessary for many users to access the database simultaneously. While a spreadsheet or database may be accessible to any number of people, it is often owned by a business and managed by an appointed individual that has complete control over how it works and the data within it.

conclusion: the theme is to do the perfect EDA of those 200 cryptos and explain them finey wrt features.

Spreadsheet database containing information relating to The National Archives

The Presolar Grain Database (PGD) contains the vast majority of isotope data (published and unpublished) on presolar grains and was first released as a collection of spreadsheets in 2009. It has been a helpful tool used by many researchers in cosmochemistry and astrophysics. However, over the years, accumulated errors compromised major parts of the PGD. Here, we provide a fresh start, with the PGD for graphite grains rebuilt from the ground up.

The PGD is provided here in two formats: (1) as Microsoft Excel (.xlsx) file, containing the main database as one large spreadsheet and additional information on extra spreadsheets, (2) as comma-separated ASCII (.csv) file containing the main database.

The PGD is also available for silicon carbide (SiC) grains at the DOI https://zenodo.org/doi/10.5281/zenodo.8187219.

a Food Standards Australia and New Zealand,b United States Department of Agriculture,c Food Standards Agency,d Separate databases for flavonoids, carotenoids, proanthocyanidins and isoflavones,e Eurofir EBASIS contains bioactive data for UK and Europe,f National Health Survey,ghttps://www.xyris.com.au/foodworks/fw_pro.html,hhttp://www.nutribase.com/highend.html,ihttp://www.foodresearch.ca/wp-content/uploads/2013/06/candat-features-1.pdf,j Tinuviel Software,i Downlees Systems,k Forestfield Software,l Kelicomp,mhttp://www.tinuvielsoftware.com/faqs.htm,nhttp://www.dietsoftware.com/canada.html,o Text file: a file that only contains text,p A file containing tables of information stored in columns and separated by tabs (can be exported into almost any spreadsheet program),q Microsoft Excel spreadsheet,r Microsoft Access Database file: is a database file with automated functions and queries,s American Standard Code for Information Interchange (a standard file type that can be used by many programs),t Database File Format (this file type can be opened with Microsoft Excel and Access),u information to create Excel or PDF available,v Composition of Foods, Australia,w International Network of Food Data System,x Users guide states food name is most descriptive & recognisable of food referencedyhttp://www.foodstandards.gov.au/science/monitoringnutrients/nutrientables/nuttab/Pages/NUTTAB-2010-electronic-database-files.aspx,zhttp://www.foodstandards.gov.au/science/monitoringnutrients/ausnut/ausnutdatafiles/Pages/default.aspx,aahttp://ndb.nal.usda.gov/ndb/search/list,bbhttp://tna.europarchive.org/20110116113217/http://www.food.gov.uk/science/dietarysurveys/dietsurveys/,cchttp://webprod3.hc-sc.gc.ca/cnf-fce/index-eng.jspDesktop analysis and examination of six key food composition databases format.

The Forest Inventory Database Management System is made of three parts; the factory database where field data is ingested and calculations, relationships, and summaries are developed. Summaries statistics are then manicured in the report databases, and then displayed within a spreadsheet workbook.

The Presolar Grain Database (PGD) contains the vast majority of isotope data (published and unpublished) on presolar grains and was first released as a collection of spreadsheets in 2009. It has been a helpful tool used by many researchers in cosmochemistry and astrophysics. However, over the years, accumulated errors compromised major parts of the PGD. Here, we provide a fresh start, with the PGD for silicon carbide (SiC) grains rebuilt from the ground up.

The PGD is provided here in two formats: (1) as Microsoft Excel (.xlsx) file, containing the main database as one large spreadsheet and additional information on extra spreadsheets, (2) as comma-separated ASCII (.csv) file containing the main database.

Systematic Review Database Extraction Spreadsheet. See https://ro-journal.biomedcentral.com/articles/10.1186/s13014-022-02146-8

Spreadsheet database containing user and cost information relating to The National Archives

This dataset contains in-depth statistics for League of Legends matchups involving Varus. The data is the result of extensive analysis of hundreds of thousands to millions of games, processed through a data pipeline directly from the Riot API. This page features interactive UI elements, including filter buttons for roles (Top, Mid, Jungle, Bot, Support) and a search bar to filter matchups by opponent champion. Our unique data provides unparalleled insights that are not available on competitor websites. Including matchup-specific tips, skill order, rune setups, summoner spells, item builds, and detailed in-game statistics such as gold differences, damage metrics, KDA ratios, gank frequencies, cooldown comparisons, and experience point differences. Whether you're looking to improve your gameplay or gain a competitive edge, this dataset is an invaluable resource for mastering the Varus matchups.

The datasets in the .pdf and .zip attached to this record are in support of Intelligent Transportation Systems Joint Program Office (ITS JPO) report FHWA-JPO-15-222, "Impacts Assessment of Dynamic Speed Harmonization with Queue Warning: Task 3, Impacts Assessment Report". The files in these zip files are specifically related to the US-101 Testbed, near San Mateo, CA. The uncompressed and compressed files total 2.0265 GB in size. The files have been uploaded as-is; no further documentation was supplied by NTL. All located .docx files were converted to .pdf document files which are an open, archival format. These .pdfs were then added to the zip file alongside the original .docx files. The attached zip files can be unzipped using any zip compression/decompression software. These zip file contains files in the following formats: .pdf document files which can be read using any pdf reader; .xlsxm macro-enabled spreadsheet files which can be read in Microsoft Excel and some Tech Report spreadsheet programs; .accdb database files which may be opened with Microsoft Access Database software and Tech Report open database software applications ; as well as .db generic database files, often associated with thumbnail images in the Windows operating environment. [software requirements] These files were last accessed in 2017. File and .zip file names include: FHWA_JPO_15_222_INFLO_Performance_Measure_METADATA.pdf ; FHWA_JPO_15_222_INFLO_Performance_Measure_METADATA.docx ; FHWA_JPO_15_222_INFLO_VISSIM_Output_and_Analysis_Spreadsheets.zip ; FHWA_JPO_15_222_INFLO_Spreadsheet_PDFs.zip ; FHWA_JPO_15_222_DATA_CV50.zip ; and, FHWA_JPO_15_222_DATA_CV25.zip

Describes methods and procedures, data generation and evaluation, formats of tables, data dissemination, references cited in the documentation and database, and other miscellaneous information about this database. Resource Title: Fluoride Database of Selected Beverages and Foods (Release 2). File Name: F02.xlsResource Description: This file contains the Fluoride Database imported into a Microsoft Excel spreadsheet. You need Excel 2000 or later to use this file.

The SEABORNE (Sustainable UsE And Benefits fOR mariNE) has consolidated and synthesised existing information about who is using the Reef, how it is being used and what the benefits are from this use. SEABORNE began in November 2021, and initially, we were provided with a list of potential datasets relevant to our project in a spreadsheet. To this, we continued to search various data portals online and find additional datasets relevant to our project, particularly focusing on the Great Barrier Reef. We recorded these initially in an Excel spreadsheet. We then transferred this to an MS Access database and developed a more user-friendly entry form. Within the MS Access database, there is one table that stores all the metadata records entered. And another table that stores the static preview images. There are 58 fields (which have been described in a data dictionary) – some of these are mandatory. At the moment there are 3 metadata records entered and we expect this to grow to 50-100 records by the completion of the project. Lineage: Data was produced by examining each of the datasets metadata and documenting various features of each of the individual datasets and how useful they were for examining ecosystem services. Data was initially entered in excel, then migrated to MS Access database, and then imported or read in by SHiny R app.

Comparisons of basic characteristics in patients with and without infection H. pylori.