Video and instructions on how to use pivot tables in Excel for data analysis.

On an annual basis (individual hospital fiscal year), individual hospitals and hospital systems report detailed facility-level data on services capacity, inpatient/outpatient utilization, patients, revenues and expenses by type and payer, balance sheet and income statement.

Due to the large size of the complete dataset, a selected set of data representing a wide range of commonly used data items, has been created that can be easily managed and downloaded. The selected data file includes general hospital information, utilization data by payer, revenue data by payer, expense data by natural expense category, financial ratios, and labor information.

There are two groups of data contained in this dataset: 1) Selected Data - Calendar Year: To make it easier to compare hospitals by year, hospital reports with report periods ending within a given calendar year are grouped together. The Pivot Tables for a specific calendar year are also found here. 2) Selected Data - Fiscal Year: Hospital reports with report periods ending within a given fiscal year (July-June) are grouped together.

The complete data set of annual utilization data reported by hospitals contains basic licensing information including bed classifications; patient demographics including occupancy rates, the number of discharges and patient days by bed classification, and the number of live births; as well as information on the type of services provided including the number of surgical operating rooms, number of surgeries performed (both inpatient and outpatient), the number of cardiovascular procedures performed, and licensed emergency medical services provided.

This dataset contains annual Excel pivot tables that display summaries of the inpatients treated in each hospital. The summary data include discharges, discharge days, average length of stay, age groups, race groups, sex, expected payer, type of care, do not resuscitate orders, admission source, admission type, discharge disposition, principal diagnosis groups, principal procedure groups, and principal external cause of injury/morbidity groups. The data can also be summarized statewide or for a specific hospital county, bed size grouping, and/or type of control.

This is a dataset to be used to explain pivot tables, as part of a School of Data course.

For this project, I cleaned data on a data sheet that had some errors within the data. After cleaning this data, I created 2 pivot tables to summarize the number of products for the top suppliers.

In this paper, a method of intelligent identification and data smooth processing of flying flexible joint pivoting center based on machine vision is proposed. The intelligent identification is realized by the following process: first of all the geometric center of the two markers attached to the flying body is located on a straight line at a certain angle to the center-line of the measured pivoting body, secondly then continuous image sampling is carried out by industrial camera when the marker swings with the pivoting body, and image data is transmitted through a data interface to an industrial computer, Finally the image processing module de-noises the image, removes the background and locates the markers to obtain the plane coordinates of the markers in the coordinate system of the test system. The data smooth of obtained coordinates is carried outby Matlab software including the following steps: the coordinates of the mark points detected based on machine vision are optimized to obtain the smooth curve by fitting of the parabola and arc. Then the coordinates of the points on the curve are used to optimize the coordinates of the marked points from measurement. The optimized coordinate values are substituted into the calculation module of pivoting center, so the average pivoting center of the sampling interval of two images is calculated according to the mathematical model to approach the instantaneous pivoting center during the motion of the pivoting body. The result processing module displays and records the curve of pivoting center shift directly and effectively. Finally, it is validated by simulation and experiments that the precision of pivoting center measured by such measuring system is ~0.5%.

969 Global import shipment records of Pivot with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

This dataset contains annual Excel pivot tables that identify where a facility’s patients come from (Patient Origin) and where patients from a specific area go to (Market Share) for hospital inpatient, emergency department, and ambulatory surgery treatment. The Patient Origin Report shows the ZIP codes of origin (based on a selected facility or facility county) and the Market Share Report lists the destination facilities (based on a selected patient ZIP code or patient county). Note: Physician-owned ambulatory surgery clinics do not report their data to HCAI and, therefore, are not included here.

With a step-by-step approach, learn to prepare Excel files, data worksheets, and individual data columns for data analysis; practice conditional formatting and creating pivot tables/charts; go over basic principles of Research Data Management as they might apply to an Excel project. Avec une approche étape par étape, apprenez à préparer pour l’analyse des données des fichiers Excel, des feuilles de calcul de données et des colonnes de données individuelles; pratiquez la mise en forme conditionnelle et la création de tableaux croisés dynamiques ou de graphiques; passez en revue les principes de base de la gestion des données de recherche tels qu’ils pourraient s’appliquer à un projet Excel.

This step-by-step exercise demonstrates how to use Excel pivot tables to create cross-tabulations from public use microdata files.

This dataset tracks the updates made on the dataset "Hospital Annual Financial Data - Selected Data & Pivot Tables" as a repository for previous versions of the data and metadata.

Pivot table based on Supplementary Data S6 summarizing counts of significantly (p_adj < 0.05) associated SNPs per gene.

Historical Dataset of Pivot Charter School is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (2013-2023),Total Classroom Teachers Trends Over Years (2013-2023),Distribution of Students By Grade Trends,Student-Teacher Ratio Comparison Over Years (2013-2023),Asian Student Percentage Comparison Over Years (2012-2023),Hispanic Student Percentage Comparison Over Years (2013-2023),Black Student Percentage Comparison Over Years (2013-2023),White Student Percentage Comparison Over Years (2013-2023),Two or More Races Student Percentage Comparison Over Years (2013-2023),Diversity Score Comparison Over Years (2013-2023),Free Lunch Eligibility Comparison Over Years (2013-2023),Reduced-Price Lunch Eligibility Comparison Over Years (2013-2023),Reading and Language Arts Proficiency Comparison Over Years (2012-2022),Math Proficiency Comparison Over Years (2012-2023),Science Proficiency Comparison Over Years (2021-2022),Overall School Rank Trends Over Years (2012-2022),Graduation Rate Comparison Over Years (2013-2023)

On an annual basis (individual hospital fiscal year), individual hospitals and hospital systems report detailed facility-level data on services capacity, inpatient/outpatient utilization, patients, revenues and expenses by type and payer, balance sheet and income statement. Due to the large size of the complete dataset, a selected set of data representing a wide range of commonly used data items, has been created that can be easily managed and downloaded. The selected data file includes general hospital information, utilization data by payer, revenue data by payer, expense data by natural expense category, financial ratios, and labor information. There are two groups of data contained in this dataset: 1) Selected Data - Calendar Year: To make it easier to compare hospitals by year, hospital reports with report periods ending within a given calendar year are grouped together. The Pivot Tables for a specific calendar year are also found here. 2) Selected Data - Fiscal Year: Hospital reports with report periods ending within a given fiscal year (July-June) are grouped together.

127 Global export shipment records of Pivot Pins with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

Using the combined data from Comext and the UN Comtrade databases, a comprehensive dataset was created for EU trade data of the selected bio-based value chains, covering 2015, 2018 and 2021. This dataset is presented in a pivot table format, offering enhanced filtering options for products, import and export data, and intra- and extra-EU trade.

This dataset contains annual Excel pivot tables that display summaries of the patients treated in each Emergency Department (ED). The Emergency Department data is sourced from two databases, the ED Treat-and-Release Database and the Inpatient Database (i.e. patients treated in the ED and then formally admitted to the hospital). The summary data include number of visits, expected payer, discharge disposition, age groups, sex, preferred language spoken, race groups, principal diagnosis groups, and principal external cause of injury/morbidity groups. The data can also be summarized statewide or for a specific hospital county, ED service level, teaching/rural status, and/or type of control.

A database of funding opportunities for research administrators, research development professionals, and institutions. Researcher profiles are matched to current funding opportunities in the COS database using a proprietary algorithm. Users may also find funding opportunities by searching the database.

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.