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 dataset is about book series. It has 1 row and is filtered where the books is Excel at problem solving. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.

This is a computer exercise that takes you through retrieving multiple time series in CANSIM.

This database contains one hour oxygen saturation (SpO2) measurements of 36 patients, used for the analysis of oxygen saturation variability. The Ascii (.txt) files contain the raw data of SpO2 recorded with a sampling rate of 1/s. The attached excel file "Participant characteristics" contains anonymised participant information. Detailed analysis of this data is published on Frontiers Physiology.

Days-of-Sales-Outstanding Time Series for Excel Force MSC Bhd. Excel Force MSC Berhad, together with its subsidiaries, develops, provides, and maintains software application solutions for the financial services industry in Malaysia. The company operates through Application Solutions, Maintenance Services, Application Services Provider, and Other segments. Its product portfolio includes CyberStock BTX, a bridging trader and exchange system platform that provides trading tools classes; and CyberStock ECOS, a stock broking solution which offers real time market information, place trades, and manage orders solution. In addition, the company provides CyberStock Mobile Trader, a mobile trading system that connects users smartphones to exchanges to manage trading activities; and CyberStock EDS, an exempt dealer system that provides advanced trading infrastructure and facilities for commercial banks. Further, it offers CyberStock SMF, a share margin financing system that enables financial institutions, brokerage firms, and banks to operate and manage margin financing services; and CyberStock CNS, a custodian and nominee system, which provides value-added services, such as trade settlement, cash balances investment, income collection, corporate actions processing, recordkeeping and reporting to custodian banks for domestic services. Additionally, the company provides CyberStock BOS, a back office system to manage enormous file and data; and offers network and security services. Excel Force MSC Berhad was founded in 1994 and is based in Petaling Jaya, Malaysia.

This repository contains a collection of data about 454 value chains from 23 rural European areas of 16 countries. This data is obtained through a semi-automatic workflow that transforms raw textual data from an unstructured MS Excel sheet into semantic knowledge graphs.In particular, the repository contains:MS Excel sheet containing different value chains details provided by MOuntain Valorisation through INterconnectedness and Green growth (MOVING) European project;454 CSV files containing events, titles, entities and coordinates of narratives of each value chain, obtained by pre-processing the MS Excel sheet454 Web Ontology Language (OWL) files. This collection of files is the result of the semi-automatic workflow, and is organized as a semantic knowledge graph of narratives, where each narrative is a sub-graph explaining one among the 454 value chains and its territory aspects. The knowledge graph is based on the Narrative Ontology, an ontology developed by Institute of Information Science and Technologies (ISTI-CNR) as an extension of CIDOC CRM, FRBRoo, and OWL Time.Two CSV files that compile all the possible available information extracted from 454 Web Ontology Language (OWL) files.GeoPackage files with the geographic coordinates related to the narratives.The HTML files that show all the different SPARQL and GeoSPARQL queries.The HTML files that show the story maps about the 454 value chains.An image showing how the various components of the dataset interact with each other.

The Nation is the series of basic data from the 1991 Census, providing national coverage. This series covers characteristics of the population, including demographic, social, cultural, labour force and income variables as well as details on dwellings, households and families. Generally the data are represented for Canada, provinces, territories and census metropolitan areas. Some tables include comparisons with data from earlier censuses. The aggregate data tables are presented in Beyond 20/20 Format (.ivt).

This dataset is composed of 176 Excel files, downloaded via the Google Trends tool between June 11 and 15, 2025. The files include time series data on the relative frequency (in percentages) of Google searches conducted in European Union member states on four topics: corruption, immigration, security, and transexuality. They also include data related to right-wing, center-right, and center-left (used as a control group) political parties in each country. Each file contains one column with the date (on a weekly basis) and another with the series value (a percentage normalized by Google Trends). The time span covered in each file is five years.

Methylated long-chain aliphatic compounds such as terminal methyl ethers are a common compound type found on the epicuticular layer of arthropods, e.g., spiders. Because complex mixtures are encountered in small amounts when analyzing these mixtures, GC/MS is the method of choice for characterizing the individual constituents. However, the methyl branch location cannot be deduced from the original spectra due to the easy loss of methanol, resulting in nonspecific spectra, and a complex derivatization scheme has been employed to address this issue. We noted that although mass spectra obtained by EI-quadrupol and EI-Orbitrap ionization are superficially quite similar, a +2.0 V C-trap offset of the latter leads to reduced fragmentation. The high-resolution Orbitrap spectra contain enough information to allow for methyl group localization in the chain. However, the spectra of the methyl ethers contain many ions, making individual analysis quite time-consuming. Therefore, scripts using Excel and R were developed with the help of ChatGPT 4.0, resulting in ion series spectra (ISS) that contained only ions of a specific ion series. The analysis of 11 synthetic methyl ethers showed that especially the ion series CnH2n+1O (ISS45) and CnH2n–2 (ISS40) are of high diagnostic value, together with some methoxy group-induced fragmentation. The approach was successfully tested with lipids from the spider Tetragnatha versicolor, which had been previously analyzed by derivatization, and with web extracts of Erigone atra, revealing 1-methoxy-2,16-dimethylhenicosane as a male-specific componentthe first spider methyl ether in a volatility range that would allow detection via the gas phase. This approach can also be applied to structurally related primary alcohols, although the diagnostic ions are of lower intensity.

The series consists of a list of files registered on the computer-based Records and Correspondence Management System (RCMS), under Registry 11 Correctional Services. It was created by exporting file data from the RCMS system into a Microsoft Excel spreadsheet. It is an artificial series, created by the Department of Justice at the request of Public Record Office Victoria, to provide access to VPRS 12700 General Correspondence Files, Registry 11 Correctional Services.

The list captured the file number, key-term classification, file title, and certain additional information for each file.

Organisation of the Data

The data is organised into 13 columns, or fields, presumably corresponding to discrete fields within the RCMS database.

The columns, from left to right, are as follows:

1. FILE.YEAR - The year the file was raised.

2. REGISTRY - The number of the registry in which the file has been registered on the RCMS system. The files referred to by this series were registered under Registry 11 Correctional Services.

3. FILE SEQUENCE - The sequential number allocated to each file as it is raised. Numbers start again from one each year.

4. FILE PART - The part number of the file.

The FILE.YEAR, REGISTRY, FILE SEQUENCE, and FILE PART fields, taken together, provide the file number.

5. KEY TERM - In theory, this is term used to describe the principle subject area of the file.

6. DESCRIPTOR.1, DESCRIPTOR.2 and DESCRIPTOR.3 (Columns 6 to 8) - In theory, these are narrower terms used to break the general subject area into smaller, more specific areas.

7. KWOC.1, KWOC.2, KWOC.3, and KWOC.4 (Key Word Out of Context) (Columns 9 to 12) - Provide for free text description of the file.

The KEY-TERM, DESCRIPTOR, and KWOC fields, taken together, provide the file title.

In practice, many different terms have been used in the key-term and descriptor fields. There appears to have been little control over the creation of new terms and the way in which the terms are used.

8. ADD.FILE.INFO (Additional File Information) - This field contains useful information about previous and subsequent files, related files, file closure, and so forth.

A range of quarterly Excel spreadsheets and SuperTABLE datacubes. The spreadsheets contain broad level data covering all the major items of the Labour Force Survey in time series format, including …Show full descriptionA range of quarterly Excel spreadsheets and SuperTABLE datacubes. The spreadsheets contain broad level data covering all the major items of the Labour Force Survey in time series format, including seasonally adjusted and trend estimates. The datacubes contain more detailed and cross classified original data than the spreadsheets.

This file includes 3 excels on Fama-MacBeth first-stage time-series regression data. The first excel includes portfolios “s1b1”-“s1b5” and “s2b1”-“s2b5”; the second excel includes portfolios “s3b1”-“s3b5” and “s4b1”-“s4b5”, and the third one includes the portfolios “s5b1”-“s5b5”

Distribution of doses of a volatile organic compound from inhalation of one consumer product, other near -field sources, far-field sources, and aggregate (total) exposure. In this instance, far-field scenarios account for several orders of magnitude of less of the predicted dose compared to near-field scenarios. This dataset is associated with the following publication: Vallero, D. Air Pollution Monitoring Changes to Accompany the Transition from a Control to a Systems Focus. Sustainability. MDPI AG, Basel, SWITZERLAND, 8(12): 1216, (2016).

The Nuclear Medicine National HQ System database is a series of MS Excel spreadsheets and Access Database Tables by fiscal year. They consist of information from all Veterans Affairs Medical Centers (VAMCs) performing or contracting nuclear medicine services in Veterans Affairs medical facilities. The medical centers are required to complete questionnaires annually (RCS 10-0010-Nuclear Medicine Service Annual Report). The information is then manually entered into the Access Tables, which includes: * Distribution and cost of in-house VA - Contract Physician Services, whether contracted services are made via sharing agreement (with another VA medical facility or other government medical providers) or with private providers. * Workload data for the performance and/or purchase of PET/CT studies. * Organizational structure of services. * Updated changes in key imaging service personnel (chiefs, chief technicians, radiation safety officers). * Workload data on the number and type of studies (scans) performed, including Medicare Relative Value Units (RVUs), also referred to as Weighted Work Units (WWUs). WWUs are a workload measure calculated as the product of a study's Current Procedural Terminology (CPT) code, which consists of total work costs (the cost of physician medical expertise and time), and total practice costs (the costs of running a practice, such as equipment, supplies, salaries, utilities etc). Medicare combines WWUs together with one other parameter to derive RVUs, a workload measure widely used in the health care industry. WWUs allow Nuclear Medicine to account for the complexity of each study in assessing workload, that some studies are more time consuming and require higher levels of expertise. This gives a more accurate picture of workload; productivity etc than using just 'total studies' would yield. * A detailed Full-Time Equivalent Employee (FTEE) grid, and staffing distributions of FTEEs across nuclear medicine services. * Information on Radiation Safety Committees and Radiation Safety Officers (RSOs). Beginning in 2011 this will include data collection on part-time and non VA (contract) RSOs; other affiliations they may have and if so to whom they report (supervision) at their VA medical center.Collection of data on nuclear medicine services' progress in meeting the special needs of our female veterans. Revolving documentation of all major VA-owned gamma cameras (by type) and computer systems, their specifications and ages. * Revolving data collection for PET/CT cameras owned or leased by VA; and the numbers and types of PET/CT studies performed on VA patients whether produced on-site, via mobile PET/CT contract or from non-VA providers in the community. Types of educational training/certification programs available at VA sites * Ongoing funded research projects by Nuclear Medicine (NM) staff, identified by source of funding and research purpose. * Data on physician-specific quality indicators at each nuclear medicine service. Academic achievements by NM staff, including published books/chapters, journals and abstracts. * Information from polling field sites re: relevant issues and programs Headquarters needs to address. * Results of a Congressionally mandated contracted quality assessment exercise, also known as a Proficiency study. Study results are analyzed for comparison within VA facilities (for example by mission or size), and against participating private sector health care groups. * Information collected on current issues in nuclear medicine as they arise. Radiation Safety Committee structures and membership, Radiation Safety Officer information and information on how nuclear medicine services provided for female Veterans are examples of current issues.The database is now stored completely within MS Access Database Tables with output still presented in the form of Excel graphs and tables.

Property-Plant-and-Equipment-Net Time Series for Excel Force MSC Bhd. Excel Force MSC Berhad, together with its subsidiaries, develops, provides, and maintains software application solutions for the financial services industry in Malaysia. The company operates through Application Solutions, Maintenance Services, Application Services Provider, and Other segments. Its product portfolio includes CyberStock BTX, a bridging trader and exchange system platform that provides trading tools classes; and CyberStock ECOS, a stock broking solution which offers real time market information, place trades, and manage orders solution. In addition, the company provides CyberStock Mobile Trader, a mobile trading system that connects users smartphones to exchanges to manage trading activities; and CyberStock EDS, an exempt dealer system that provides advanced trading infrastructure and facilities for commercial banks. Further, it offers CyberStock SMF, a share margin financing system that enables financial institutions, brokerage firms, and banks to operate and manage margin financing services; and CyberStock CNS, a custodian and nominee system, which provides value-added services, such as trade settlement, cash balances investment, income collection, corporate actions processing, recordkeeping and reporting to custodian banks for domestic services. Additionally, the company provides CyberStock BOS, a back office system to manage enormous file and data; and offers network and security services. Excel Force MSC Berhad was founded in 1994 and is based in Petaling Jaya, Malaysia.

Operating-Profit-Margin Time Series for Excel Force MSC Bhd. Excel Force MSC Berhad, together with its subsidiaries, develops, provides, and maintains software application solutions for the financial services industry in Malaysia. The company operates through Application Solutions, Maintenance Services, Application Services Provider, and Other segments. Its product portfolio includes CyberStock BTX, a bridging trader and exchange system platform that provides trading tools classes; and CyberStock ECOS, a stock broking solution which offers real time market information, place trades, and manage orders solution. In addition, the company provides CyberStock Mobile Trader, a mobile trading system that connects users smartphones to exchanges to manage trading activities; and CyberStock EDS, an exempt dealer system that provides advanced trading infrastructure and facilities for commercial banks. Further, it offers CyberStock SMF, a share margin financing system that enables financial institutions, brokerage firms, and banks to operate and manage margin financing services; and CyberStock CNS, a custodian and nominee system, which provides value-added services, such as trade settlement, cash balances investment, income collection, corporate actions processing, recordkeeping and reporting to custodian banks for domestic services. Additionally, the company provides CyberStock BOS, a back office system to manage enormous file and data; and offers network and security services. Excel Force MSC Berhad was founded in 1994 and is based in Petaling Jaya, Malaysia.

The dataset included with this article contains three files describing and defining the sample and variables for VAT impact, and Excel file 1 consists of all raw and filtered data for the variables for the panel data sample. Excel file 2 depicts time-series and cross-sectional data for nonfinancial firms listed on the Saudi market for the second and third quarters of 2019 and the third and fourth quarters of 2020. Excel file 3 presents the raw material of variables used in measuring the company's profitability of the panel data sample

This page contains datasets in Excel and CSV formats. This data will be particularly useful for users who would like the same data for a series of different years rather than just for one year. Archive Previous version of Estimated population by sex, single year of age, 2011 Data Zone area, and council area

Subjective measurement data including participants' self-reported muscle fatigue rank, physiotherapist's palpation-based assessment of muscle stiffness during the 210-second experiment with 30-second intervals, and final assessment of muscle fatigue were summarised in Excel spreadsheet format (e.g., SelfReported_Subject01.xlsx and PhysioPalpation_Subject01.xlsx).readme.pdf with instructions about loading the dataset, running the code, and code execution.Subject: Each data file is named according to the participant number, which is an integer ranging from 1 to 30.Muscle stiffness measurements for 210 seconds with 30-second intervals: The subjective data records for each participant include the physiotherapist's palpation-based measurements taken at 0s and 30-second intervals for a total of 8 times across nine muscle locations.Physiotherapist's palpation-based muscle tightness Rank 1, Rank 2, Rank 3: Followed by the muscle stiffness measurement with 30-second intervals, the data records for physiotherapist-assessed muscle tightness rank 1, 2, and 3 contain the evaluations conducted by the physiotherapist to assess muscle tightness. Each record includes the participant number, the rank of muscle fatigue assigned by the physiotherapist (1, 2, or 3), and the associated muscle location. These records reflect the expert judgment of the physiotherapist regarding the severity and localization of muscle fatigue, providing valuable objective assessments of muscle condition during the experimental sessions.Self-reported perceived muscle fatigue Rank 1, Rank 2, Rank 3: The data records for self-reported muscle fatigue rank 1, 2, and 3 include information on the participants' subjective assessment of their muscle fatigue levels. Each record specifies the participant number, the rank of muscle fatigue (1, 2, or 3), and the corresponding muscle site. These records provide insights into the participants' individual perceptions of muscle fatigue and contribute to understanding the subjective experience of fatigue during the experimental sessions.Raw data contains sEMG data for all subjects with nine muscles. The sEMG time and signal data were collected via a Bluetooth module and an in-house data acquisition (DAQ) system. The recorded data was stored in Excel Spreadsheets in .xlsx format, with each participant's data saved in a separate file (e.g. Subject01.xlsx).Time: The sEMG raw time data consists of the time series measurements recorded from the sEMG sensors. These sensors captured the electrical activity generated by the muscles during the experimental sessions. Each data entry in the time series corresponds to a specific time point. The sEMG raw time data is stored in an Excel spreadsheet (.xlsx) using Time [s] format.Raw sEMG signal: The sEMG raw signal data contains the amplitude of the electrical signals recorded by the sEMG sensors. These signals represent the muscular electrical activity and provide insights into the muscle's activation levels during the experimental sessions. Each entry in the signal data corresponds to a specific time point, reflecting the magnitude of the electrical activity at that particular moment. The sEMG raw signal data is stored in an Excel spreadsheet (.xlsx) using Avanti sensor 5: EMG.A 5 [V] format.For any further information, please contact Jihoon Lim (jihoon.lim@student.unimelb.edu.au).