In today's data-driven world, extracting meaningful insights from vast amounts of information is crucial for informed decision-making. This presentation tackles the challenge of creating presentable data visualizations based on employee type and region of sales.

Leveraging the power of PivotTables in Microsoft Excel, we will delve into a comprehensive approach to transforming raw sales data into compelling visual representations. By mastering PivotTable techniques, we will gain insights into employee sales trends, identify top performers, and uncover regional sales patterns.

Powerpoint presentation on the data portal

Presentation slides from the Interagency Data Team meeting. The Interagency Data Team is a community of data analysts, or agency liaisons, who convene regularly with representation from DC agencies of all persuasions. Participants engage in discussions regarding the team’s core mission and priorities for a better kind of data culture – collection, application, sharing, classification and governance to name a few. The team is coordinated by the Office of the Chief Technology Officer (OCTO), lead by the Chief Data Officer (CDO), and directly supports the District of Columbia's Data Policy.

This metric estimates the proportion of all malignant cancers where patients first presented to the health system as an emergency. This latest publication has been updated to include quarterly data for January to March, April to June and July to September 2022 (quarter 4 of financial year 2021 to 2022 and quarters 1 and 2 of financial year 2022 to 2023) and an update of the one-year rolling proportion.

Presentation skill workshop data.

This DSS presentation describes the Comprehensive Child Welfare Information System (CCWIS) Data Quality Requirements as defined by Federal Regulation 45 CFR 1355.52(d) and provides examples.

Metadata-only record linking to the original dataset. Open original dataset below.

This dataset provides information about the number of properties, residents, and average property values for Presentation Circle cross streets in Staten Island, NY.

A recent proteomics-grade (95%+ sequence reliability) high-throughput de novo sequencing method utilizes the benefits of high resolution, high mass accuracy, and the use of two complementary fragmentation techniques collision-activated dissociation (CAD) and electron capture dissociation (ECD). With this high-fidelity sequencing approach, hundreds of peptides can be sequenced de novo in a single LC−MS/MS experiment. The high productivity of the new analysis technique has revealed a new bottleneck which occurs in data representation. Here we suggest a new method of data analysis and visualization that presents a comprehensive picture of the peptide content including relative abundances and grouping into families. The 2D mass mapping consists of putting the molecular masses onto a two-dimensional bubble plot, with the relative monoisotopic mass defect and isotopic shift being the axes and with the bubble area proportional to the peptide abundance. Peptides belonging to the same family form a compact group on such a plot, so that the family identity can in many cases be determined from the molecular mass alone. The performance of the method is demonstrated on the high-throughput analysis of skin secretion from three frogs, Rana ridibunda, Rana arvalis, and Rana temporaria. Two dimensional mass maps simplify the task of global comparison between the species and make obvious the similarities and differences in the peptide contents that are obscure in traditional data presentation methods. Even biological activity of the peptide can sometimes be inferred from its position on the plot. Two dimensional mass mapping is a general method applicable to any complex mixture, peptide and nonpeptide alike.

The Kids’ Well-being Indicators Clearinghouse (KWIC) contains county-level health, education and well-being data for children and youth and is used as a tool to advance policy development, planning and accountability. KWIC users are able to create: pre-built and custom indicator and county reports; motion charts; custom regions with aggregated data; presentation-ready data snapshots (KWIC Views); MyKWIC accounts to save frequently used queries and custom regions; and color-shaded maps using KWIC data — users have the ability to display community assets and district overlays on the maps as well as compare maps over time. Narratives and data source information are available for every indicator and all data on KWIC are exportable

From July 2016 onwards this data has been published on the 1st Friday of the month. The March 2017 data will be published on Friday 2 May 2017. What does the data cover? General practice prescribing data is a list of all medicines, dressings and appliances that are prescribed and dispensed each month. A record will only be produced when this has occurred and there is no record for a zero total. For each practice in England, the following information is presented at presentation level for each medicine, dressing and appliance, (by presentation name): - the total number of items prescribed and dispensed - the total net ingredient cost - the total actual cost - the total quantity The data covers NHS prescriptions written in England and dispensed in the community in the UK. Prescriptions written in England but dispensed outside England are included. The data includes prescriptions written by GPs and other non-medical prescribers (such as nurses and pharmacists) who are attached to GP practices. GP practices are identified only by their national code, so an additional data file - linked to the first by the practice code - provides further detail in relation to the practice. Presentations are identified only by their BNF code, so an additional data file - linked to the first by the BNF code - provides the chemical name for that presentation. Warning: Large file size (over 1GB). Each monthly data set is large (over 10 million rows), but can be viewed in standard software such as Microsoft WordPad (save by right-clicking on the file name and selecting 'Save Target As', or equivalent on Mac OSX). It is then possible to select the required rows of data and copy and paste the information into another software application, such as a spreadsheet. Alternatively add-ons to existing software, such as the Microsoft PowerPivot add-on for Excel, to handle larger data sets, can be used. The Microsoft PowerPivot add-on for Excel is available using the link in the 'Related Links' section below. Once PowerPivot has been installed, to load the large files, please follow the instructions below. Note that it may take at least 20 to 30 minutes to load one monthly file. 1. Start Excel as normal 2. Click on the PowerPivot tab 3. Click on the PowerPivot Window icon (top left) 4. In the PowerPivot Window, click on the "From Other Sources" icon 5. In the Table Import Wizard e.g. scroll to the bottom and select Text File 6. Browse to the file you want to open and choose the file extension you require e.g. CSV Once the data has been imported you can view it in a spreadsheet.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and for the unorganized area, census areas. The latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four states (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities. The boundaries for counties and equivalent entities are as of January 1, 2017, primarily as reported through the Census Bureau's Boundary and Annexation Survey (BAS).

The U.S. Census Bureau, in collaboration with five federal agencies, launched the Household Pulse Survey to produce data on the social and economic impacts of Covid-19 on American households. The Household Pulse Survey was designed to gauge the impact of the pandemic on employment status, consumer spending, food security, housing, education disruptions, and dimensions of physical and mental wellness.

The survey was designed to meet the goal of accurate and timely weekly estimates. It was conducted by an internet questionnaire, with invitations to participate sent by email and text message. The sample frame is the Census Bureau Master Address File Data. Housing units linked to one or more email addresses or cell phone numbers were randomly selected to participate, and one respondent from each housing unit was selected to respond for him or herself. Estimates are weighted to adjust for nonresponse and to match Census Bureau estimates of the population by age, gender, race and ethnicity, and educational attainment. All estimates shown meet the NCHS Data Presentation Standards for Proportions.

Israel BoP: Current Account: Services: Balance: Travel data was reported at 158.200 USD mn in Mar 2018. This records a decrease from the previous number of 421.500 USD mn for Dec 2017. Israel BoP: Current Account: Services: Balance: Travel data is updated quarterly, averaging 121.500 USD mn from Mar 1980 (Median) to Mar 2018, with 153 observations. The data reached an all-time high of 787.700 USD mn in Dec 1999 and a record low of -1.062 USD bn in Sep 2017. Israel BoP: Current Account: Services: Balance: Travel data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Global Database’s Israel – Table IL.JB003: Balance of Payments: Detailed Presentation.

Kazakhstan BoP: Analytic Presentation (AP): Current Account data was reported at -592.850 USD mn in Mar 2018. This records an increase from the previous number of -745.116 USD mn for Dec 2017. Kazakhstan BoP: Analytic Presentation (AP): Current Account data is updated quarterly, averaging -223.119 USD mn from Mar 2000 (Median) to Mar 2018, with 73 observations. The data reached an all-time high of 6.656 USD bn in Mar 2014 and a record low of -3.081 USD bn in Sep 2007. Kazakhstan BoP: Analytic Presentation (AP): Current Account data remains active status in CEIC and is reported by The National Bank of the Republic of Kazakhstan. The data is categorized under Global Database’s Kazakhstan – Table KZ.JB003: BPM6: Balance of Payments: Analytic Presentation.

The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The primary legal divisions of most States are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, and municipalities, and for the unorganized area, census areas. The latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four States (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary divisions of their States. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities. The 2010 Census boundaries for counties and equivalent entities are as of January 1, 2010, primarily as reported through the Census Bureau's Boundary and Annexation Survey (BAS).

UY: BoP: Current Account: Services: Other Business: Research & Development: Credit data was reported at 0.000 USD mn in 2017. This stayed constant from the previous number of 0.000 USD mn for 2016. UY: BoP: Current Account: Services: Other Business: Research & Development: Credit data is updated yearly, averaging 0.000 USD mn from Dec 2000 (Median) to 2017, with 17 observations. UY: BoP: Current Account: Services: Other Business: Research & Development: Credit data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s Uruguay – Table UY.IMF.BOP: BPM6: Balance of Payments: Detailed Presentation: Annual.

HT: BoP: Current Account: Primary Income: Investment Income: Credit data was reported at 22.434 USD mn in Jun 2018. This records an increase from the previous number of 17.356 USD mn for Mar 2018. HT: BoP: Current Account: Primary Income: Investment Income: Credit data is updated quarterly, averaging 9.748 USD mn from Dec 2004 (Median) to Jun 2018, with 55 observations. The data reached an all-time high of 22.434 USD mn in Jun 2018 and a record low of 0.000 USD mn in Sep 2005. HT: BoP: Current Account: Primary Income: Investment Income: Credit data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s Haiti – Table HT.IMF.BOP: BPM6: Balance of Payments: Detailed Presentation.

TL: BoP: Financial Account: Other Investment: Assets: Other Equity data was reported at 0.000 USD mn in Mar 2018. This stayed constant from the previous number of 0.000 USD mn for Dec 2017. TL: BoP: Financial Account: Other Investment: Assets: Other Equity data is updated quarterly, averaging 0.000 USD mn from Mar 2017 (Median) to Mar 2018, with 5 observations. TL: BoP: Financial Account: Other Investment: Assets: Other Equity data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s Timor-Leste – Table TL.IMF.BOP: BPM6: Balance of Payments: Analytical Presentation.

MK: BoP: Financial Account: Direct Investment: Assets: Equity: Reinvested Earnings: ow Money Market Fund Shares/Units data was reported at 0.000 USD mn in Mar 2018. This stayed constant from the previous number of 0.000 USD mn for Dec 2017. MK: BoP: Financial Account: Direct Investment: Assets: Equity: Reinvested Earnings: ow Money Market Fund Shares/Units data is updated quarterly, averaging 0.000 USD mn from Mar 2017 (Median) to Mar 2018, with 5 observations. MK: BoP: Financial Account: Direct Investment: Assets: Equity: Reinvested Earnings: ow Money Market Fund Shares/Units data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s Macedonia – Table MK.IMF.BOP: BPM6: Balance of Payments: Detailed Presentation.

CR: BoP: Financial Account: Other Investment: Assets: Debt Instruments: Other Sectors: Financial Corporations data was reported at 0.269 USD mn in Sep 2024. This records an increase from the previous number of -0.453 USD mn for Jun 2024. CR: BoP: Financial Account: Other Investment: Assets: Debt Instruments: Other Sectors: Financial Corporations data is updated quarterly, averaging 0.272 USD mn from Mar 2014 (Median) to Sep 2024, with 43 observations. The data reached an all-time high of 1.768 USD mn in Mar 2014 and a record low of -4.996 USD mn in Jun 2015. CR: BoP: Financial Account: Other Investment: Assets: Debt Instruments: Other Sectors: Financial Corporations data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s Costa Rica – Table CR.IMF.BOP: BPM6: Balance of Payments: Analytical Presentation.