The USDMXN increased 0.0914 or 0.45% to 20.2579 on Friday March 21 from 20.1665 in the previous trading session. Mexican Peso - values, historical data, forecasts and news - updated on March of 2025.

Explore the historical Whois records related to data.is.it (Domain). Get insights into ownership history and changes over time.

Abstract copyright UK Data Service and data collection copyright owner.The Great Britain Historical Database has been assembled as part of the ongoing Great Britain Historical GIS Project. The project aims to trace the emergence of the north-south divide in Britain and to provide a synoptic view of the human geography of Britain at sub-county scales. Further information about the project is available on A Vision of Britain webpages, where users can browse the database's documentation system online. This study assembles historical data from the National Insurance system, plus some data from trade union welfare systems gathered and published by the Board of Trade Labour Department. The data were computerised by the Great Britain Historical GIS Project. They form part of the Great Britain Historical Database, which contains a wide range of geographically-located statistics, selected to trace the emergence of the north-south divide in Britain and to provide a synoptic view of the human geography of Britain, generally at sub-county scales. Most of the data here was originally published by the Ministry of Labour, either in the Labour Gazette, later the Employment Gazette, or in the specialised Local Unemployment Index (LUI), published between 1927 and 1939. The largest dataset here is a complete transcription of the LUI data for each January, April, July and October from January 1927 to July 1939 inclusive, the most detailed information that exists on the geography of the inter-war depression, other than the 1931 census. Unlike census data, these data concern a wide range of regions, "divisions", "districts", towns and sometimes areas within towns, seldom defined (the LUI data do list counties). The study therefore also includes two specially constructed gazetteers which attempt to provide towns and areas within towns with point coordinates. Another limitation is that these data generally provide counts of the unemployed, but not counts of the insured, or numbers in work, so calculation of rates often requires data from other sources such as the census. The study also includes two transcriptions from unpublished tabulations in the National Archives, relating to unemployment in 1928 and 1933. Please note: this study does not include information on named individuals and would therefore not be useful for personal family history research.For the second edition (February 2024), the data was updated; data running up to 1974 has been added and the former study 3711 has been incorporated.

Sweetener Market Data (SMD) report - beet and cane processors and cane refiners in the U.S. are required by the FAIR Act of 1996, as amended, to report data on physical quantities delivered by use for "Multiple and All Other Food Uses" on a monthly basis. Quantities are reported by region. Regions include: "New England", "Mid Atlantic", "North Central", "South", "West" and "Puerto Rico".

The Check-In Dataset is the second public-use dataset in the Dunham's Data series, a unique data collection created by Kate Elswit (Royal Central School of Speech and Drama, University of London) and Harmony Bench (The Ohio State University) to explore questions and problems that make the analysis and visualization of data meaningful for dance history through the case study of choreographer Katherine Dunham. The Check-In Dataset accounts for the comings and goings of Dunham's nearly 200 dancers, drummers, and singers and discerns who among them were working in the studio and theatre together over the fourteen years from 1947 to 1960. As with the Everyday Itinerary Dataset, the first public-use dataset from Dunham's Data, data on check-ins come from scattered sources. Due to information available, it has a greater level of ambiguity as many dates are approximated in order to achieve accurate chronological sequence. By showing who shared time and space together, the Check-In Dataset can be used to trace potential lines of transmission of embodied knowledge within and beyond the Dunham Company. Dunham's Data: Digital Methods for Dance Historical Inquiry is funded by the United Kingdom Arts and Humanities Research Council (AHRC AH/R012989/1, 2018-2022) and is part of a larger suite of ongoing digital collaborations by Bench and Elswit, Movement on the Move. The Dunham's Data team also includes digital humanities postdoctoral research assistant Antonio Jiménez-Mavillard and dance history postdoctoral research assistants Takiyah Nur Amin and Tia-Monique Uzor. For more information about Dunham's Data, please see the Dunham's Data website. Also, visit the Dunham's Data research blog to view the interactive visualizations based on the Dunham's Data.

On October 20, 2022, CDC began retrieving aggregate case and death data from jurisdictional and state partners weekly instead of daily. This dataset contains archived historical community transmission and related data elements by county. Although these data will continue to be publicly available, this dataset has not been updated since October 20, 2022. An archived dataset containing weekly historical community transmission data by county can also be found here: Weekly COVID-19 County Level of Community Transmission Historical Changes | Data | Centers for Disease Control and Prevention (cdc.gov).

Related data CDC has been providing the public with two versions of COVID-19 county-level community transmission level data: this historical dataset with the daily county-level transmission data from January 22, 2020, and a dataset with the daily values as originally posted on the COVID Data Tracker. Similar to this dataset, the original dataset with daily data as posted is archived on 10/20/2022. It will continue to be publicly available but will no longer be updated. A new dataset containing community transmission data by county as originally posted is now published weekly and can be found at: Weekly COVID-19 County Level of Community Transmission as Originally Posted | Data | Centers for Disease Control and Prevention (cdc.gov).

This public use dataset has 7 data elements reflecting historical data for community transmission levels for all available counties and jurisdictions. It contains historical data for the county level of community transmission and includes updated data submitted by states and jurisdictions. Each day, the dataset was updated to include the most recent days’ data and incorporate any historical changes made by jurisdictions. This dataset includes data since January 22, 2020. Transmission level is set to low, moderate, substantial, or high using the calculation rules below.

Methods for calculating county level of community transmission indicator The County Level of Community Transmission indicator uses two metrics: (1) total new COVID-19 cases per 100,000 persons in the last 7 days and (2) percentage of positive SARS-CoV-2 diagnostic nucleic acid amplification tests (NAAT) in the last 7 days. For each of these metrics, CDC classifies transmission values as low, moderate, substantial, or high (below and here). If the values for each of these two metrics differ (e.g., one indicates moderate and the other low), then the higher of the two should be used for decision-making.

CDC core metrics of and thresholds for community transmission levels of SARS-CoV-2

Total New Case Rate Metric: "New cases per 100,000 persons in the past 7 days" is calculated by adding the number of new cases in the county (or other administrative level) in the last 7 days divided by the population in the county (or other administrative level) and multiplying by 100,000. "New cases per 100,000 persons in the past 7 days" is considered to have transmission level of Low (0-9.99); Moderate (10.00-49.99); Substantial (50.00-99.99); and High (greater than or equal to 100.00).

Test Percent Positivity Metric: "Percentage of positive NAAT in the past 7 days" is calculated by dividing the number of positive tests in the county (or other administrative level) during the last 7 days by the total number of tests resulted over the last 7 days. "Percentage of positive NAAT in the past 7 days" is considered to have transmission level of Low (less than 5.00); Moderate (5.00-7.99); Substa

The Farm Production and Conservation Business Center (FPAC-BC) Geospatial Enterprise Operations (GEO) Branch Historical Availability ArcGIS Online web map provides an easy to use reference of what historical imagery is available by county. GEO has one of the largest collections of historical aerial photography in the nation. Imagery ranges in age from 1955 to the present. Click on the map to view information about years of imagery available for each county. Information includes year, imagery program (i.e. NAIP, FSA, NHAP, etc), how much coverage is available (i.e. 100%, or partial (P), and imagery type (i.e. M4B (Multispectral, 4 bands which include RGB & Near Infrared, NC (Natural Color), or Black and White (BW)). Listings that are not denoted as film were digital collections. Click on the pop-up for a county to view the catalog listing of imagery for that county as a .jpeg attachment.To view some of the historic imagery from the National Aerial Photography Program (NAPP) and National High Altitude Program (NHAP) visit their respective imagery galleries: NAPP, NHAP.The National Agriculture Imagery Program (NAIP) Change 2002-2023 Story Map provides highlights and changes to the NAIP program throughout its history.For ordering information please contact the GEO Customer Service Section at geo.sales@usda.gov.

Abstract The dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement. The dataset consists of shapefiles of historical mine foot prints for the South Sydney Basin derived from Landsat imagery. Mine boundaries were digitised through interpretation of the …Show full descriptionAbstract The dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement. The dataset consists of shapefiles of historical mine foot prints for the South Sydney Basin derived from Landsat imagery. Mine boundaries were digitised through interpretation of the disturbed land in the vicinity of known coal mines. A historical sequence using multiple images for selected years was built to represent the changing mine foot prints. Dataset History Mine boundaries were digitised through interpretation of the disturbed land in the vicinity of known coal mines. A historical sequence using multiple images for selected years was built to represent the changing mine foot prints. Dataset Citation Bioregional Assessment Programme (2016) SSB Historical Landsat Derived Mine Foot Prints v01. Bioregional Assessment Derived Dataset. Viewed 18 June 2018, http://data.bioregionalassessments.gov.au/dataset/302e2a0d-244a-4369-9ed6-c529f14b4db8. Dataset Ancestors Derived From SSB Landsat processed data v01 Derived From SYD Landsat raw data v01

The earliest point where scientists can make reasonable estimates for the population of global regions is around 10,000 years before the Common Era (or 12,000 years ago). Estimates suggest that Asia has consistently been the most populated continent, and the least populated continent has generally been Oceania (although it was more heavily populated than areas such as North America in very early years). Population growth was very slow, but an increase can be observed between most of the given time periods. There were, however, dips in population due to pandemics, the most notable of these being the impact of plague in Eurasia in the 14th century, and the impact of European contact with the indigenous populations of the Americas after 1492, where it took almost four centuries for the population of Latin America to return to its pre-1500 level. The world's population first reached one billion people in 1803, which also coincided with a spike in population growth, due to the onset of the demographic transition. This wave of growth first spread across the most industrially developed countries in the 19th century, and the correlation between demographic development and industrial or economic maturity continued until today, with Africa being the final major region to begin its transition in the late-1900s.

Catalog of Historic Villages divided between: 'Orange Flag' and 'Most Beautiful Villages in Italy' villages (selected and certified respectively by TCI and the Club Most Beautiful Villages in Italy), 'Historical Seaside Villages' (identified within the project interregional project promoted by MiBACT ex L. 296/2006) and 'Authentic villages' (members of the Association of authentic villages of Italy).-Coverage: Entire Regional Territory - Origin: Georeference on numerical and raster CTR; year: 2023

Imports - Parts, Engines, Bodies & Chassis (Census Basis) in the United States increased to 16976.46 USD Million in February from 16234.39 USD Million in January of 2024. This dataset includes a chart with historical data for the United States Imports of Parts, Engines, Bodies & Chassis.

In 1870, the GDP of the U.S., Canada, Australia, and New Zealand was eight times larger than in 1820, and by 1913 it was almost 42 times larger. Although Europe had the largest share of global GDP in 1913, it had only grown by 5.4 times since 1820. GDP in the Asia-Pacific region did not double over this period, as it was not until the latter half of the twentieth century when industrialization began on a large scale.

Aggregated data about fires detected by NASA satellites on orbit from 2017 to 2019. This dataset is more refined than the dataset on active fire data: the data has been processed to scientific-grade to correct errors and avoid false positives.

This collection includes historical oceanographic biological, biochemical, chemical, physical, meteorological, and other data. The data includes barometric pressure, cloud amount and frequency, current, wave, conductivity, nutrients, pH, salinity, temperature, turbidity, transmissivity, biomass measurements, nutrients, fluorescence, species and subspecies identification, phaeophytin, zooplankton, chlorophyll, dissolved oxygen, nitrate, nitrite, phosphate, silicate, alkalinity, and other measurements. These data were collected by bottle, net, CTD, XBT, MBT, BT, and other instruments from drifting buoy, ships, and other platforms in oceans and seas around the world.

Explore the historical Whois records related to history.expert (Domain). Get insights into ownership history and changes over time.

Historical HurricanesThis feature layer, utilizing data from the National Oceanic and Atmospheric Administration, displays hurricanes from 1842-2024. According to NOAA, "a tropical cyclone is a rotating low-pressure weather system that has organized thunderstorms but no fronts (a boundary separating two air masses of different densities). Tropical cyclones with maximum sustained surface winds of less than 39 miles per hour (mph) are called tropical depressions. Those with maximum sustained winds of 39 mph or higher are called tropical storms. When a storm's maximum sustained winds reach 74 mph, it is called a hurricane."Hurricane Andrew (1992)Data currency: December 31, 2024Data source: International Best Track Archive for Climate Stewardship (IBTrACS)Data modification: Field added - Hurricane DateFor more information: International Best Track Archive for Climate Stewardship (IBTrACS)Support documentation: IBTrACS v04 column documentationFor feedback, please contact: ArcGIScomNationalMaps@esri.comNational Oceanic and Atmospheric Administration (NOAA)Per NOAA, its mission is "To understand and predict changes in climate, weather, ocean, and coasts, to share that knowledge and information with others, and to conserve and manage coastal and marine ecosystems and resources."

This dataset is about book subjects and is filtered where the books includes Historical sailing ships : remote controlled, featuring 10 columns including authors, average publication date, book publishers, book subject, and books. The preview is ordered by number of books (descending).

This historical legacy dataset depicts the 50-year mean annual rainfall isoheyts (contours) over Queensland for the period 1920 to 1969. The dataset was a project activity, and produced from the mean annual rainfall of as many locations as possible including private collections. Incomplete datasets were made whole by calculating values for missing periods through correlation with adjacent rainfall stations.

Explore the historical Whois records related to switchdataprint.com (Domain). Get insights into ownership history and changes over time.