The main stock market index of United States, the US500, rose to 6391 points on July 31, 2025, gaining 0.45% from the previous session. Over the past month, the index has climbed 3.12% and is up 17.34% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from United States. United States Stock Market Index - values, historical data, forecasts and news - updated on July of 2025.

View data of the S&P 500, an index of the stocks of 500 leading companies in the US economy, which provides a gauge of the U.S. equity market.

United States Leading Economic Index: Diffusion Index: 6 Months data was reported at 70.000 NA in Dec 2024. This records an increase from the previous number of 60.000 NA for Nov 2024. United States Leading Economic Index: Diffusion Index: 6 Months data is updated monthly, averaging 70.000 NA from Apr 1959 (Median) to Dec 2024, with 789 observations. The data reached an all-time high of 100.000 NA in Apr 2018 and a record low of 0.000 NA in Nov 2007. United States Leading Economic Index: Diffusion Index: 6 Months data remains active status in CEIC and is reported by The Conference Board. The data is categorized under Global Database’s United States – Table US.The Conference Board: Leading Economic Index. [COVID-19-IMPACT]

An Environmental Quality Index (EQI) for all counties in the United States for the time period 2000-2005 was developed which incorporated data from five environmental domains: air, water, land, built, and socio-demographic. The EQI was developed in four parts: domain identification; data source identification and review; variable construction; and data reduction using principal components analysis (PCA). The methods applied provide a reproducible approach that capitalizes almost exclusively on publically-available data sources. The primary goal in creating the EQI is to use it as a composite environmental indicator for research on human health. A series of peer reviewed manuscripts utilized the EQI in examining health outcomes. This dataset is not publicly accessible because: This series of papers are considered Human health research - not to be loaded onto ScienceHub. It can be accessed through the following means: The EQI data can be accessed at: https://edg.epa.gov/data/Public/ORD/NHEERL/EQI. Format: EQI data, metadata, formats, and data dictionary all available at website. This dataset is associated with the following publications: Gray, C., L. Messer, K. Rappazzo, J. Jagai, S. Grabich, and D. Lobdell. The association between physical inactivity and obesity is modified by five domains of environmental quality in U.S. adults: A cross-sectional study. PLoS ONE. Public Library of Science, San Francisco, CA, USA, 13(8): e0203301, (2018). Patel, A., J. Jagai, L. Messer, C. Gray, K. Rappazzo, S. DeflorioBarker, and D. Lobdell. Associations between environmental quality and infant mortality in the United States, 2000-2005. Archives of Public Health. BioMed Central Ltd, London, UK, 76(60): 1, (2018). Gray, C., D. Lobdell, K. Rappazzo, Y. Jian, J. Jagai, L. Messer, A. Patel, S. Deflorio-Barker, C. Lyttle, J. Solway, and A. Rzhetsky. Associations between environmental quality and adult asthma prevalence in medical claims data. ENVIRONMENTAL RESEARCH. Elsevier B.V., Amsterdam, NETHERLANDS, 166: 529-536, (2018).

This table contains data on the modified retail food environment index for California, its regions, counties, cities, towns, and census tracts. An adequate, nutritious diet is a necessity at all stages of life. Pregnant women and their developing babies, children, adolescents, adults, and older adults depend on adequate nutrition for optimum development and maintenance of health and functioning. Nutrition also plays a significant role in causing or preventing a number of illnesses, such as cardiovascular disease, some cancers, obesity, type-2 diabetes, and anemia. Peoples’ food choices and their likelihood of being overweight or obese are also influenced by their food environment: the foods available in their neighborhoods including stores, restaurants, schools, and worksites.

The modified retail food environment index table is part of a series of indicators in the Healthy Communities Data and Indicators Project (HCI) of the Office of Health Equity. The goal of HCI is to enhance public health by providing data, a standardized set of statistical measures, and tools that a broad array of sectors can use for planning healthy communities and evaluating the impact of plans, projects, policy, and environmental changes on community health. The creation of healthy social, economic, and physical environments that promote healthy behaviors and healthy outcomes requires coordination and collaboration across multiple sectors, including transportation, housing, education, agriculture and others. Statistical metrics, or indicators, are needed to help local, regional, and state public health and partner agencies assess community environments and plan for healthy communities that optimize public health. More information on HCI can be found here: https://www.cdph.ca.gov/Programs/OHE/CDPH%20Document%20Library/Accessible%202%20CDPH_Healthy_Community_Indicators1pager5-16-12.pdf

The format of the modified retail food environment table is based on the standardized data format for all HCI indicators. As a result, this data table contains certain variables used in the HCI project (e.g., indicator ID, and indicator definition). Some of these variables may contain the same value for all observations.

The Case Mix Index (CMI) is the average relative DRG weight of a hospital’s inpatient discharges, calculated by summing the Medicare Severity-Diagnosis Related Group (MS-DRG) weight for each discharge and dividing the total by the number of discharges. The CMI reflects the diversity, clinical complexity, and resource needs of all the patients in the hospital. A higher CMI indicates a more complex and resource-intensive case load. Although the MS-DRG weights, provided by the Centers for Medicare & Medicaid Services (CMS), were designed for the Medicare population, they are applied here to all discharges regardless of payer. Note: It is not meaningful to add the CMI values together.

Twelve Data is a technology-driven company that provides financial market data, financial tools, and dedicated solutions. Large audiences - from individuals to financial institutions - use our products to stay ahead of the competition and success.

At Twelve Data we feel responsible for where the markets are going and how people are able to explore them. Coming from different technological backgrounds, we see how the world is lacking the unique and simple place where financial data can be accessed by anyone, at any time. This is what distinguishes us from others, we do not only supply the financial data but instead, we want you to benefit from it, by using the convenient format, tools, and special solutions.

We believe that the human factor is still a very important aspect of our work and therefore our ethics guides us on how to treat people, with convenient and understandable resources. This includes world-class documentation, human support, and dedicated solutions.

United States Import Value Index data was reported at 126.779 2015=100 in 2021. This records an increase from the previous number of 103.958 2015=100 for 2020. United States Import Value Index data is updated yearly, averaging 51.384 2015=100 from Dec 1980 (Median) to 2021, with 42 observations. The data reached an all-time high of 126.779 2015=100 in 2021 and a record low of 11.319 2015=100 in 1982. United States Import Value Index data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Trade Index. Import value indexes are the current value of imports (c.i.f.) converted to U.S. dollars and expressed as a percentage of the average for the base period (2015). UNCTAD's import value indexes are reported for most economies.;United Nations Conference on Trade and Development;;

The real-time index database market is experiencing robust growth, driven by the increasing demand for immediate insights from large volumes of data across diverse sectors. The market's expansion is fueled by the proliferation of IoT devices generating massive real-time data streams, the need for faster decision-making in competitive environments, and the rise of sophisticated analytics applications requiring rapid data access. Cloud-based solutions dominate the market due to their scalability, cost-effectiveness, and ease of deployment, attracting both individual users and large enterprises. However, concerns around data security and latency in cloud-based systems present some restraints. The on-premises segment, while smaller, continues to cater to businesses with stringent data sovereignty requirements or those managing exceptionally sensitive information. Key players like Elastic, Amazon Web Services, Apache Solr, Splunk, and Microsoft are shaping the market landscape through continuous innovation and competitive offerings. Geographic distribution reflects the concentration of technological infrastructure and data generation, with North America and Europe currently leading the market, followed by the Asia-Pacific region showing significant potential for future growth. The market's Compound Annual Growth Rate (CAGR) suggests a consistent upward trajectory, indicating continued investment and market expansion throughout the forecast period. The competitive dynamics are marked by a mix of established players and emerging entrants. Established players leverage their existing infrastructure and customer bases, while new entrants focus on niche areas and innovative solutions. The market is also witnessing increased adoption of hybrid models combining cloud and on-premises solutions to balance cost-efficiency, security, and performance. Future growth will depend on technological advancements, particularly in areas like distributed ledger technology and edge computing, which will enhance the real-time capabilities and scalability of index databases. Furthermore, the increasing focus on data governance and regulatory compliance will also influence market adoption and shape the development of future solutions. The market is anticipated to witness a sustained period of growth, fueled by the ever-growing demand for real-time data analytics and insights across various sectors and regions.

This dataset contains all the citation data (in N-Triples format) included in the OpenCitations Index, released on March 24, 2025. In particular, any citation in the dataset, defined as an individual of the class cito:Citation, includes the following information:[citation IRI] the Open Citation Identifier (OCI) for the citation, defined in the final part of the URL identifying the citation (https://w3id.org/oc/index/ci/[OCI]);[property "cito:hasCitingEntity"] the citing entity identified by its OMID URL (https://https://opencitations.net/meta/[OMID]);[property "cito:hasCitedEntity"] the cited entity identified by its OMID URL (https://https://opencitations.net/meta/[OMID]);[property "cito:hasCitationCreationDate"] the creation date of the citation (i.e. the publication date of the citing entity);[property "cito:hasCitationTimeSpan"] the time span of the citation (i.e. the interval between the publication date of the cited entity and the publication date of the citing entity);[type "cito:JournalSelfCitation"] it records whether the citation is a journal self-citations (i.e. the citing and the cited entities are published in the same journal);[type "cito:AuthorSelfCitation"] it records whether the citation is an author self-citation (i.e. the citing and the cited entities have at least one author in common).Note: the information for each citation is sourced from OpenCitations Meta (https://opencitations.net/meta), a database that stores and delivers bibliographic metadata for all bibliographic resources included in the OpenCitations Indexes. The data provided in this dump is therefore based on the state of OpenCitations Meta at the time this collection was generated.This version of the dataset contains:2,155,497,918 citationsThe size of the zipped archive is 80.6 GB, while the size of the unzipped N-Triples files is 1.9 TB.

United States Leading Index: US data was reported at 1.718 % in Feb 2020. This records an increase from the previous number of 1.573 % for Jan 2020. United States Leading Index: US data is updated monthly, averaging 1.536 % from Jan 1982 (Median) to Feb 2020, with 458 observations. The data reached an all-time high of 3.355 % in Nov 1983 and a record low of -2.654 % in Mar 2009. United States Leading Index: US data remains active status in CEIC and is reported by Federal Reserve Bank of Philadelphia. The data is categorized under Global Database’s United States – Table US.S012: State Leading Index. The data predicts the six-month growth rate of the state’s coincident index. In addition to the coincident index, the models include other variables that lead the economy such as the state-level housing permits (1 to 4 units), initial unemployment insurance claims, delivery times from the Institute for Supply Management (ISM) manufacturing survey, and the interest rate spread between the 10-year Treasury bond and the 3-month Treasury bill. Given the sudden, extreme impact of the COVID-19 outbreak on initial unemployment claims in recent weeks, Federal Reserve Bank of Philadelphia researchers’ standard approach for estimating the six-month change in coincident indexes is not appropriate. Therefore, they suspended the release of the state leading indexes indefinitely.

Updated investor sentiment index dataset up to December 2014 (including both Baker and Wurgler's sentiment index, and Huang, Jiang, Tu and Zhou (2015 RFS)'s investor sentiment index)

For lands used to produce crops, CEC developed a suitability model to simultaneously evaluate several factors that impact an area’s relative implication for croplands. In the CEC land use screens, implication is defined as a possible significance or a likely consequence of an action. For example, planning for energy infrastructure development in areas with more factors that support high-value croplands has implications for opportunities to preserve agricultural land. The variables used in the CEC Cropland Index Model contain information on soil quality (CA Revised Storie Index, Electrical Conductivity, and Sodium Adsorption Ratio), farmland designations (Prime Farmland, Unique Farmland and Farmland of Statewide Importance), and current existence of crops (as indicated by the California Statewide Crop Mapping). The CEC Cropland Index Model does not include statewide information for grazing lands or rangelands, and it is only applied to solar technology.

Each input data layer is transformed onto a common scale and weighted according to each dataset’s relative importance. The result is a summation of the input data layers into a single-gridded map. This final model output provides a numerically weighted index of importance for croplands at a given location. The classified version of the model output, given in this dataset, partitions the CEC Cropland Index Model at the mean into areas of high and low implication. The high implication area is used as an exclusion in the CEC Land Use Screens for solar technology. These regions have a relatively higher implication for cropland than the lower implication region.

The table below provides data sources that the CEC Cropland Index Model relies on. For a complete description of the model and its use in the 2023 CEC Land-Use Screens, please refer to the Land Use Screens Staff Report in the CEC Energy Planning Library.

This dataset provides values for INDEX reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

United States CCI: Mountain data was reported at 84.800 1985=100 in Apr 2025. This records a decrease from the previous number of 99.700 1985=100 for Mar 2025. United States CCI: Mountain data is updated monthly, averaging 101.200 1985=100 from Jan 1981 (Median) to Apr 2025, with 532 observations. The data reached an all-time high of 152.400 1985=100 in Sep 2018 and a record low of 24.800 1985=100 in Feb 2009. United States CCI: Mountain data remains active status in CEIC and is reported by The Conference Board. The data is categorized under Global Database’s United States – Table US.H049: Consumer Confidence Index. [COVID-19-IMPACT]

About Transportation Services Index

The Transportation Services Index (TSI), created by the U.S. Department of Transportation (DOT), Bureau of Transportation Statistics (BTS), measures the movement of freight and passengers. The index, which is seasonally adjusted, combines available data on freight traffic, as well as passenger travel, that have been weighted to yield a monthly measure of transportation services output.

For charts and discussion on the relationship of the TSI to the economy, see our Transportation as an Economic Indicator: Transportation Services Index page (https://data.bts.gov/stories/s/TET-indicator-1/9czv-tjte)

For release schedule see: https://www.bts.gov/newsroom/transportation-services-index-release-schedule

About seasonally-adjusted data

Statisticians use the process of seasonal-adjustment to uncover trends in data. Monthly data, for instance, are influenced by the number of days and the number of weekends in a month as well as by the timing of holidays and seasonal activity. These influences make it difficult to see underlying changes in the data. Statisticians use seasonal adjustment to control for these influences.

Controlling of seasonal influences allows measurement of real monthly changes; short and long term patterns of growth or decline; and turning points. Data for one month can be compared to data for any other month in the series and the data series can be ranked to find high and low points. Any observed differences are “real” differences; that is, they are differences brought about by changes in the data and not brought about by a change in the number of days or weekends in the month, the occurrence or non-occurrence of a holiday, or seasonal activity.

France: Innovations index (0-100): The latest value from 2024 is 55.4 points, a decline from 56.02 points in 2023. In comparison, the world average is 31.57 points, based on data from 132 countries. Historically, the average for France from 2011 to 2024 is 53.69 points. The minimum value, 49.3 points, was reached in 2011 while the maximum of 56.02 points was recorded in 2023.

The Elemental Data Index provides access to the holdings of NIST Physical Measurement Laboratory (PML) online data organized by element. It is intended to simplify the process of retrieving online scientific data for a specific element from various online databases, including atomic spectroscopy, atomic data, x-ray absorption, and nuclear data. For some of the databases, the data are immediately retrieved; for others, the retrieval form is provided with the element entered in the form, but additional options must be selected in order to retrieve the data. Each of the databases can be individually accessed from the PML's Physical Reference Data page (http://pml.nist.gov/data).

Geophysics that are shown as polygons. Sometimes the real position of geophysical lines cannot be shown because of confidentiality reasons and in this case a polygon that shows the approximate location is used instead. In other cases the geophysics is best represented by a polygon – for example for 3D seismic surveys.