The United States has an average elevation of roughly 2,500 feet (763m) above sea level, however there is a stark contrast in elevations across the country. Highest states Colorado is the highest state in the United States, with an average elevation of 6,800 feet (2,074m) above sea level. The 10 states with the highest average elevation are all in the western region of the country, as this is, by far, the most mountainous region in the country. The largest mountain ranges in the contiguous western states are the Rocky Mountains, Sierra Nevada, and Cascade Range, while the Appalachian Mountains is the longest range in the east - however, the highest point in the U.S. is Denali (Mount McKinley), found in Alaska. Lowest states At just 60 feet above sea level, Delaware is the state with the lowest elevation. Delaware is the second smallest state, behind Rhode Island, and is located on the east coast. Larger states with relatively low elevations are found in the southern region of the country - both Florida and Louisiana have an average elevation of just 100 feet (31m) above sea level, and large sections of these states are extremely vulnerable to flooding and rising sea levels, as well as intermittent tropical storms.

How does your organization use this dataset? What other NYSERDA or energy-related datasets would you like to see on Open NY? Let us know by emailing OpenNY@nyserda.ny.gov. The Low- to Moderate-Income (LMI) New York State (NYS) Census Population Analysis dataset is resultant from the LMI market database designed by APPRISE as part of the NYSERDA LMI Market Characterization Study (https://www.nyserda.ny.gov/lmi-tool). All data are derived from the U.S. Census Bureau’s American Community Survey (ACS) 1-year Public Use Microdata Sample (PUMS) files for 2013, 2014, and 2015. Each row in the LMI dataset is an individual record for a household that responded to the survey and each column is a variable of interest for analyzing the low- to moderate-income population. The LMI dataset includes: county/county group, households with elderly, households with children, economic development region, income groups, percent of poverty level, low- to moderate-income groups, household type, non-elderly disabled indicator, race/ethnicity, linguistic isolation, housing unit type, owner-renter status, main heating fuel type, home energy payment method, housing vintage, LMI study region, LMI population segment, mortgage indicator, time in home, head of household education level, head of household age, and household weight. The LMI NYS Census Population Analysis dataset is intended for users who want to explore the underlying data that supports the LMI Analysis Tool. The majority of those interested in LMI statistics and generating custom charts should use the interactive LMI Analysis Tool at https://www.nyserda.ny.gov/lmi-tool. This underlying LMI dataset is intended for users with experience working with survey data files and producing weighted survey estimates using statistical software packages (such as SAS, SPSS, or Stata).

This map shows population density of the United States. Areas in darker magenta have much higher population per square mile than areas in orange or yellow. Data is from the U.S. Census Bureau’s 2020 Census Demographic and Housing Characteristics. The map's layers contain total population counts by sex, age, and race groups for Nation, State, County, Census Tract, and Block Group in the United States and Puerto Rico. From the Census:"Population density allows for broad comparison of settlement intensity across geographic areas. In the U.S., population density is typically expressed as the number of people per square mile of land area. The U.S. value is calculated by dividing the total U.S. population (316 million in 2013) by the total U.S. land area (3.5 million square miles).When comparing population density values for different geographic areas, then, it is helpful to keep in mind that the values are most useful for small areas, such as neighborhoods. For larger areas (especially at the state or country scale), overall population density values are less likely to provide a meaningful measure of the density levels at which people actually live, but can be useful for comparing settlement intensity across geographies of similar scale." SourceAbout the dataYou can use this map as is and you can also modify it to use other attributes included in its layers. This map's layers contain total population counts by sex, age, and race groups data from the 2020 Census Demographic and Housing Characteristics. This is shown by Nation, State, County, Census Tract, Block Group boundaries. Each geography layer contains a common set of Census counts based on available attributes from the U.S. Census Bureau. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.Vintage of boundaries and attributes: 2020 Demographic and Housing Characteristics Table(s): P1, H1, H3, P2, P3, P5, P12, P13, P17, PCT12 (Not all lines of these DHC tables are available in this feature layer.)Data downloaded from: U.S. Census Bureau’s data.census.gov siteDate the Data was Downloaded: May 25, 2023Geography Levels included: Nation, State, County, Census Tract, Block GroupNational Figures: included in Nation layer The United States Census Bureau Demographic and Housing Characteristics: 2020 Census Results 2020 Census Data Quality Geography & 2020 Census Technical Documentation Data Table Guide: includes the final list of tables, lowest level of geography by table and table shells for the Demographic Profile and Demographic and Housing Characteristics.News & Updates This map is ready to be used in ArcGIS Pro, ArcGIS Online and its configurable apps, Story Maps, dashboards, Notebooks, Python, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the U.S. Census Bureau when using this data. Data Processing Notes: These 2020 Census boundaries come from the US Census TIGER geodatabases. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For Census tracts and block groups, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract and block group boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are unchanged and available as attributes within the data table (units are square meters).  The layer contains all US states, Washington D.C., and Puerto Rico. Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99). Block groups that fall within the same criteria (Block Group denoted as 0 with no area land) have also been removed.Percentages and derived counts, are calculated values (that can be identified by the "_calc_" stub in the field name). Field alias names were created based on the Table Shells file available from the Data Table Guide for the Demographic Profile and Demographic and Housing Characteristics. Not all lines of all tables listed above are included in this layer. Duplicative counts were dropped. For example, P0030001 was dropped, as it is duplicative of P0010001.To protect the privacy and confidentiality of respondents, their data has been protected using differential privacy techniques by the U.S. Census Bureau.

The official State census for Common Least Terns in Massachusetts

Out of all 50 states, New York had the highest per-capita real gross domestic product (GDP) in 2023, at 90,730 U.S. dollars, followed closely by Massachusetts. Mississippi had the lowest per-capita real GDP, at 39,102 U.S. dollars. While not a state, the District of Columbia had a per capita GDP of more than 214,000 U.S. dollars. What is real GDP? A country’s real GDP is a measure that shows the value of the goods and services produced by an economy and is adjusted for inflation. The real GDP of a country helps economists to see the health of a country’s economy and its standard of living. Downturns in GDP growth can indicate financial difficulties, such as the financial crisis of 2008 and 2009, when the U.S. GDP decreased by 2.5 percent. The COVID-19 pandemic had a significant impact on U.S. GDP, shrinking the economy 2.8 percent. The U.S. economy rebounded in 2021, however, growing by nearly six percent. Why real GDP per capita matters Real GDP per capita takes the GDP of a country, state, or metropolitan area and divides it by the number of people in that area. Some argue that per-capita GDP is more important than the GDP of a country, as it is a good indicator of whether or not the country’s population is getting wealthier, thus increasing the standard of living in that area. The best measure of standard of living when comparing across countries is thought to be GDP per capita at purchasing power parity (PPP) which uses the prices of specific goods to compare the absolute purchasing power of a countries currency.

United States PCE: PI: Qtr: Less Formula Eff: Tobacco data was reported at 0.000 Point in Mar 2013. This stayed constant from the previous number of 0.000 Point for Dec 2012. United States PCE: PI: Qtr: Less Formula Eff: Tobacco data is updated quarterly, averaging 0.000 Point from Mar 2002 (Median) to Mar 2013, with 45 observations. The data reached an all-time high of 0.010 Point in Jun 2003 and a record low of -0.090 Point in Jun 2009. United States PCE: PI: Qtr: Less Formula Eff: Tobacco data remains active status in CEIC and is reported by Bureau of Economic Analysis. The data is categorized under Global Database’s USA – Table US.A139: NIPA 2009: Personal Consumption Expenditure Price Index and CPI Reconciliation: Quarterly.

About this dataset

Context

The dataset presents the mean household income for each of the five quintiles in United States, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

Key observations

• Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 16,840, while the mean income for the highest quintile (20% of households with the highest income) is 285,351. This indicates that the top earners earn 17 times compared to the lowest earners.
• *Top 5%: * The mean household income for the wealthiest population (top 5%) is 515,555, which is 180.67% higher compared to the highest quintile, and 3061.49% higher compared to the lowest quintile.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income Levels:

• Lowest Quintile
• Second Quintile
• Third Quintile
• Fourth Quintile
• Highest Quintile
• Top 5 Percent

Variables / Data Columns

• Income Level: This column showcases the income levels (As mentioned above).
• Mean Household Income: Mean household income, in 2023 inflation-adjusted dollars for the specific income level.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for United States median household income. You can refer the same here

United States PCE: PI: Less Wt Effect: Rent of Shelter (RS) data was reported at -0.030 Point in May 2013. This stayed constant from the previous number of -0.030 Point for Apr 2013. United States PCE: PI: Less Wt Effect: Rent of Shelter (RS) data is updated monthly, averaging -0.030 Point from Jan 2002 (Median) to May 2013, with 137 observations. The data reached an all-time high of 0.010 Point in Mar 2010 and a record low of -0.070 Point in May 2006. United States PCE: PI: Less Wt Effect: Rent of Shelter (RS) data remains active status in CEIC and is reported by Bureau of Economic Analysis. The data is categorized under Global Database’s USA – Table US.A200: NIPA 2009: Personal Consumption Expenditure Price Index and CPI Reconciliation: Monthly.

Announcement Beginning October 20, 2022, CDC will report and publish aggregate case and death data from jurisdictional and state partners on a weekly basis rather than daily. As a result, community transmission levels data reported on data.cdc.gov will be updated weekly on Thursdays, typically by 8 PM ET, instead of daily. This public use dataset has 7 data elements reflecting historical data for community transmission levels for all available counties. This dataset contains historical data for the county level of community transmission and includes updated data submitted by states and jurisdictions. Each day, the dataset is appended to contain the most recent day's data. This dataset includes data from January 1, 2021. Transmission level is set to low, moderate, substantial, or high using the calculation rules below. Currently, CDC provides the public with two versions of COVID-19 county-level community transmission level data: this dataset with the levels for each county from January 1, 2021 (Historical Changes dataset) and a dataset with the levels as originally posted (Originally Posted dataset), updated daily with the most recent day’s data. 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); Substantial (8.00-9.99); and High (greater than or equal to 10.00). If the two metrics suggest different transmission levels, the higher level is selected. If one metric is missing, the other metric is used for the indicator. Transmission categories include: Low Transmission Threshold: Counties with fewer than 10 total cases per 100,000 population in the past 7 days, and a NAAT percent test positivity in the past 7 days below 5%; Moderate Transmission Threshold: Counties with 10-49 total cases per 100,000 population in the past 7 days or a NAAT test percent positivity in the past 7 days of 5.0-7.99%; Substantial Transmission Threshold: Counties with 50-99 total cases per 100,000 population in the past 7 days or a NAAT test percent positivity in the past 7 days of 8.0-9.99%; High Transmission Threshold: Counties with 100

This dataset provides information on 433 in California, United States as of June, 2025. It includes details such as email addresses (where publicly available), phone numbers (where publicly available), and geocoded addresses. Explore market trends, identify potential business partners, and gain valuable insights into the industry. Download a complimentary sample of 10 records to see what's included.

This USGS data release contains 7Q10 and 30Q10 [lowest annual 7-day and 30-day average streamflow that occurs (on average) once every 10 years] statistics at 292 USGS streamgages in or adjacent to New York State excluding Long Island. all_sites_wstats.csv - includes 7Q10 and 30Q10 values for all sites and includes information on results from the trend analysis and which sites have daily exceedance probability values available. site_regulated_7day_exc_perc#.csv and site_regulated_30day_exc_perc#.csv files include daily exceedance probability values for all altered sites that were not suitable for calculating low flow statistics. R scripts used to compile and screen streamgage datasets of daily flow, perform trend analysis, and calculate the low streamflow statistics 7Q10 and 30Q10 are included in processing_scripts.zip. Users are encouraged to read the readme file in this zipped file for details on the scripts and associated files used to generate the statistics.

Graph and download economic data for Estimated Percent of People of All Ages in Poverty for United States (PPAAUS00000A156NCEN) from 1989 to 2023 about percent, child, poverty, and USA.

This dataset provides information on 60 in Colorado, United States as of June, 2025. It includes details such as email addresses (where publicly available), phone numbers (where publicly available), and geocoded addresses. Explore market trends, identify potential business partners, and gain valuable insights into the industry. Download a complimentary sample of 10 records to see what's included.

This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from the U.S. Census Bureau’s American Community Survey 5-year estimates for 2013-2017, to show levels of educational attainment by State of Georgia in the Atlanta region. The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent. The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2013-2017). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available. For further explanation of ACS estimates and margin of error, visit Census ACS website. Naming conventions: Prefixes:NoneCountpPercentrRatemMedianaMean (average)tAggregate (total)chChange in absolute terms (value in t2 - value in t1)pchPercent change ((value in t2 - value in t1) / value in t1)chpChange in percent (percent in t2 - percent in t1)Suffixes:NoneChange over two periods_eEstimate from most recent ACS_mMargin of Error from most recent ACS_00Decennial 2000 Attributes: SumLevelSummary level of geographic unit (e.g., County, Tract, NSA, NPU, DSNI, SuperDistrict, etc)GEOIDCensus tract Federal Information Processing Series (FIPS) code NAMEName of geographic unitPlanning_RegionPlanning region designation for ARC purposesAcresTotal area within the tract (in acres)SqMiTotal area within the tract (in square miles)CountyCounty identifier (combination of Federal Information Processing Series (FIPS) codes for state and county)CountyNameCounty NamePop25P_e# Population 25 years and over, 2017Pop25P_m# Population 25 years and over, 2017 (MOE)NoHS_e# Population 25 years and over, less than 9th grade education, 2017NoHS_m# Population 25 years and over, less than 9th grade education, 2017 (MOE)pNoHS_e% Population 25 years and over, less than 9th grade education, 2017pNoHS_m% Population 25 years and over, less than 9th grade education, 2017 (MOE)SomeHS_e# Population 25 years and over, 9th-12th grade, no diploma, 2017SomeHS_m# Population 25 years and over, 9th-12th grade, no diploma, 2017 (MOE)pSomeHS_e% Population 25 years and over, 9th-12th grade, no diploma, 2017pSomeHS_m% Population 25 years and over, 9th-12th grade, no diploma, 2017 (MOE)HSGrad_e# Population 25 years and over, high school graduate (includes GED), 2017HSGrad_m# Population 25 years and over, high school graduate (includes GED), 2017 (MOE)pHSGrad_e% Population 25 years and over, high school graduate (includes GED), 2017pHSGrad_m% Population 25 years and over, high school graduate (includes GED), 2017 (MOE)SomeColl_e# Population 25 years and over, some college, no degree, 2017SomeColl_m# Population 25 years and over, some college, no degree, 2017 (MOE)pSomeColl_e% Population 25 years and over, some college, no degree, 2017pSomeColl_m% Population 25 years and over, some college, no degree, 2017 (MOE)Associates_e# Population 25 years and over, associate's degree, 2017Associates_m# Population 25 years and over, associate's degree, 2017 (MOE)pAssociates_e% Population 25 years and over, associate's degree, 2017pAssociates_m% Population 25 years and over, associate's degree, 2017 (MOE)BA_e# Population 25 years and over, bachelor's degree, 2017BA_m# Population 25 years and over, bachelor's degree, 2017 (MOE)pBA_e% Population 25 years and over, bachelor's degree, 2017pBA_m% Population 25 years and over, bachelor's degree, 2017 (MOE)GradProf_e# Population 25 years and over, graduate or professional degree, 2017GradProf_m# Population 25 years and over, graduate or professional degree, 2017 (MOE)pGradProf_e% Population 25 years and over, graduate or professional degree, 2017pGradProf_m% Population 25 years and over, graduate or professional degree, 2017 (MOE)LtHS_e# Population 25 years and over, Less than high school graduate, 2017LtHS_m# Population 25 years and over, Less than high school graduate, 2017 (MOE)pLtHS_e% Population 25 years and over, Less than high school graduate, 2017pLtHS_m% Population 25 years and over, Less than high school graduate, 2017 (MOE)HSPlus_e# Population 25 years and over, high school graduate or higher, 2017HSPlus_m# Population 25 years and over, high school graduate or higher, 2017 (MOE)pHSPlus_e% Population 25 years and over, high school graduate or higher, 2017pHSPlus_m% Population 25 years and over, high school graduate or higher, 2017 (MOE)BAPlus_e# Population 25 years and over, bachelor's degree or higher, 2017BAPlus_m# Population 25 years and over, bachelor's degree or higher, 2017 (MOE)pBAPlus_e% Population 25 years and over, bachelor's degree or higher, 2017pBAPlus_m% Population 25 years and over, bachelor's degree or higher, 2017 (MOE)last_edited_dateLast date the feature was edited by ARC Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2013-2017 For additional information, please visit the Census ACS website.

Although the founding fathers declared American independence in 1776, and the subsequent Revolutionary War ended in 1783, individual states did not officially join the union until 1787. The first states to ratify the U.S. Constitution were Delaware, Pennsylvania and New Jersey, in December 1787, and they were joined by the remainder of the thirteen ex-British colonies by 1790. Another three states joined before the turn of the nineteenth century, and there were 45 states by 1900. The final states, Alaska and Hawaii, were admitted to the union in 1959, almost 172 years after the first colonies became federal states. Secession in the American Civil War The issues of slavery and territorial expansion in the mid nineteenth century eventually led to the American Civil War, which lasted from 1861 until 1865. As the U.S. expanded westwards, a moral and economic argument developed about the legality of slavery in these new states; northern states were generally opposed to the expansion of slavery, whereas the southern states (who were economically dependent on slavery) saw this lack of extension as a stepping stone towards nationwide abolition. In 1861, eleven southern states seceded from the Union, and formed the Confederate States of America. When President Lincoln refused to relinquish federal property in the south, the Confederacy attacked, setting in motion the American Civil War. After four years, the Union emerged victorious, and the Confederate States of America was disbanded, and each individual state was readmitted to Congress gradually, between 1866 and 1870. Expansion of other territories Along with the fifty U.S. states, there is one federal district (Washington D.C., the capital city), and fourteen overseas territories, five of which with a resident population (American Samoa, Guam, the Northern Mariana Islands, Puerto Rico, and the U.S. Virgin Islands). In 2019, President Trump inquired about the U.S. purchasing the territory of Greenland from Denmark, and, although Denmark's response indicated that this would be unlikely, this does suggest that the US may be open to further expansion of it's states and territories in the future. There is also a movement to make Washington D.C. the 51st state to be admitted to the union, as citizens of the nation's capital (over 700,000 people) do not have voting representation in the houses of Congress nor control over many local affairs; as of 2020, the U.S. public appears to be divided on the issue, and politicians are split along party lines, as D.C. votes overwhelmingly for the Democratic nominee in presidential elections.

This dataset provides information on 98 in Ohio, United States as of May, 2025. It includes details such as email addresses (where publicly available), phone numbers (where publicly available), and geocoded addresses. Explore market trends, identify potential business partners, and gain valuable insights into the industry. Download a complimentary sample of 10 records to see what's included.

This dataset provides information on 31 in Montana, United States as of June, 2025. It includes details such as email addresses (where publicly available), phone numbers (where publicly available), and geocoded addresses. Explore market trends, identify potential business partners, and gain valuable insights into the industry. Download a complimentary sample of 10 records to see what's included.

United States SL: saar: CA: Less: Consumption of Fixed Capital data was reported at 271.195 USD bn in Mar 2018. This records an increase from the previous number of 267.996 USD bn for Dec 2017. United States SL: saar: CA: Less: Consumption of Fixed Capital data is updated quarterly, averaging 45.532 USD bn from Dec 1951 (Median) to Mar 2018, with 266 observations. The data reached an all-time high of 271.195 USD bn in Mar 2018 and a record low of 2.621 USD bn in Dec 1951. United States SL: saar: CA: Less: Consumption of Fixed Capital data remains active status in CEIC and is reported by Federal Reserve Board. The data is categorized under Global Database’s USA – Table US.AB080: Integrated Macroeconomic Accounts: State and Local Governments.

When analyzing the ratio of homelessness to state population, New York, Vermont, and Oregon had the highest rates in 2023. However, Washington, D.C. had an estimated 73 homeless individuals per 10,000 people, which was significantly higher than any of the 50 states. Homeless people by race The U.S. Department of Housing and Urban Development performs homeless counts at the end of January each year, which includes people in both sheltered and unsheltered locations. The estimated number of homeless people increased to 653,104 in 2023 – the highest level since 2007. However, the true figure is likely to be much higher, as some individuals prefer to stay with family or friends - making it challenging to count the actual number of homeless people living in the country. In 2023, nearly half of the people experiencing homelessness were white, while the number of Black homeless people exceeded 243,000. How many veterans are homeless in America? The  number of homeless veterans in the United States has halved since 2010. The state of California, which is currently suffering a homeless crisis, accounted for the highest number of homeless veterans in 2022. There are many causes of homelessness among veterans of the U.S. military, including post-traumatic stress disorder (PTSD), substance abuse problems, and a lack of affordable housing.

United States SBP: KS: Back to Usual Operations: 1 Mos or Less data was reported at 5.200 % in 20 Sep 2020. This records a decrease from the previous number of 5.500 % for 13 Sep 2020. United States SBP: KS: Back to Usual Operations: 1 Mos or Less data is updated weekly, averaging 6.300 % from Apr 2020 (Median) to 20 Sep 2020, with 12 observations. The data reached an all-time high of 8.700 % in 23 Aug 2020 and a record low of 5.000 % in 07 Jun 2020. United States SBP: KS: Back to Usual Operations: 1 Mos or Less data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.S048: Small Business Pulse Survey: by State: Midwest Region: Weekly, Beg Sunday (Discontinued).