9 datasets found
  1. A

    ‘District Resource Statement - SNAP Population’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Jan 26, 2022
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2022). ‘District Resource Statement - SNAP Population’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-district-resource-statement-snap-population-15a4/59c59309/?iid=003-718&v=presentation
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    Dataset updated
    Jan 26, 2022
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Analysis of ‘District Resource Statement - SNAP Population’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/4ef4a33e-02ab-4923-a148-6f6cfb57d4dc on 26 January 2022.

    --- Dataset description provided by original source is as follows ---

    Population of individuals and households receiving SNAP Benefits. For a complete list of District Resource Statement datasets,please follow this link.

    --- Original source retains full ownership of the source dataset ---

  2. d

    Borough/Community District Report

    • catalog.data.gov
    • data.cityofnewyork.us
    • +1more
    Updated Apr 19, 2025
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    data.cityofnewyork.us (2025). Borough/Community District Report [Dataset]. https://catalog.data.gov/dataset/borough-community-district-report
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    Dataset updated
    Apr 19, 2025
    Dataset provided by
    data.cityofnewyork.us
    Description

    Population of individuals and households receiving Supplemental Nutrition Assistance Program (SNAP), Cash Assistance (CA), or Medicaid Benefits (MA) as shown on the Borough Consultation Report.

  3. V

    Number of Households With 60+ Older Adult Receiving SNAP/Food Stamps (by...

    • data.virginia.gov
    csv
    Updated Apr 5, 2024
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    Datathon 2024 (2024). Number of Households With 60+ Older Adult Receiving SNAP/Food Stamps (by Planning and Service Area [PSA]) -VA [Dataset]. https://data.virginia.gov/dataset/number-of-households-with-60-older
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    csv(10856)Available download formats
    Dataset updated
    Apr 5, 2024
    Dataset authored and provided by
    Datathon 2024
    Description

    Data Source: U.S. Census Bureau, American Community Survey (ACS) 5-year Estimates 2016-2020 .
    *Note. The total population refers to households with at least one person aged 60 years and over.

  4. d

    District Resource Statement (DRS)

    • catalog.data.gov
    • data.cityofnewyork.us
    Updated Mar 8, 2024
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    data.cityofnewyork.us (2024). District Resource Statement (DRS) [Dataset]. https://catalog.data.gov/dataset/district-resource-statement-drs
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    Dataset updated
    Mar 8, 2024
    Dataset provided by
    data.cityofnewyork.us
    Description

    This dataset includes information regarding the population of individuals and households receiving SNAP, Cash Assistance, and/or Medicaid.

  5. d

    Demographics

    • catalog.data.gov
    • datasets.ai
    • +4more
    Updated Nov 22, 2024
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    Lake County Illinois GIS (2024). Demographics [Dataset]. https://catalog.data.gov/dataset/demographics-0be32
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    Dataset updated
    Nov 22, 2024
    Dataset provided by
    Lake County Illinois GIS
    Description

    Lake County, Illinois Demographic Data. Explanation of field attributes: Total Population – The entire population of Lake County. White – Individuals who are of Caucasian race. This is a percent.African American – Individuals who are of African American race. This is a percent.Asian – Individuals who are of Asian race. This is a percent. Hispanic – Individuals who are of Hispanic ethnicity. This is a percent. Does not Speak English- Individuals who speak a language other than English in their household. This is a percent. Under 5 years of age – Individuals who are under 5 years of age. This is a percent. Under 18 years of age – Individuals who are under 18 years of age. This is a percent. 18-64 years of age – Individuals who are between 18 and 64 years of age. This is a percent. 65 years of age and older – Individuals who are 65 years old or older. This is a percent. Male – Individuals who are male in gender. This is a percent. Female – Individuals who are female in gender. This is a percent. High School Degree – Individuals who have obtained a high school degree. This is a percent. Associate Degree – Individuals who have obtained an associate degree. This is a percent. Bachelor’s Degree or Higher – Individuals who have obtained a bachelor’s degree or higher. This is a percent. Utilizes Food Stamps – Households receiving food stamps/ part of SNAP (Supplemental Nutrition Assistance Program). This is a percent. Median Household Income - A median household income refers to the income level earned by a given household where half of the homes in the area earn more and half earn less. This is a dollar amount. No High School – Individuals who have not obtained a high school degree. This is a percent. Poverty – Poverty refers to families and people whose income in the past 12 months is below the poverty level. This is a percent.

  6. V

    HRTPO Transportation-Vulnerable Communities

    • data.virginia.gov
    • hub.arcgis.com
    Updated Nov 25, 2024
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    Hampton Roads PDC & Hampton Roads TPO (2024). HRTPO Transportation-Vulnerable Communities [Dataset]. https://data.virginia.gov/dataset/hrtpo-transportation-vulnerable-communities
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    html, geojson, csv, kml, zip, arcgis geoservices rest apiAvailable download formats
    Dataset updated
    Nov 25, 2024
    Dataset provided by
    HRPDC & HRTPO
    Authors
    Hampton Roads PDC & Hampton Roads TPO
    Description

    StoryMap link:https://arcg.is/1OXPW1

    This dataset contains the Hampton Roads Transportation Planning Organization (HRTPO) 9 Environmental Justice (EJ) Indicators (Carless Households, Cash Public Assistance Households, Disabled Population, Elderly Population, Female Head of Household, Food Stamps/SNAP Household, Limited English Proficiency Population, Minority Population, and Low-Income/Poverty Households) at the Census Block Group level. The U.S. Census data source uses the 2017-2021 ACS 5-Year Estimates. The dataset includes Youth Population, which is not an EJ Indicator but is used in the Transportation Challenges and Strategies Long-Range Transportation Plan (LRTP) report. This data will be used for the HRTPO 2050 LRTP, for planning purposes only.

    Title VI - Environmental Justice Framework

    Applied to 2050 Long-Range Transportation Plan

    Introduction
    Providing equitable access to transportation is essential for thriving communities. Below are federal regulations to help foster transportation equity.
    Title VI of the Civil Rights Act prohibits discrimination based on race, color, and national origin in programs and activities receiving federal financial assistance.
    Environmental Justice (EJ) is the fair treatment and meaningful involvement of all people regardless of race, color, national origin, or income with respect to the development, implementation, and enforcement of environmental laws, regulations, and policies. The Environmental Justice Executive Order 12898, signed in 1994, reinforces the requirements of Title VI.
    Transportation-Vulnerability Key Indicators
    The following transportation-vulnerability key indicators were used to identify individuals or households that may experience varying degrees of disadvantage in transportation accessibility and/or the transportation planning process:
    • Minority
    • Low-Income Households
    • Households Receiving Cash Public Assistance
    • Households Receiving Food Stamps
    • Carless Households
    • Disabled Populations
    • Elderly Populations
    • Female Heads of Household
    • Limited English Proficiency Households
    Transportation-Vulnerable Communities
    Using US Census Bureau’s 2017-2021 American Community Survey data, each transportation-vulnerability key indicator was assessed by census block groups, the smallest available geography for the identified key indicators, and compared to regional averages. Any census block group with an average key indicator equal to or higher than the regional average for that indicator is identified as a transportation-vulnerable community.

    The dataset contains the 9 EJ Indicators used for the HRTPO Title VI/EJ Analysis and the 2050 LRTP. The field names/aliases will change based on what platform the user is viewing the data (e.g., ArcMap, ArcPro, ArcGIS Online, Microsoft Excel, etc.). The suggestion is to view 'Field Alias Names'. To help preserve the field names and descriptions and to help the user understand the data, the following list contains the field names, field alias names, and field descriptions: (EXAMPLE: Field Name = Field Alias Name. Field Description.).

    OBJECTID = OBJECTID. Unique integer field used to identify rows in tables in a geodatabase uniquely. ESRI ArcMap/ArcPro automatically defines this field.

    Shape = Shape. The type of shape for the data. In this case, the EJ data are all 2021 Census Block Group (CBG) polygons. ESRI ArcMap/ArcPro automatically defines this field.

    GEOID = Census GEOID. Census numeric codes that uniquely identify all administrative/legal and statistical geographic areas. In this case, the EJ data are all 2021 CBGs.

    GEOID_1 = Census GEOID - Joined. Census numeric codes that uniquely identify all administrative/legal and statistical geographic areas. In this case, the EJ data are all 2021 CBGs.

    Block_Grou = Census Block Group. CBG is a geographical unit used by the U.S. Census Bureau which is between the Census Tract and the Census Block levels.

    TAZ = Transportation Analysis Zones (TAZ). HRTPO Transportation Analysis Zones (TAZs) that spatially join with the CBGs. Each CBG has a TAZ that intersects/overlays with the HRTPO TAZs.

    Locality = Locality. Locality name: the dataset includes 16 localities (Cities of Chesapeake, Franklin, Hampton, Newport News, Norfolk, Poquoson, Portsmouth, Suffolk, Virginia Beach, and Williamsburg, and the Counties of Gloucester, Isle of Wight, James City, Southampton, Surry*, and York). The HRTPO/MPO Boundary does not include Surry County, but the data is included for HRPDC/MPA purposes.

    Total_Popu = Total Population. Census Total Population.

    Total_Hous = Total Households. Census Total Households.

    Carless_To = Carless Total. Total Carless Households. Households with no vehicles available.

    Carless_Re = Carless regional Avg. Carless Households regional average.

    Carless_BG = Carless BG Avg. Carless Households Census Block Group average.

    Carless_AB = Carless Above Avg (Yes/No). Carless Households above the regional average. No = Not an EJ Community, Yes = EJ Community.

    Carless_Nu = Carless Numeric Value (0/1). Carless Households numerical value. 0 = Not an EJ Community, 1 = EJ Community.

    Cash_Assis = Cash Public Assistance Total. Total Households Receiving Cash Public Assistance (CPA). household that received either cash assistance or in-kind benefits.

    Cash_Ass_1 = Cash Public Assistance Regional Avg. CPA Households regional average.

    Cash_Ass_2 = Cash Public Assistance BG Avg. CPA Households Census Block Group average.

    Cash_Ass_3 = Cash Assistance Above Avg (Yes/No). CPA Households above the regional average. No = Not an EJ Community, Yes = EJ Community.

    CPA_Num = Cash Public Assistance Numeric Value (0/1). CPA Households numerical value. 0 = Not an EJ Community, 1 = EJ Community.

    Disability = Disability Total. Total Disabled Populations. non-institutionalized persons identified as having a disability of the following basic areas of functioning - hearing, vision, cognition, and ambulation.

    Disabili_1 = Disability Regional Avg. Disabled Populations regional average.

    Disabili_2 = Disability BG Average. Disabled Populations Census Block Group average.

    Disabili_3 = Disability Above Avg (Yes/No). Disabled Populations above the regional average. No = Not an EJ Community, Yes = EJ Community.

    Disabili_4 = Disability Numeric Value (0/1). Disabled Populations numerical value. 0 = Not an EJ Community, 1 = EJ Community.

    Elderly_To = Elderly Total. Total Elderly Populations. People who are aged 65 and older.

    Elderly_Re = Elderly Region Avg. Elderly Population regional average.

    Elderly_BG = Elderly BG Avg. Elderly Population Census Block Group avg.

    Elderly_Ab = Elderly Above Avg (Yes/No). Elderly Population above the regional average. No = Not an EJ Community, Yes = EJ Community.

    Elderly_Num = Elderly Numeric Value (0/1). Elderly Population numerical value. 0 = Not an EJ Community, 1 = EJ Community.

    Female_HoH = Female Head of Households Total. Total Female Head of Households. Households where females are the head of households with children present and no husband present.

    Female_H_1 = Female Head of Households Regional Avg. Female Head of Households regional average.

    Female_H_2 = Female Head of Households BG Avg. Female Head of Households Census Block Group average.

    Female_H_3 = Female Head of Households Above Avg (Yes/No). Female Head of Households above the regional average. No = Not an EJ Community, Yes = EJ Community.

    FemaleHoH_ = Female Head of Households Numeric Value (0/1). Female Head of Households numerical value. 0 = Not an EJ Community, 1 = EJ Community.

    Food_Stamp = Food Stamps Total. Total Households receiving Food Stamps. Households that received Supplemental Nutrition Assistance Program (SNAP) or Food Stamps.

    Food_Sta_1 = Food Stamps Region Avg. Food Stamps Households regional average.

    Food_Sta_2 = Food Stamps BG Avg. Food Stamps Households Census Block Group average.

    Food_Sta_3 = Food Stamps Above Avg (Yes/No). Food Stamps Households above the regional average. No = Not an EJ Community, Yes = EJ Community.

    FoodStamps = Food Stamps Numeric Value (0/1). Food Stamps Households numerical value. 0 = Not an EJ Community, 1 = EJ Community.

    Limited_En = Limited English Proficiency Total. Total Limited English

  7. International Food Security

    • agdatacommons.nal.usda.gov
    txt
    Updated Feb 8, 2024
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    US Department of Agriculture, Economic Research Service (2024). International Food Security [Dataset]. http://doi.org/10.15482/USDA.ADC/1299294
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    txtAvailable download formats
    Dataset updated
    Feb 8, 2024
    Dataset provided by
    Economic Research Servicehttp://www.ers.usda.gov/
    Authors
    US Department of Agriculture, Economic Research Service
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Description

    This dataset measures food availability and access for 76 low- and middle-income countries. The dataset includes annual country-level data on area, yield, production, nonfood use, trade, and consumption for grains and root and tuber crops (combined as R&T in the documentation tables), food aid, total value of imports and exports, gross domestic product, and population compiled from a variety of sources. This dataset is the basis for the International Food Security Assessment 2015-2025 released in June 2015. This annual ERS report projects food availability and access for 76 low- and middle-income countries over a 10-year period. Countries (Spatial Description, continued): Democratic Republic of the Congo, Ecuador, Egypt, El Salvador, Eritrea, Ethiopia, Gambia, Georgia, Ghana, Guatemala, Guinea, Guinea-Bissau, Haiti, Honduras, India, Indonesia, Jamaica, Kenya, Kyrgyzstan, Laos, Lesotho, Liberia, Madagascar, Malawi, Mali, Mauritania, Moldova, Mongolia, Morocco, Mozambique, Namibia, Nepal, Nicaragua, Niger, Nigeria, North Korea, Pakistan, Peru, Philippines, Rwanda, Senegal, Sierra Leone, Somalia, Sri Lanka, Sudan, Swaziland, Tajikistan, Tanzania, Togo, Tunisia, Turkmenistan, Uganda, Uzbekistan, Vietnam, Yemen, Zambia, and Zimbabwe. Resources in this dataset:Resource Title: CSV File for all years and all countries. File Name: gfa25.csvResource Title: International Food Security country data. File Name: GrainDemandProduction.xlsxResource Description: Excel files of individual country data. Please note that these files provide the data in a different layout from the CSV file. This version of the data files was updated 9-2-2021

    More up-to-date files may be found at: https://www.ers.usda.gov/data-products/international-food-security.aspx

  8. T

    American Community Survey 5 Year Estimates - City of Buffalo, NY

    • covid19.buffalony.gov
    Updated Apr 14, 2020
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    U. S. Census - American Community Survey (2020). American Community Survey 5 Year Estimates - City of Buffalo, NY [Dataset]. https://covid19.buffalony.gov/dataset/American-Community-Survey-5-Year-Estimates-City-of/cp4j-66dd
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    application/rdfxml, csv, tsv, xml, application/rssxml, application/geo+json, kml, kmzAvailable download formats
    Dataset updated
    Apr 14, 2020
    Dataset authored and provided by
    U. S. Census - American Community Survey
    Area covered
    Buffalo, New York
    Description

    Population over 60 (S0101), Women Who Had a Birth in the Past 12 Months (B13002), Below Poverty Level (B17015), No Health Insurance (B27001), Household Receiving SNAP Assistance (S2201), No Internet Access (B28002), Total Population (B01003) and Language at Home (C16001)

  9. Instagram: distribution of global audiences 2024, by age and gender

    • statista.com
    • davegsmith.com
    Updated Jun 17, 2025
    + more versions
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    Stacy Jo Dixon (2025). Instagram: distribution of global audiences 2024, by age and gender [Dataset]. https://www.statista.com/topics/1164/social-networks/
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    Dataset updated
    Jun 17, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Stacy Jo Dixon
    Description

    As of April 2024, around 16.5 percent of global active Instagram users were men between the ages of 18 and 24 years. More than half of the global Instagram population worldwide was aged 34 years or younger.

                  Teens and social media
    
                  As one of the biggest social networks worldwide, Instagram is especially popular with teenagers. As of fall 2020, the photo-sharing app ranked third in terms of preferred social network among teenagers in the United States, second to Snapchat and TikTok. Instagram was one of the most influential advertising channels among female Gen Z users when making purchasing decisions. Teens report feeling more confident, popular, and better about themselves when using social media, and less lonely, depressed and anxious.
                  Social media can have negative effects on teens, which is also much more pronounced on those with low emotional well-being. It was found that 35 percent of teenagers with low social-emotional well-being reported to have experienced cyber bullying when using social media, while in comparison only five percent of teenagers with high social-emotional well-being stated the same. As such, social media can have a big impact on already fragile states of mind.
    
  10. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2022). ‘District Resource Statement - SNAP Population’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-district-resource-statement-snap-population-15a4/59c59309/?iid=003-718&v=presentation

‘District Resource Statement - SNAP Population’ analyzed by Analyst-2

Explore at:
Dataset updated
Jan 26, 2022
Dataset authored and provided by
Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

Analysis of ‘District Resource Statement - SNAP Population’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/4ef4a33e-02ab-4923-a148-6f6cfb57d4dc on 26 January 2022.

--- Dataset description provided by original source is as follows ---

Population of individuals and households receiving SNAP Benefits. For a complete list of District Resource Statement datasets,please follow this link.

--- Original source retains full ownership of the source dataset ---

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