Analysis of ‘US Public Food Assistance’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/jpmiller/publicassistance on 13 February 2022.

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

Context

This dataset focuses on public assistance programs in the United States that provide food, namely SNAP and WIC. If you are interested in a broader picture of food security across the world, please see Food Security Indicators for the World 2016-2020.

Initial coverage was for the Special Supplemental Nutrition Program for Women, Infants, and Children Program, or simply WIC. The program allocates Federal and State funds to help low-income women and children up to age five who are at nutritional risk. Funds are used to provide supplemental foods, baby formula, health care, and nutrition education.

Starting with version 5, the dataset also covers the US Supplemental Nutrition Assistance Program, more commonly known as SNAP. The program is the successor to the Food Stamps program previously in place. The program provides food assistance to low-income families in the form of a debit card. A 2016 study using POS data from SNAP-eligible vendors showed the three most purchased types of food to be meats, sweetened beverages, and vegetables.

Content

Files may include participation data and spending for state programs, and poverty data for each state. Data for WIC covers fiscal years 2013-2016, which is actually October 2012 through September 2016. Data for SNAP covers 2015 to 2020.

Motivation

My original purpose here is two-fold:

• Explore various aspects of US Public Assistance. Show trends over recent years and better understand differences across state agencies. Although the federal government sponsors the program and provides funding, program are administered at the state level and can widely vary. Indian nations (native Americans) also administer their own programs.

• Share with the Kaggle Community the joy - and pain - of working with government data. Data is often spread across numerous agency sites and comes in a variety of formats. Often the data is provided in Excel, with the files consisting of multiple tabs. Also, files are formatted as reports and contain aggregated data (sums, averages, etc.) along with base data.

As of March 2nd, I am expanding the purpose to support the M5 Forecasting Challenges here on Kaggle. Store sales are partly driven by participation in Public Assistance programs. Participants typically receive the items free of charge. The store then recovers the sale price from the state agencies administering the program.

Additional Content Ideas

The dataset can benefit greatly from additional content. Economics, additional demographics, administrative costs and more. I'd like to eventually explore the money trail from taxes and corporate subsidies, through the government agencies, and on to program participants. All community ideas are welcome!

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

The Supplemental Nutrition Assistance Program (SNAP) is the largest of the domestic nutrition assistance programs administered by the Food and Nutrition Service (FNS) of the U.S. Department of Agriculture (USDA), providing millions of Americans with the means to purchase food for a nutritious diet. During fiscal year (FY) 2020, SNAP served an average of 39.9 million people monthly and paid out $74.2 billion in benefits, which includes the cost of emergency allotments to supplement SNAP benefits due to the COVID-19 public health emergency. In response to legislative adjustments to program rules and changes in economic and demographic trends, the characteristics of SNAP participants and households and the size of the SNAP caseload change over time. To quantify these changes or estimate the effect of adjustments to program rules on the current SNAP caseload, FNS relies on data from the SNAP Quality Control (QC) database. This database is an edited version of the raw data file of monthly case reviews conducted by State SNAP agencies to assess the accuracy of eligibility determinations and benefit calculations for each State’s SNAP caseload. The COVID-19 public health emergency resulted in an incomplete FY 2020 sample in the raw data file. FNS granted States temporary waivers on conducting QC reviews starting in March 2020. Very few States collected QC data from March 2020 through May 2020. Most States opted to conduct QC reviews from June 2020 through September 2020, although FNS was unable to provide its usual level of oversight of the sampling procedures. Furthermore, monthly State samples for this time period were often smaller than usual. This dataset includes separate SNAP QC files for FY 2020. The first covers the “pre-pandemic” period of October 2019 through February 2020. The second covers the “waiver” period of June 2020 through September 2020 for the 47 States and territories that provided sufficient data for at least one of those months. Resources in this dataset:Resource Title: Fiscal Year 2020 Supplemental Nutrition Assistance Program Quality Control Database (Period 2). File Name: qc_pub_fy2020_per2.csvResource Description: The Supplemental Nutrition Assistance Program (SNAP) is the largest of the domestic nutrition assistance programs administered by the Food and Nutrition Service (FNS) of the U.S. Department of Agriculture (USDA), providing millions of Americans with the means to purchase food for a nutritious diet. During fiscal year (FY) 2020, SNAP served an average of 39.9 million people monthly and paid out $74.2 billion in benefits, which includes the cost of emergency allotments to supplement SNAP benefits due to the COVID-19 public health emergency. In response to legislative adjustments to program rules and changes in economic and demographic trends, the characteristics of SNAP participants and households and the size of the SNAP caseload change over time. To quantify these changes or estimate the effect of adjustments to program rules on the current SNAP caseload, FNS relies on data from the SNAP Quality Control (QC) database. This database is an edited version of the raw data file of monthly case reviews conducted by State SNAP agencies to assess the accuracy of eligibility determinations and benefit calculations for each State’s SNAP caseload.

The COVID-19 public health emergency resulted in an incomplete FY 2020 sample in the raw data file. FNS granted States temporary waivers on conducting QC reviews starting in March 2020. Very few States collected QC data from March 2020 through May 2020. Most States opted to conduct QC reviews from June 2020 through September 2020, although FNS was unable to provide its usual level of oversight of the sampling procedures. Furthermore, monthly State samples for this time period were often smaller than usual.

There are separate SNAP QC databases for FY 2020. The first covers the “pre-pandemic” period of October 2019 through February 2020. The second covers the “waiver” period of June 2020 through September 2020 for the 47 States and territories that provided sufficient data for at least one of those months.Resource Title: Fiscal Year 2020 Supplemental Nutrition Assistance Program Quality Control Database (Period 1). File Name: qc_pub_fy2020_per1.csvResource Description: The Supplemental Nutrition Assistance Program (SNAP) is the largest of the domestic nutrition assistance programs administered by the Food and Nutrition Service (FNS) of the U.S. Department of Agriculture (USDA), providing millions of Americans with the means to purchase food for a nutritious diet. During fiscal year (FY) 2020, SNAP served an average of 39.9 million people monthly and paid out $74.2 billion in benefits, which includes the cost of emergency allotments to supplement SNAP benefits due to the COVID-19 public health emergency. In response to legislative adjustments to program rules and changes in economic and demographic trends, the characteristics of SNAP participants and households and the size of the SNAP caseload change over time. To quantify these changes or estimate the effect of adjustments to program rules on the current SNAP caseload, FNS relies on data from the SNAP Quality Control (QC) database. This database is an edited version of the raw data file of monthly case reviews conducted by State SNAP agencies to assess the accuracy of eligibility determinations and benefit calculations for each State’s SNAP caseload.

The COVID-19 public health emergency resulted in an incomplete FY 2020 sample in the raw data file. FNS granted States temporary waivers on conducting QC reviews starting in March 2020. Very few States collected QC data from March 2020 through May 2020. Most States opted to conduct QC reviews from June 2020 through September 2020, although FNS was unable to provide its usual level of oversight of the sampling procedures. Furthermore, monthly State samples for this time period were often smaller than usual.

There are separate SNAP QC databases for FY 2020. The first covers the “pre-pandemic” period of October 2019 through February 2020. The second covers the “waiver” period of June 2020 through September 2020 for the 47 States and territories that provided sufficient data for at least one of those months.Resource Title: Technical Documentation for the Fiscal Year 2020 Supplemental Nutrition Assistance Program Quality Control Database and the QC Minimodel. File Name: FY2020TechDoc.pdfResource Description: The Supplemental Nutrition Assistance Program (SNAP) is the largest of the domestic nutrition assistance programs administered by the Food and Nutrition Service (FNS) of the U.S. Department of Agriculture (USDA), providing millions of Americans with the means to purchase food for a nutritious diet. During fiscal year (FY) 2020, SNAP served an average of 39.9 million people monthly and paid out $74.2 billion in benefits, which includes the cost of emergency allotments to supplement SNAP benefits due to the COVID-19 public health emergency. In response to legislative adjustments to program rules and changes in economic and demographic trends, the characteristics of SNAP participants and households and the size of the SNAP caseload change over time. To quantify these changes or estimate the effect of adjustments to program rules on the current SNAP caseload, FNS relies on data from the SNAP Quality Control (QC) database. This database is an edited version of the raw data file of monthly case reviews conducted by State SNAP agencies to assess the accuracy of eligibility determinations and benefit calculations for each State’s SNAP caseload.

The COVID-19 public health emergency resulted in an incomplete FY 2020 sample in the raw data file. FNS granted States temporary waivers on conducting QC reviews starting in March 2020. Very few States collected QC data from March 2020 through May 2020. Most States opted to conduct QC reviews from June 2020 through September 2020, although FNS was unable to provide its usual level of oversight of the sampling procedures. Furthermore, monthly State samples for this time period were often smaller than usual.

There are separate SNAP QC databases for FY 2020. The first covers the “pre-pandemic” period of October 2019 through February 2020. The second covers the “waiver” period of June 2020 through September 2020 for the 47 States and territories that provided sufficient data for at least one of those months.

"ForeignAssistance.gov is the U.S. government’s flagship website for making U.S. foreign assistance data available to the public. It serves as the central resource for budgetary and financial data produced by U.S. government agencies that manage foreign assistance portfolios. In keeping with the U.S. government’s commitment to transparency, ForeignAssistance.gov presents a picture of U.S. foreign assistance in accurate and understandable terms. The website also includes links to associated strategies and evaluations for U.S. foreign assistance programs. This site will be continually updated as data are available. Look for new features and enhancements as they come online.The primary objective of the site is to fulfill the requirements set forth in the Foreign Aid Transparency and Accountability Act of 2016 (FATAA) through the collection, tracking, and publication of the full lifecycle of all USG foreign assistance data." Retrieved 2/20/25 from https://foreignassistance.gov/aboutContents US International Development Finance Corporation - usdfc_ActiveProjects.xlsx The Active Projects database reflects active DFC commitments as of the most recent quarter. The database is updated approximately 45 days after the end of each quarter. Last updated 9/30/24https://www.dfc.gov/what-we-do/active-projects Data from ForeignAssistance.gov Last updated on: 12/19/2024https://foreignassistance.gov/data#tab-data-download The complete ForeignAssistance.gov dataset: us_foreign_aid_complete.csv Budget Dataset - The complete foreign aid budget dataset: President's Budget Request, initial allocations, and final allocations. us_foreign_budget_complete.csv Country Summary - These tables offer a summary of obligations and disbursements in current and constant dollars by country from 1946 to the most recent year. us_foreign_aid_country.csv OECD/DAC Sector Summary These tables offer a summary of obligations and disbursements by OECD/DAC sector and sector category from 2001 to the most recent year. us_foreign_aid_dac_sector.csv USG Sector Summary These tables offer a summary of obligations and disbursements in current and constant dollars by U.S. Government (USG) sector and country from 2001 to the most recent year. us_foreign_aid_usg_sector.csv Managing Agency Summary These tables offer a summary of obligations and disbursements in current and constant dollars by managing agency and country from 2001 to the most recent year. us_foreign_aid_implementing.csv Funding Agency Summary These tables offer a summary of obligations and disbursements in current and constant dollars by funding agency, funding account, and country from 2001 to the most recent year. us_foreign_aid_usg_funding.csv Data Dictionary A table with information describing the contents and structure of the U.S. ForeignAssistance.gov data fields. DataDictionary_ForeignAssistancegov.pdf

The Current Population Survey Food Security Supplement (CPS-FSS) is the source of national and State-level statistics on food insecurity used in USDA's annual reports on household food security. The CPS is a monthly labor force survey of about 50,000 households conducted by the Census Bureau for the Bureau of Labor Statistics. Once each year, after answering the labor force questions, the same households are asked a series of questions (the Food Security Supplement) about food security, food expenditures, and use of food and nutrition assistance programs. Food security data have been collected by the CPS-FSS each year since 1995. Four data sets that complement those available from the Census Bureau are available for download on the ERS website. These are available as ASCII uncompressed or zipped files. The purpose and appropriate use of these additional data files are described below: 1) CPS 1995 Revised Food Security Status data--This file provides household food security scores and food security status categories that are consistent with procedures and variable naming conventions introduced in 1996. This includes the "common screen" variables to facilitate comparisons of prevalence rates across years. This file must be matched to the 1995 CPS Food Security Supplement public-use data file. 2) CPS 1998 Children's and 30-day Food Security data--Subsequent to the release of the April 1999 CPS-FSS public-use data file, USDA developed two additional food security scales to describe aspects of food security conditions in interviewed households not captured by the 12-month household food security scale. This file provides three food security variables (categorical, raw score, and scale score) for each of these scales along with household identification variables to allow the user to match this supplementary data file to the CPS-FSS April 1998 data file. 3) CPS 1999 Children's and 30-day Food Security data--Subsequent to the release of the April 1999 CPS-FSS public-use data file, USDA developed two additional food security scales to describe aspects of food security conditions in interviewed households not captured by the 12-month household food security scale. This file provides three food security variables (categorical, raw score, and scale score) for each of these scales along with household identification variables to allow the user to match this supplementary data file to the CPS-FSS April 1999 data file. 4) CPS 2000 30-day Food Security data--Subsequent to the release of the September 2000 CPS-FSS public-use data file, USDA developed a revised 30-day CPS Food Security Scale. This file provides three food security variables (categorical, raw score, and scale score) for the 30-day scale along with household identification variables to allow the user to match this supplementary data file to the CPS-FSS September 2000 data file. Food security is measured at the household level in three categories: food secure, low food security and very low food security. Each category is measured by a total count and as a percent of the total population. Categories and measurements are broken down further based on the following demographic characteristics: household composition, race/ethnicity, metro/nonmetro area of residence, and geographic region. The food security scale includes questions about households and their ability to purchase enough food and balanced meals, questions about adult meals and their size, frequency skipped, weight lost, days gone without eating, questions about children meals, including diversity, balanced meals, size of meals, skipped meals and hunger. Questions are also asked about the use of public assistance and supplemental food assistance. The food security scale is 18 items that measure insecurity. A score of 0-2 means a house is food secure, from 3-7 indicates low food security, and 8-18 means very low food security. The scale and the data also report the frequency with which each item is experienced. Data are available as .dat files which may be processed in statistical software or through the United State Census Bureau's DataFerret http://dataferrett.census.gov/. Data from 2010 onwards is available below and online. Data from 1995-2009 must be accessed through DataFerrett. DataFerrett is a data analysis and extraction tool to customize federal, state, and local data to suit your requirements. Through DataFerrett, the user can develop an unlimited array of customized spreadsheets that are as versatile and complex as your usage demands then turn those spreadsheets into graphs and maps without any additional software. Resources in this dataset:Resource Title: December 2014 Food Security CPS Supplement. File Name: dec14pub.zipResource Title: December 2013 Food Security CPS Supplement. File Name: dec13pub.zipResource Title: December 2012 Food Security CPS Supplement. File Name: dec12pub.zipResource Title: December 2011 Food Security CPS Supplement. File Name: dec11pub.zipResource Title: December 2010 Food Security CPS Supplement. File Name: dec10pub.zip

WARNING: This is a pre-release dataset and its fields names and data structures are subject to change. It should be considered pre-release until the end of 2024. Expected changes:Metadata is missing or incomplete for some layers at this time and will be continuously improved.We expect to update this layer roughly in line with CDTFA at some point, but will increase the update cadence over time as we are able to automate the final pieces of the process.This dataset is continuously updated as the source data from CDTFA is updated, as often as many times a month. If you require unchanging point-in-time data, export a copy for your own use rather than using the service directly in your applications.PurposeCounty and incorporated place (city) boundaries along with third party identifiers used to join in external data. Boundaries are from the authoritative source the California Department of Tax and Fee Administration (CDTFA), altered to show the counties as one polygon. This layer displays the city polygons on top of the County polygons so the area isn"t interrupted. The GEOID attribute information is added from the US Census. GEOID is based on merged State and County FIPS codes for the Counties. Abbreviations for Counties and Cities were added from Caltrans Division of Local Assistance (DLA) data. Place Type was populated with information extracted from the Census. Names and IDs from the US Board on Geographic Names (BGN), the authoritative source of place names as published in the Geographic Name Information System (GNIS), are attached as well. Finally, coastal buffers are removed, leaving the land-based portions of jurisdictions. This feature layer is for public use.Related LayersThis dataset is part of a grouping of many datasets:Cities: Only the city boundaries and attributes, without any unincorporated areasWith Coastal BuffersWithout Coastal BuffersCounties: Full county boundaries and attributes, including all cities within as a single polygonWith Coastal BuffersWithout Coastal BuffersCities and Full Counties: A merge of the other two layers, so polygons overlap within city boundaries. Some customers require this behavior, so we provide it as a separate service.With Coastal BuffersWithout Coastal Buffers (this dataset)Place AbbreviationsUnincorporated Areas (Coming Soon)Census Designated Places (Coming Soon)Cartographic CoastlinePolygonLine source (Coming Soon)Working with Coastal BuffersThe dataset you are currently viewing includes the coastal buffers for cities and counties that have them in the authoritative source data from CDTFA. In the versions where they are included, they remain as a second polygon on cities or counties that have them, with all the same identifiers, and a value in the COASTAL field indicating if it"s an ocean or a bay buffer. If you wish to have a single polygon per jurisdiction that includes the coastal buffers, you can run a Dissolve on the version that has the coastal buffers on all the fields except COASTAL, Area_SqMi, Shape_Area, and Shape_Length to get a version with the correct identifiers.Point of ContactCalifornia Department of Technology, Office of Digital Services, odsdataservices@state.ca.govField and Abbreviation DefinitionsCOPRI: county number followed by the 3-digit city primary number used in the Board of Equalization"s 6-digit tax rate area numbering systemPlace Name: CDTFA incorporated (city) or county nameCounty: CDTFA county name. For counties, this will be the name of the polygon itself. For cities, it is the name of the county the city polygon is within.Legal Place Name: Board on Geographic Names authorized nomenclature for area names published in the Geographic Name Information SystemGNIS_ID: The numeric identifier from the Board on Geographic Names that can be used to join these boundaries to other datasets utilizing this identifier.GEOID: numeric geographic identifiers from the US Census Bureau Place Type: Board on Geographic Names authorized nomenclature for boundary type published in the Geographic Name Information SystemPlace Abbr: CalTrans Division of Local Assistance abbreviations of incorporated area namesCNTY Abbr: CalTrans Division of Local Assistance abbreviations of county namesArea_SqMi: The area of the administrative unit (city or county) in square miles, calculated in EPSG 3310 California Teale Albers.COASTAL: Indicates if the polygon is a coastal buffer. Null for land polygons. Additional values include "ocean" and "bay".GlobalID: While all of the layers we provide in this dataset include a GlobalID field with unique values, we do not recommend you make any use of it. The GlobalID field exists to support offline sync, but is not persistent, so data keyed to it will be orphaned at our next update. Use one of the other persistent identifiers, such as GNIS_ID or GEOID instead.AccuracyCDTFA"s source data notes the following about accuracy:City boundary changes and county boundary line adjustments filed with the Board of Equalization per Government Code 54900. This GIS layer contains the boundaries of the unincorporated county and incorporated cities within the state of California. The initial dataset was created in March of 2015 and was based on the State Board of Equalization tax rate area boundaries. As of April 1, 2024, the maintenance of this dataset is provided by the California Department of Tax and Fee Administration for the purpose of determining sales and use tax rates. The boundaries are continuously being revised to align with aerial imagery when areas of conflict are discovered between the original boundary provided by the California State Board of Equalization and the boundary made publicly available by local, state, and federal government. Some differences may occur between actual recorded boundaries and the boundaries used for sales and use tax purposes. The boundaries in this map are representations of taxing jurisdictions for the purpose of determining sales and use tax rates and should not be used to determine precise city or county boundary line locations. COUNTY = county name; CITY = city name or unincorporated territory; COPRI = county number followed by the 3-digit city primary number used in the California State Board of Equalization"s 6-digit tax rate area numbering system (for the purpose of this map, unincorporated areas are assigned 000 to indicate that the area is not within a city).Boundary ProcessingThese data make a structural change from the source data. While the full boundaries provided by CDTFA include coastal buffers of varying sizes, many users need boundaries to end at the shoreline of the ocean or a bay. As a result, after examining existing city and county boundary layers, these datasets provide a coastline cut generally along the ocean facing coastline. For county boundaries in northern California, the cut runs near the Golden Gate Bridge, while for cities, we cut along the bay shoreline and into the edge of the Delta at the boundaries of Solano, Contra Costa, and Sacramento counties.In the services linked above, the versions that include the coastal buffers contain them as a second (or third) polygon for the city or county, with the value in the COASTAL field set to whether it"s a bay or ocean polygon. These can be processed back into a single polygon by dissolving on all the fields you wish to keep, since the attributes, other than the COASTAL field and geometry attributes (like areas) remain the same between the polygons for this purpose.SliversIn cases where a city or county"s boundary ends near a coastline, our coastline data may cross back and forth many times while roughly paralleling the jurisdiction"s boundary, resulting in many polygon slivers. We post-process the data to remove these slivers using a city/county boundary priority algorithm. That is, when the data run parallel to each other, we discard the coastline cut and keep the CDTFA-provided boundary, even if it extends into the ocean a small amount. This processing supports consistent boundaries for Fort Bragg, Point Arena, San Francisco, Pacifica, Half Moon Bay, and Capitola, in addition to others. More information on this algorithm will be provided soon.Coastline CaveatsSome cities have buffers extending into water bodies that we do not cut at the shoreline. These include South Lake Tahoe and Folsom, which extend into neighboring lakes, and San Diego and surrounding cities that extend into San Diego Bay, which our shoreline encloses. If you have feedback on the exclusion of these items, or others, from the shoreline cuts, please reach out using the contact information above.Offline UseThis service is fully enabled for sync and export using Esri Field Maps or other similar tools. Importantly, the GlobalID field exists only to support that use case and should not be used for any other purpose (see note in field descriptions).Updates and Date of ProcessingConcurrent with CDTFA updates, approximately every two weeks, Last Processed: 12/17/2024 by Nick Santos using code path at https://github.com/CDT-ODS-DevSecOps/cdt-ods-gis-city-county/ at commit 0bf269d24464c14c9cf4f7dea876aa562984db63. It incorporates updates from CDTFA as of 12/12/2024. Future updates will include improvements to metadata and update frequency.

The Coronavirus State and Local Fiscal Recovery Funds program, as part of the American Rescue Plan Act delivers financial assistance to state, local, and Tribal governments across the country to support their response to and recovery from the COVID-19 public health emergency. The American Rescue Plan Act, or ARPA, was one of the largest recovery responses taken by the federal government and passed by Congress on March 11, 2021. The City of Phoenix received an allocation of $396 million and funds were delivered in two tranches over two years. On June 8, 2021, the Phoenix City Council approved the first tranche strategic plan and on June 7, 2022, Phoenix City Council approved the second tranche strategic plan. This dataset provides the funding types and amounts invested in the community and city operations.

The NOAA National Centers for Environmental Information ceased providing support for this product in May 2025 in response to an initiative to implement reductions within the U.S. federal government. This dataset contains U.S. disaster cost assessments of the total, direct losses ($) inflicted by: tropical cyclones, inland floods, drought & heat waves, severe local storms (i.e., tornado, hail, straight-line wind damage), wildfires, crop freeze events and winter storms. These assessments require input from a variety of public and private data sources including: the Insurance Services Office (ISO) Property Claim Services (PCS), Federal Emergency Management Agency (FEMA) National Flood Insurance Program (NFIP) and Presidential Disaster Declaration (PDD) assistance, and the United States Department of Agriculture (USDA) National Agricultural Statistics Service (NASS) & Risk Management Agency (RMA), the National Interagency Fire Center (NIFC) and state agency reporting, among others. Each of these data sources provides unique information as part of the overall disaster loss assessment.