AndreaBozzo/ceres-open-data-index huggingface dataset:
Quarterly House Price Index for Large Metropolitan Areas

This dataset contains the quarterly house price index for the 100 largest metropolitan areas in the U.S. from 1991 to present. The HPI is determined by the Federal Housing Finance Agency (FHFA). According to the FHFA, the HPI is a weighted, repeat-sales index, meaning that it measures average price changes in repeat sales or refinancings on the same properties. In addition to the quarterly HPI, this dataset includes the quarter-to-quarter percent change and the quarterly year-over-year (YoY) percent change in the HPI.
Quarterly Census of Employment & Wages

This dataset is derived from the Quarterly Census of Employment & Wages (QCEW) from the U.S. Bureau of Labor Statistics for Fulton County, the Atlanta MSA and the U.S. The dataset includes QCEW data aggregated down to the NAICS Sector (e.g. NAICS 23 Construction, NAICS 31-33 Manufacturing). Information on each quarter, geographic area and industry include total employment, total number of establishments and average wages.
Public Transportation Usage for Travel to Work by U.S. County

This dataset contains the percentage of workers 16 years and older in each U.S. county with a population of 65,000 or more who reports using public transportation as their principal mode of transportation from home to work. Annual numbers are provided for the years beginning with 2010 and ending with the most recent year for which data area available. The source of the data is the U.S. Census Bureau's American Community Survey, 1-Year Estimates, Table S0801.
Average Daily Maximum Temperatures with Projections

This dataset consists of observed, modeled historic and modeled projected average daily maximum temperatures for Fulton County for the years 1950 to 2099. The source of the data is the U.S. Climate Resilience Toolkit Climate Explorer (https://crt-climate-explorer.nemac.org/). Additional details can be found at https://crt-climate-explorer.nemac.org/about/.
Advance Voters by Voting Location, August 11, 2020 Runoff Election

This dataset contains the cumulative number of people who voted at each Fulton County advance voting location for the August 11, 2020 runoff election. It was derived from the Voter Absentee File produced by the Georgia Secretary of State and made available at https://elections.sos.ga.gov/Elections/voterabsenteefile.do.
Vendor Payments

This dataset consists of a listing of payments made to Fulton County vendors for poducts and services provided to the County. The payment records span the period from January 1, 2014 to present. Included with each payment record is the disbursement date, the department making the payment, the type of service or product, the fund from which the payment is drawn, the payment amount and the name of the vendor to which the payment was made. This dataset is updated weekly.
U.S. County Populations (>65,000)

The data contains the total population for U.S. counties with a population of over 65,000 as reported in the U.S. Census American Community Survey 1-year Summary (B01001_001). Data will generally reflect the latest survey data available. Additional information includes fields with True/False flags indicating whether the county has a population over 1 million and half a million and whether the (Georgia) county is part of the Atlanta metropolitan statistical area, part of the core metropolitan area, a member of the Atlanta Regional Commission or part of the Metropolitan North Georgia Water Planning District.
Trips by Distance

This dataset is sourced from the U.S. Department of Transportation Bureau of Transportation Statistics. All data and metadata is sourced from the page linked below. Metadata is not updated automatically; data updates weekly. Source Data Link: https://data.bts.gov/Research-and-Statistics/Trips-by-Distance/w96p-f2qv How many people are staying at home? How far are people traveling when they don’t stay home? Which states and counties have more people taking trips? The Bureau of Transportation Statistics (BTS) now provides answers to those questions through our new mobility statistics. The Trips by Distance data and number of people staying home and not staying home are estimated for the Bureau of Transportation Statistics by the Maryland Transportation Institute and Center for Advanced Transportation Technology Laboratory at the University of Maryland. The travel statistics are produced from an anonymized national panel of mobile device data from multiple sources. All data sources used in the creation of the metrics contain no personal information. Data analysis is conducted at the aggregate national, state, and county levels. A weighting procedure expands the sample of millions of mobile devices, so the results are representative of the entire population in a nation, state, or county. To assure confidentiality and support data quality, no data are reported for a county if it has fewer than 50 devices in the sample on any given day. Trips are defined as movements that include a stay of longer than 10 minutes at an anonymized location away from home. Home locations are imputed on a weekly basis. A movement with multiple stays of longer than 10 minutes before returning home is counted as multiple trips. Trips capture travel by all modes of transportation. including driving, rail, transit, and air. The daily travel estimates are from a mobile device data panel from merged multiple data sources that address the geographic and temporal sample variation issues often observed in a single data source. The merged data panel only includes mobile devices whose anonymized location data meet a set of data quality standards, which further ensures the overall data quality and consistency. The data quality standards consider both temporal frequency and spatial accuracy of anonymized location point observations, temporal coverage and representativeness at the device level, spatial representativeness at the sample and county level, etc. A multi-level weighting method that employs both device and trip-level weights expands the sample to the underlying population at the county and state levels, before travel statistics are computed. These data are experimental and may not meet all of our quality standards. Experimental data products are created using new data sources or methodologies that benefit data users in the absence of other relevant products. We are seeking feedback from data users and stakeholders on the quality and usefulness of these new products. Experimental data products that meet our quality standards and demonstrate sufficient user demand may enter regular production if resources permit.
Superior Court, Pending Cases per Month

This dataset contains a monthly record of how many cases each judge had pending at the end of the month, as well as the average number of pending cases among judges. The average pending is calculated by group, so the average for non-complex is different than the average among the judges handling complex criminal cases. There is one data point for the number of cases pending on the last day of each previous month, starting 2019-01-01, and a datapoint for the current number of pending cases.
Superior Court, Cases Pending Over 1 Year, Per Month

This dataset contains a monthly record of how many cases pending over a year each judge had at the end of the month, as well as the average number of pending cases over one year among judges. The average pending is calculated by group, so the average for non-complex is different than the average among the judges handling complex criminal cases. There is one data point for the last day of each previous month, starting 2019-01-01, and a datapoint for the current number of pending cases over one year.
Superior Court Case Assignments

This dataset consists of assignments of all civil, criminal, business, and family court cases in the Fulton County Superior Court, from 1992-01-01 to present. Information provided on each case includes the case number, case type (e.g., non-complex felony, capital felony), the date filed, the date assigned, the judge assigned, the current status (e.g. open, closed), and flags indicating whether the defendant is in jail and whether the assignment is current (or the last assignment in the case of closed cases).
Semi-Annual Real Wages for Fulton County, Metro Atlanta and U.S.

This dataset contains the average real wages for Fulton County, metro Atlanta and the U.S. calculated semi-annually. Real wages represent actual (nominal) wages adjusted for inflation using the Consumer Price Index (CPI). Real wages are expressed in terms of 1982-1984 dollars. Semi-annual numbers are used because local area wages are reported by the Bureau of Labor Statistics (BLS) quarterly and CPI is reported every two months; therefore, reporting periods coincide twice a year. Real wages are reported as moving 12-month averages in order to better illustrate the general trend over time. Nominal wages and CPI are from the BLS; semi-annual real wages are calculated by the Fulton County Strategy & Performance Management Office.
Small Area Fair Market Rents - Metro Atlanta

This dataset consists of the small area fair market rents (FMRs) published annually by the U.S. Department of Housing and Urban Development (HUD). Small areas correspond to zip codes. The FMRs in this dataset are confined to the Atlanta metro area and include FMRs for the most recent year, the previous year and four years ago along with the percent change between those years. Small Area FMRs are required to be used to set Section 8 Housing Choice Voucher payment standards in areas designated by HUD. Additional information can be found at https://www.huduser.gov/portal/datasets/fmr/smallarea/index.html.
National Transit Database - Monthly Unlinked Passenger Trips

This dataset is one component of the National Transit Database (NTD). The NTD records the financial, operating, and asset condition of transit systems helping to keep track of the industry and provide public information and statistics. This dataset includes only monthly unlinked passenger trips for each urban transit system in the U.S. Transit systems are separated by type (mode) such as heavy rail, light rail, and bus. "Unlinked passenger trips" represents the number of passengers who board public transportation vehicles. Passengers are counted each time they board vehicles no matter how many vehicles they use to travel from their origin to their destination. More information about the NTD is available at https://www.transit.dot.gov/ntd.
Monthly Operational Metrics for U.S. Public Transit Systems

Beginning with Calendar Year 2012, the bottom of each monthly data worksheet (UPT, VRM, VRH, VOMS) presents estimated monthly industry totals for Reduced Reporters (agencies operating fewer than 30 vehicles in maximum service). These agencies do not report data to the Monthly Ridership module effective in 2012. Estimates are calculated by dividing the annual service data values reported on the Reduced Reporting (RR-20) forms for the previous Annual Report year by 12. Estimated VOMS is presented as the actual VOMS reported on the most recent annual RR-20 form. Any values entered by agencies with Reduced Reporting Waivers during CY 2012 are removed to prevent double-counting values. · A Master File of all properties that currently report or reported monthly data during the period January 2002 - Current Calendar Year. The following data elements are included in the master file and reflect the data reported in the Annual module for the most recently reported fiscal year:
SC All Judges, Total Defendants in Jail

This dataset contains a monthly record of how many defendants are in jail on Superior Court Criminal cases. It counts each defendant in jail once, using the dataset https://sharefulton.fultoncountyga.gov/Government/Superior-Court-Defendants-in-Jail/raqb-js7j. This data contains the current days count, as well as one datapoint from the last day of each previous month, starting 2019-01-01.
Monthly Building Permit Counts

This dataset contains counts of permits for privately-owned residential construction issued by local jurisdictions in the U.S. summarized by county. Permits are categorized by number of units within the building: 1 unit (single-family), 2 units (duplex), 3-4 units (tri-/quadra-plex), and 5+ units (apartment). Permit counts are given as both reported and imputed.
Firearm Homicides by U.S. County

This dataset contains the crude number, crude rate and age-adjusted rate of firearm homicides for each U.S. county. Numbers for many counties are suppressed due to low numbers of homicides and others are flagged as unstable due to large margins of error. The CDC updates numbers annually; however, there is generally an 18 month delay in making the numbers for a given year publicly available. The homicide counts originate from death certificates from local coroner and medical examiner offices. More information is available at https://www.cdc.gov/injury/wisqars/index.html.
Country of Origin for Foreign-Born Fulton County Residents - 2010, 2020

This dataset consists of the number of foreign-born Fulton County residents by country of birth. Counts are included for the 2020 American Community Survey (ACS) and for the 2010 ACS as a reference for showing trends over time. The data are derived from Table B05002 (PLACE OF BIRTH BY NATIVITY AND CITIZENSHIP STATUS).
City of Atlanta Crime Incidents

This dataset contains a listing of crime incidents reported by the Atlanta Police Department (APD) since 2009. It is based on incident-level data compiled from files released publicly by the ATP at https://www.atlantapd.org/i-want-to/crime-data-downloads. The data include the date the incident was reported and the date the incident occurred, the type of crime (based on the Uniform Crime Reporting classification), the nearest address and the latitude and longitude of the incident.
Bi-Monthly Consumer Price Index for Atlanta Metro - Wide Format

This dataset contains the consumer price index (CPI) over time for the Atlanta Metropolitan Statistical Area (MSA). The CPI is given for all goods and services combined as well for individual classes such as energy, housing, transportation and food. The 2-month change and year-over-year change in CPI is also included. This dataset is in a wide format with the metrics for each category of consumer item in a separate column.