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Easily lookup US historical demographics by county FIPS or zipcode in seconds with this file containing over 5,901 different columns including:
*Lat/Long *Boundaries *State FIPS *Population from 2010-2019 *Death Rate from 2010-2019 *Unemployment from 2001-2020 *Education from 1970-2019 *Gender and Age Population
Provided by bitrook.com to help Data Scientists clean data faster.
https://www.ers.usda.gov/data-products/county-level-data-sets/download-data/
https://www.ers.usda.gov/data-products/county-level-data-sets/download-data/
https://www.ers.usda.gov/data-products/county-level-data-sets/download-data/
https://data.world/niccolley/us-zipcode-to-county-state
https://www2.census.gov/programs-surveys/popest/datasets/2010-2019/counties/asrh/cc-est2019-agesex-**.csv https://www2.census.gov/programs-surveys/popest/technical-documentation/file-layouts/2010-2019/cc-est2019-agesex.pdf
https://www2.census.gov/programs-surveys/popest/datasets/2010-2019/counties/asrh/cc-est2019-alldata.csv https://www2.census.gov/programs-surveys/popest/technical-documentation/file-layouts/2010-2019/cc-est2019-alldata.pdf
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TwitterThe Bureau of the Census has released Census 2000 Summary File 1 (SF1) 100-Percent data. The file includes the following population items: sex, age, race, Hispanic or Latino origin, household relationship, and household and family characteristics. Housing items include occupancy status and tenure (whether the unit is owner or renter occupied). SF1 does not include information on incomes, poverty status, overcrowded housing or age of housing. These topics will be covered in Summary File 3. Data are available for states, counties, county subdivisions, places, census tracts, block groups, and, where applicable, American Indian and Alaskan Native Areas and Hawaiian Home Lands. The SF1 data are available on the Bureau's web site and may be retrieved from American FactFinder as tables, lists, or maps. Users may also download a set of compressed ASCII files for each state via the Bureau's FTP server. There are over 8000 data items available for each geographic area. The full listing of these data items is available here as a downloadable compressed data base file named TABLES.ZIP. The uncompressed is in FoxPro data base file (dbf) format and may be imported to ACCESS, EXCEL, and other software formats. While all of this information is useful, the Office of Community Planning and Development has downloaded selected information for all states and areas and is making this information available on the CPD web pages. The tables and data items selected are those items used in the CDBG and HOME allocation formulas plus topics most pertinent to the Comprehensive Housing Affordability Strategy (CHAS), the Consolidated Plan, and similar overall economic and community development plans. The information is contained in five compressed (zipped) dbf tables for each state. When uncompressed the tables are ready for use with FoxPro and they can be imported into ACCESS, EXCEL, and other spreadsheet, GIS and database software. The data are at the block group summary level. The first two characters of the file name are the state abbreviation. The next two letters are BG for block group. Each record is labeled with the code and name of the city and county in which it is located so that the data can be summarized to higher-level geography. The last part of the file name describes the contents . The GEO file contains standard Census Bureau geographic identifiers for each block group, such as the metropolitan area code and congressional district code. The only data included in this table is total population and total housing units. POP1 and POP2 contain selected population variables and selected housing items are in the HU file. The MA05 table data is only for use by State CDBG grantees for the reporting of the racial composition of beneficiaries of Area Benefit activities. The complete package for a state consists of the dictionary file named TABLES, and the five data files for the state. The logical record number (LOGRECNO) links the records across tables.
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All data was collected from US Census official site: data.census.gov
The first row in all data files contains column descriptions. It should be ignored in the load, e.g.:
df = pd.read_csv('ACSST5Y2018.S0101-Data.csv', skiprows=[1], low_memory=False)
Next, if you need county CFIPS, it can be exctracted from the GEO_ID column:
df['CFIPS'] = df['GEO_ID'].apply(lambda x: int(x.split('US')[-1]))
American Community Survey (ACS) data derived from S0101 AGE AND SEX: - ACSST5Y2018.S0101-Data.csv - ACSST5Y2018.S0101-Column-Metadata.csv - ACSST5Y2019.S0101-Data.csv - ACSST5Y2019.S0101-Column-Metadata.csv - ACSST5Y2020.S0101-Data.csv - ACSST5Y2020.S0101-Column-Metadata.csv - ACSST5Y2021.S0101-Data.csv - ACSST5Y2021.S0101-Column-Metadata.csv
Includes basic info on population and age structure
American Community Survey (ACS) data derived from DP05ACS DEMOGRAPHIC AND HOUSING ESTIMATES: - ACSDP5Y2018.DP05-Data.csv - ACSDP5Y2018.DP05-Column-Metadata.csv - ACSDP5Y2019.DP05-Data.csv - ACSDP5Y2019.DP05-Column-Metadata.csv - ACSDP5Y2020.DP05-Data.csv - ACSDP5Y2020.DP05-Column-Metadata.csv - ACSDP5Y2021.DP05-Data.csv - ACSDP5Y2021.DP05-Column-Metadata.csv
Includes detailed info on demographic structure: age, race, sex, etc
County Business Patterns (CBP) data derived from: - CB1800CBP All Sectors: County Business Patterns, including ZIP Code Business Patterns, by Legal Form of Organization and Employment Size Class for the U.S., States, and Selected Geographies: 2018 - CBP2018.CB1800CBP-Data.csv - CBP2018.CB1800CBP-Column-Metadata.csv - CB1900CBP All Sectors: County Business Patterns, including ZIP Code Business Patterns, by Legal Form of Organization and Employment Size Class for the U.S., States, and Selected Geographies: 2019 - CBP2019.CB1900CBP-Data.csv - CBP2019.CB1900CBP-Column-Metadata.csv - CB2000CBP All Sectors: County Business Patterns, including ZIP Code Business Patterns, by Legal Form of Organization and Employment Size Class for the U.S., States, and Selected Geographies: 2020 - CBP2020.CB2000CBP-Data.csv - CBP2020.CB2000CBP-Column-Metadata.csv
Includes info on number of establishments, payroll, and other metrics by different business size (less than 5 employees, 5 to 9 employees, etc).
American Community Survey (ACS) data derived from B28003 PRESENCE OF A COMPUTER AND TYPE OF INTERNET SUBSCRIPTION IN HOUSEHOLD: - ACSDT5Y2018.B28003-Data.csv - ACSDT5Y2018.B28003-Column-Metadata.csv - ACSDT5Y2019.B28003-Data.csv - ACSDT5Y2019.B28003-Column-Metadata.csv - ACSDT5Y2020.B28003-Data.csv - ACSDT5Y2020.B28003-Column-Metadata.csv - ACSDT5Y2021.B28003-Data.csv - ACSDT5Y2021.B28003-Column-Metadata.csv
American Community Survey (ACS) data derived from S2801 TYPES OF COMPUTERS AND INTERNET SUBSCRIPTIONS: - ACSST5Y2018.S2801-Data.csv - ACSST5Y2018.S2801-Column-Metadata.csv - ACSST5Y2019.S2801-Data.csv - ACSST5Y2019.S2801-Column-Metadata.csv - ACSST5Y2020.S2801-Data.csv - ACSST5Y2020.S2801-Column-Metadata.csv - ACSST5Y2021.S2801-Data.csv - ACSST5Y2021.S2801-Column-Metadata.csv
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Free U.S. ZIP Code Database with 7 essential data fields for personal use. Includes all 42,000+ ZIP codes with city, state, latitude, longitude, classification, and 2020 Census population. Updated monthly with lifetime access. Download in CSV, Excel, Access, and SQL formats at no cost. Perfect for educational projects, address validation, basic mapping, and personal applications. No credit card required.
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TwitterThis dataset denotes ZIP Code centroid locations weighted by population. Population weighted centroids are a common tool for spatial analysis, particularly when more granular data is unavailable or researchers lack sophisticated geocoding tools. The ZIP Code Population Weighted Centroids allows researchers and analysts to estimate the center of population in a given geography rather than the geometric center.
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TwitterOur zip code Database offers comprehensive postal code data for spatial analysis, including postal and administrative areas. This dataset contains accurate and up-to-date information on all administrative divisions, cities, and zip codes, making it an invaluable resource for various applications such as address capture and validation, map and visualization, reporting and business intelligence (BI), master data management, logistics and supply chain management, and sales and marketing. Our location data packages are available in various formats, including CSV, optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more. Product features include fully and accurately geocoded data, multi-language support with address names in local and foreign languages, comprehensive city definitions, and the option to combine map data with UNLOCODE and IATA codes, time zones, and daylight saving times. Companies choose our location databases for their enterprise-grade service, reduction in integration time and cost by 30%, and weekly updates to ensure the highest quality.
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License information was derived automatically
PRISM data converted into FIPS, ZIP Code, and census tract summaries in the USA Introduction: Parameter-elevation Regressions on Independent Slopes Model (PRISM) by PRISM Climate group Oregon State temperature, precipitation 4km daily weather variable grids that I have converted to daily county FIPS, ZIP Code, and census tract summaries for use in several papers. Available for download (see Data below) in RDS (compact) format. CSV available on request. In Python it is easy to load RDS files and much more compact files than CSVs too. Note that ZIP Code throughout is actually ZIP Code Tabulation Area (ZCTA), which was developed to overcome the difficulties in precisely defining the land area covered by each ZIP Code. Defining the extent of an area is necessary in order to tabulate census data for that area.
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Leverage up-to-date census data with population trends for real estate, market research, audience targeting, and sales territory mapping.
Self-hosted commercial demographic dataset curated based on trusted sources such as the United Nations or the European Commission, with a 99% match accuracy. The global Census Data is standardized, unified, and ready to use.
Use cases for the Global Census Database (Consumer Demographic Data)
Ad targeting
B2B Market Intelligence
Customer analytics
Real Estate Data Estimations
Marketing campaign analysis
Demand forecasting
Sales territory mapping
Retail site selection
Reporting
Audience targeting
Census data export methodology
Our consumer demographic data packages are offered in CSV format. All Demographic data are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.
Product Features
Historical population data (55 years)
Changes in population density
Urbanization Patterns
Accurate at zip code and administrative level
Optimized for easy integration
Easy customization
Global coverage
Updated yearly
Standardized and reliable
Self-hosted delivery
Fully aggregated (ready to use)
Rich attributes
Why do companies choose our demographic databases
Standardized and unified demographic data structure
Seamless integration in your system
Dedicated location data expert
Note: Custom population data packages are available. Please submit a request via the above contact button for more details.
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Twitterwe utilized data from two main sources: the United States Census Bureau's American Community Survey (ACS) and the Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry (CDC/ATSDR) Social Vulnerability Index (SVI).American Community Survey (ACS):Conducted by the U.S. Census Bureau, the ACS is an ongoing survey that provides detailed demographic and socio-economic data on the population and housing characteristics of the United States.The survey collects information on various topics such as income, education, employment, health insurance coverage, and housing costs and conditions.It offers more frequent and up-to-date information compared to the decennial census, with annual estimates produced based on a rolling sample of households.The ACS data is essential for policymakers, researchers, and communities to make informed decisions and address the evolving needs of the population.CDC/ATSDR Social Vulnerability Index (SVI):Created by ATSDR’s Geospatial Research, Analysis & Services Program (GRASP) and utilized by the CDC, the SVI is designed to identify and map communities that are most likely to need support before, during, and after hazardous events.
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Supercharge your B2C marketing campaigns with comprehensive consumer database, featuring over 269 million verified US consumer records. Our 20+ year data expertise delivers higher quality and more extensive coverage than competitors.
Core Database Statistics
Consumer Records: Over 269 million
Email Addresses: Over 160 million (verified and deliverable)
Phone Numbers: Over 76 million (mobile and landline)
Mailing Addresses: Over 116,000,000 (NCOA processed)
Geographic Coverage: Complete US (all 50 states)
Compliance Status: CCPA compliant with consent management
Targeting Categories Available
Demographics: Age ranges, education levels, occupation types, household composition, marital status, presence of children, income brackets, and gender (where legally permitted)
Geographic: Nationwide, state-level, MSA (Metropolitan Service Area), zip code radius, city, county, and SCF range targeting options
Property & Dwelling: Home ownership status, estimated home value, years in residence, property type (single-family, condo, apartment), and dwelling characteristics
Financial Indicators: Income levels, investment activity, mortgage information, credit indicators, and wealth markers for premium audience targeting
Lifestyle & Interests: Purchase history, donation patterns, political preferences, health interests, recreational activities, and hobby-based targeting
Behavioral Data: Shopping preferences, brand affinities, online activity patterns, and purchase timing behaviors
Multi-Channel Campaign Applications
Deploy across all major marketing channels:
Email marketing and automation
Social media advertising
Search and display advertising (Google, YouTube)
Direct mail and print campaigns
Telemarketing and SMS campaigns
Programmatic advertising platforms
Data Quality & Sources
Our consumer data aggregates from multiple verified sources:
Public records and government databases
Opt-in subscription services and registrations
Purchase transaction data from retail partners
Survey participation and research studies
Online behavioral data (privacy compliant)
Technical Delivery Options
File Formats: CSV, Excel, JSON, XML formats available
Delivery Methods: Secure FTP, API integration, direct download
Processing: Real-time NCOA, email validation, phone verification
Custom Selections: 1,000+ selectable demographic and behavioral attributes
Minimum Orders: Flexible based on targeting complexity
Unique Value Propositions
Dual Spouse Targeting: Reach both household decision-makers for maximum impact
Cross-Platform Integration: Seamless deployment to major ad platforms
Real-Time Updates: Monthly data refreshes ensure maximum accuracy
Advanced Segmentation: Combine multiple targeting criteria for precision campaigns
Compliance Management: Built-in opt-out and suppression list management
Ideal Customer Profiles
E-commerce retailers seeking customer acquisition
Financial services companies targeting specific demographics
Healthcare organizations with compliant marketing needs
Automotive dealers and service providers
Home improvement and real estate professionals
Insurance companies and agents
Subscription services and SaaS providers
Performance Optimization Features
Lookalike Modeling: Create audiences similar to your best customers
Predictive Scoring: Identify high-value prospects using AI algorithms
Campaign Attribution: Track performance across multiple touchpoints
A/B Testing Support: Split audiences for campaign optimization
Suppression Management: Automatic opt-out and DNC compliance
Pricing & Volume Options
Flexible pricing structures accommodate businesses of all sizes:
Pay-per-record for small campaigns
Volume discounts for large deployments
Subscription models for ongoing campaigns
Custom enterprise pricing for high-volume users
Data Compliance & Privacy
VIA.tools maintains industry-leading compliance standards:
CCPA (California Consumer Privacy Act) compliant
CAN-SPAM Act adherence for email marketing
TCPA compliance for phone and SMS campaigns
Regular privacy audits and data governance reviews
Transparent opt-out and data deletion processes
Getting Started
Our data specialists work with you to:
Define your target audience criteria
Recommend optimal data selections
Provide sample data for testing
Configure delivery methods and formats
Implement ongoing campaign optimization
Why We Lead the Industry
With over two decades of data industry experience, we combine extensive database coverage with advanced targeting capabilities. Our commitment to data quality, compliance, and customer success has made us the preferred choice for businesses seeking superior B2C marketing performance.
Contact our team to discuss your specific ta...
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TwitterA global database of Real Estate Data that provides an understanding of population distribution at administrative and zip code levels over 55 years, past, present, and future.
Leverage up-to-date urban planning data with population trends for real estate, market research, audience targeting, and sales territory mapping.
Self-hosted commercial real estate dataset curated based on trusted sources such as the United Nations or the European Commission, with a 99% match accuracy. The Urban Planning Data is standardized, unified, and ready to use.
Use cases for the Global Population Database (Urban Planning Data)
Ad targeting
B2B Market Intelligence
Customer analytics
Real Estate Data Estimations
Marketing campaign analysis
Demand forecasting
Sales territory mapping
Retail site selection
Reporting
Audience targeting
Demographic data export methodology
Our location data packages are offered in CSV format. All Demographic data are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.
Product Features
Historical population data (55 years)
Changes in population density
Urbanization Patterns
Accurate at zip code and administrative level
Optimized for easy integration
Easy customization
Global coverage
Updated yearly
Standardized and reliable
Self-hosted delivery
Fully aggregated (ready to use)
Rich attributes
Why do companies choose our Real Estate databases
Standardized and unified demographic data structure
Seamless integration in your system
Dedicated location data expert
Note: Custom population data packages are available. Please submit a request via the above contact button for more details.
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Leverage up-to-date audience targeting data trends for market research, audience targeting, and sales territory mapping.
Self-hosted consumer data curated based on trusted sources such as the United Nations or the European Commission, with a 99% match accuracy. The Consumer Data is standardized, unified, and ready to use.
Use cases for the Global Population Database (Consumer Data Data/Segmentation data)
Ad targeting
B2B Market Intelligence
Customer analytics
Marketing campaign analysis
Demand forecasting
Sales territory mapping
Retail site selection
Reporting
Audience targeting
Segmentation data export methodology
Our location data packages are offered in CSV format. All geospatial data are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.
Product Features
Historical population data (55 years)
Changes in population density
Urbanization Patterns
Accurate at zip code and administrative level
Optimized for easy integration
Easy customization
Global coverage
Updated yearly
Standardized and reliable
Self-hosted delivery
Fully aggregated (ready to use)
Rich attributes
Why do companies choose our Population Databases
Standardized and unified demographic data structure
Seamless integration in your system
Dedicated location data expert
Note: Custom population data packages are available. Please submit a request via the above contact button for more details.
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Twitterhttps://www.ons.gov.uk/methodology/geography/licenceshttps://www.ons.gov.uk/methodology/geography/licences
This file contains the National Statistics Postcode Lookup (NSPL) for the United Kingdom as at August 2022 in Comma Separated Variable (CSV) and ASCII text (TXT) formats. To download the zip file click the Download button. The NSPL relates both current and terminated postcodes to a range of current statutory geographies via ‘best-fit’ allocation from the 2021 Census Output Areas (national parks and Workplace Zones are exempt from ‘best-fit’ and use ‘exact-fit’ allocations) for England and Wales. Scotland and Northern Ireland has the 2011 Census Output AreasIt supports the production of area based statistics from postcoded data. The NSPL is produced by ONS Geography, who provide geographic support to the Office for National Statistics (ONS) and geographic services used by other organisations. The NSPL is issued quarterly. (File size - 184 MB).
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Comprehensive Canadian Postal Code Database with complete PCCF-equivalent Statistics Canada census geography linkage. Includes 900,000+ postal codes with latitude/longitude coordinates, census demographic data, Federal Electoral Districts, and 17 supplemental reference tables. Available in Standard (8 fields), Deluxe (15 fields), and Business (43 fields) editions. Business edition includes pre-integrated Census Metropolitan Areas (CMA), Census Divisions (CD), Census Subdivisions (CSD), Dissemination Areas (DA), Census Tracts (CT), Economic Regions (ER), Population Centres, and Federal Electoral Districts-eliminating the need for separate PCCF file management. All editions include monthly updates from Canada Post, bilingual municipality names, accent supplement tables, and geocoding coordinates with ~99% coverage. Multiple formats: Microsoft Access, Excel, and CSV. Includes free FTP access, U.S.-based phone and email support, and 30-day money-back guarantee.
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A dataset comprising various variables around housing and demographics for the top 50 American cities by population.
Variables:
Zip Code: Zip code within which the listing is present.
Price: Listed price for the property.
Beds: Number of beds mentioned in the listing.
Baths: Number of baths mentioned in the listing.
Living Space: The total size of the living space, in square feet, mentioned in the listing.
Address: Street address of the listing.
City: City name where the listing is located.
State: State name where the listing is located.
Zip Code Population: The estimated number of individuals within the zip code. Data from Simplemaps.com.
Zip Code Density: The estimated number of individuals per square mile within the zip code. Data from Simplemaps.com.
County: County where the listing is located.
Median Household income: Estimated median household income. Data from the U.S. Census Bureau.
Latitude: Latitude of the zip code. ** Data from Simplemaps.com.**
Longitude: Longitude of the zip code. Data from Simplemaps.com.
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A dataset listing Washington zip codes by population for 2024.
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The property level flood risk statistics generated by the First Street Foundation Flood Model Version 2.0 come in CSV format.
The data that is included in the CSV includes:
An FSID; a First Street ID (FSID) is a unique identifier assigned to each location.
The latitude and longitude of a parcel as well as the zip code, census block group, census tract, county, congressional district, and state of a given parcel.
The property’s Flood Factor as well as data on economic loss.
The flood depth in centimeters at the low, medium, and high CMIP 4.5 climate scenarios for the 2, 5, 20, 100, and 500 year storms this year and in 30 years.
Data on the cumulative probability of a flood event exceeding the 0cm, 15cm, and 30cm threshold depth is provided at the low, medium, and high climate scenarios for this year and in 30 years.
Information on historical events and flood adaptation, such as ID and name.
This dataset includes First Street's aggregated flood risk summary statistics. The data is available in CSV format and is aggregated at the congressional district, county, and zip code level. The data allows you to compare FSF data with FEMA data. You can also view aggregated flood risk statistics for various modeled return periods (5-, 100-, and 500-year) and see how risk changes due to climate change (compare FSF 2020 and 2050 data). There are various Flood Factor risk score aggregations available including the average risk score for all properties (flood factor risk scores 1-10) and the average risk score for properties with risk (i.e. flood factor risk scores of 2 or greater). This is version 2.0 of the data and it covers the 50 United States and Puerto Rico. There will be updated versions to follow.
If you are interested in acquiring First Street flood data, you can request to access the data here. More information on First Street's flood risk statistics can be found here and information on First Street's hazards can be found here.
The data dictionary for the parcel-level data is below.
Field Name
Type
Description
fsid
int
First Street ID (FSID) is a unique identifier assigned to each location
long
float
Longitude
lat
float
Latitude
zcta
int
ZIP code tabulation area as provided by the US Census Bureau
blkgrp_fips
int
US Census Block Group FIPS Code
tract_fips
int
US Census Tract FIPS Code
county_fips
int
County FIPS Code
cd_fips
int
Congressional District FIPS Code for the 116th Congress
state_fips
int
State FIPS Code
floodfactor
int
The property's Flood Factor, a numeric integer from 1-10 (where 1 = minimal and 10 = extreme) based on flooding risk to the building footprint. Flood risk is defined as a combination of cumulative risk over 30 years and flood depth. Flood depth is calculated at the lowest elevation of the building footprint (largest if more than 1 exists, or property centroid where footprint does not exist)
CS_depth_RP_YY
int
Climate Scenario (low, medium or high) by Flood depth (in cm) for the Return Period (2, 5, 20, 100 or 500) and Year (today or 30 years in the future). Today as year00 and 30 years as year30. ex: low_depth_002_year00
CS_chance_flood_YY
float
Climate Scenario (low, medium or high) by Cumulative probability (percent) of at least one flooding event that exceeds the threshold at a threshold flooding depth in cm (0, 15, 30) for the year (today or 30 years in the future). Today as year00 and 30 years as year30. ex: low_chance_00_year00
aal_YY_CS
int
The annualized economic damage estimate to the building structure from flooding by Year (today or 30 years in the future) by Climate Scenario (low, medium, high). Today as year00 and 30 years as year30. ex: aal_year00_low
hist1_id
int
A unique First Street identifier assigned to a historic storm event modeled by First Street
hist1_event
string
Short name of the modeled historic event
hist1_year
int
Year the modeled historic event occurred
hist1_depth
int
Depth (in cm) of flooding to the building from this historic event
hist2_id
int
A unique First Street identifier assigned to a historic storm event modeled by First Street
hist2_event
string
Short name of the modeled historic event
hist2_year
int
Year the modeled historic event occurred
hist2_depth
int
Depth (in cm) of flooding to the building from this historic event
adapt_id
int
A unique First Street identifier assigned to each adaptation project
adapt_name
string
Name of adaptation project
adapt_rp
int
Return period of flood event structure provides protection for when applicable
adapt_type
string
Specific flood adaptation structure type (can be one of many structures associated with a project)
fema_zone
string
Specific FEMA zone categorization of the property ex: A, AE, V. Zones beginning with "A" or "V" are inside the Special Flood Hazard Area which indicates high risk and flood insurance is required for structures with mortgages from federally regulated or insured lenders
footprint_flag
int
Statistics for the property are calculated at the centroid of the building footprint (1) or at the centroid of the parcel (0)
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A dataset listing Illinois zip codes by population for 2024.
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Unlock the power of geographical precision with this comprehensive ZIP to FIPS dataset. Seamlessly map ZIP codes to Federal Information Processing Standards (FIPS) codes, enabling accurate location-based analyses. Ideal for geospatial applications, demographic research, and data integration. Explore the seamless fusion of ZIP and FIPS codes for enhanced spatial insights.
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Twitterhttps://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
Easily lookup US historical demographics by county FIPS or zipcode in seconds with this file containing over 5,901 different columns including:
*Lat/Long *Boundaries *State FIPS *Population from 2010-2019 *Death Rate from 2010-2019 *Unemployment from 2001-2020 *Education from 1970-2019 *Gender and Age Population
Provided by bitrook.com to help Data Scientists clean data faster.
https://www.ers.usda.gov/data-products/county-level-data-sets/download-data/
https://www.ers.usda.gov/data-products/county-level-data-sets/download-data/
https://www.ers.usda.gov/data-products/county-level-data-sets/download-data/
https://data.world/niccolley/us-zipcode-to-county-state
https://www2.census.gov/programs-surveys/popest/datasets/2010-2019/counties/asrh/cc-est2019-agesex-**.csv https://www2.census.gov/programs-surveys/popest/technical-documentation/file-layouts/2010-2019/cc-est2019-agesex.pdf
https://www2.census.gov/programs-surveys/popest/datasets/2010-2019/counties/asrh/cc-est2019-alldata.csv https://www2.census.gov/programs-surveys/popest/technical-documentation/file-layouts/2010-2019/cc-est2019-alldata.pdf