The population rate of change of Lake County, IN was -0.38% in 2018.

Population

Population Change

Above charts are based on data from the U.S. Census American Community Survey | ODN Dataset | API - Notes:

1. ODN datasets and APIs are subject to change and may differ in format from the original source data in order to provide a user-friendly experience on this site.

2. To build your own apps using this data, see the ODN Dataset and API links.

3. If you use this derived data in an app, we ask that you provide a link somewhere in your applications to the Open Data Network with a citation that states: "Data for this application was provided by the Open Data Network" where "Open Data Network" links to http://opendatanetwork.com. Where an application has a region specific module, we ask that you add an additional line that states: "Data about REGIONX was provided by the Open Data Network." where REGIONX is an HREF with a name for a geographical region like "Seattle, WA" and the link points to this page URL, e.g. http://opendatanetwork.com/region/1600000US5363000/Seattle_WA

Demographics and Population Datasets Involving Lake County, IN

  • API

    NYCHA Resident Data Book Summary

    data.cityofnewyork.us | Last Updated 2020-02-08T00:56:30.000Z

    Contains resident demographic data at a summary level as of January 1, 2019. The Resident Data Book is compiled to serve as an information source for queries involving resident demographic as well as a source of data for internal analysis. Statistics are compiled via HUD mandated annual income reviews involving NYCHA Staff and residents. Data is then aggregated and compiled by development. Each record pertains to a single public housing development.

  • API

    Choose Maryland: Compare Counties - Demographics

    opendata.maryland.gov | Last Updated 2024-07-09T17:43:22.000Z

    Population profile - total, rate of change, age, and density.

  • API

    CPI 1.1 Texas Child Population (ages 0-17) by County 2014-2023

    data.texas.gov | Last Updated 2024-09-05T21:23:24.000Z

    As recommended by the Health and Human Services Commission (HHSC) to ensure consistency across all HHSC agencies, in 2012 DFPS adopted the HHSC methodology on how to categorize race and ethnicity. As a result, data broken down by race and ethnicity in 2012 and after is not directly comparable to race and ethnicity data in 2011 and before. The population totals may not match previously printed DFPS Data Books. Past population estimates are adjusted based on the U.S. Census data as it becomes available. This is important to keep the data in line with current best practices, but may cause some past counts, such as Abuse/Neglect Victims per 1,000 Texas Children, to be recalculated. Population Data Source - Population Estimates and Projections Program, Texas State Data Center, Office of the State Demographer and the Institute for Demographic and Socioeconomic Research, The University of Texas at San Antonio. Current population estimates and projections data as of December 2020. Visit dfps.texas.gov for information on all DFPS programs.

  • API

    New York State Population Data: Beginning 2003

    health.data.ny.gov | Last Updated 2024-03-07T16:13:08.000Z

    Population data file is provided as an additional reference file when interpreting vital statistics death rates. The population data is derived from the corresponding release of the NCHS annual estimates of "Bridged Race Vintage" which are consistent with the Bureau of the Census estimates from "Vintage" (released in the summer). For more information, check out: http://www.health.ny.gov/statistics/vital_statistics/. The "About" tab contains additional details concerning this dataset.

  • API

    WAOFM - Census - Population and Housing, 2000 and 2010

    data.wa.gov | Last Updated 2021-09-01T17:20:31.000Z

    Population and housing information extracted from decennial census Public Law 94-171 redistricting summary files for Washington state for years 2000 and 2010.

  • API

    Deaths with COVID-19 by race/ethnicity

    data.sccgov.org | Last Updated 2024-10-05T00:15:25.000Z

    The dataset provides information about the demographics and characteristics of deaths with COVID-19 by racial/ethnic groups among Santa Clara County residents. Source: California Reportable Disease Information Exchange. Data notes: The Other category for the race/ethnicity graph includes American Indian/Alaska Native and people who identify as multi-racial. This table is updated every Friday.

  • API

    NYSERDA Low- to Moderate-Income New York State Census Population Analysis Dataset: Average for 2013-2015

    data.ny.gov | Last Updated 2019-11-15T22:30:02.000Z

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

  • API

    COVID-19 cases by race/ethnicity

    data.sccgov.org | Last Updated 2024-10-05T00:00:27.000Z

    The dataset provides information about the demographics and characteristics of COVID-19 cases by racial/ethnic groups among Santa Clara County residents. Source: California Reportable Disease Information Exchange. Data notes: The Other category for the race/ethnicity graph includes American Indian/Alaska Native and people who identify as multi-racial. This table is updated every Thursday.

  • API

    Medicaid Inpatient Prevention Quality Indicators (PQI) for Adult Discharges by Patient County: Beginning 2011

    health.data.ny.gov | Last Updated 2016-12-05T21:58:39.000Z

    The datasets contain number of Medicaid PQI hospitalizations (numerator), county Medicaid population (denominator), observed rate, expected number of hospitalizations and rate, and risk-adjusted rate for Agency for Healthcare Research and Quality Prevention Quality Indicators – Adult (AHRQ PQI) for Medicaid enrollees beginning in 2011.

  • API

    Medicaid Potentially Preventable Emergency Visit (PPV) Rates by Patient County: Beginning 2011

    health.data.ny.gov | Last Updated 2016-12-16T15:57:37.000Z

    The dataset contains Potentially Preventable Visit (PPV) observed, expected, and risk-adjusted rates for Medicaid beneficiaries by patient county beginning in 2011. The Potentially Preventable Visits (PPV) obtained from software created by 3M Health Information Systems are emergency visits that may result from a lack of adequate access to care or ambulatory care coordination. These ambulatory sensitive conditions could be reduced or eliminated with adequate patient monitoring and follow up.