- What is the Population Rate of Change?
- What is the Population Density?
- What is the Land Area?
- What is the Percent who did not finish the 9th grade?
- What is the Median Earnings?
- What is the Number of Employees?
- What is the Crime incident count?
- What is the Water Area?
- What is the High School Graduation Rate?
- What is the Median Female Earnings?
The population count of Allentown, PA was 120,128 in 2017.
Demographics and Population Datasets Involving Allentown, PA
- API bronx.lehman.cuny.edu | Last Updated 2012-10-21T14:06:17.000Z
2010 Census Data on population, pop density, age and ethnicity per zip code
- API data.cityofnewyork.us | Last Updated 2019-07-19T21:02:11.000Z
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 health.data.ny.gov | Last Updated 2018-10-26T17:36:29.000Z
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 data.pa.gov | Last Updated 2019-08-19T17:32:46.000Z
This dataset contains aggregate death data at the state and county level for Pennsylvania residents. The data are displayed by year, race/ethnicity, gender, age group and cause of death.
- API health.data.ny.gov | Last Updated 2018-09-06T18:30:44.000Z
This dataset contains death counts by resident county and race/ethnicity. For more information check out: http://www.health.ny.gov/statistics/vital_statistics.
- API data.baltimorecity.gov | Last Updated 2017-02-06T04:55:23.000Z
Census data are frequently used throughout Vital Signs as denominators for normalizing many other indicators and rates. The socioeconomic and demographic indicators are grouped into the following categories: population, race/ethnicity, age, households, and income and poverty.
- API data.baltimorecity.gov | Last Updated 2017-02-06T04:44:33.000Z
BNIA-JFI analyzed data from the Census to provide greater understandingof the socioeconomic and demographic characteristics of the residents of the City and its neighborhoods . BNIA-JFI also used this data as denominators for many of the Vital Signs indicators allowing for data to be normalized and rates to be computed. Census data analyzed by BNIA-JFI is grouped into the following categories: population, race and ethnicity; households and families; and income.
- API opendata.ci.richmond.ca.us | Last Updated 2017-01-25T20:58:31.000Z
Census data from Bay Area Census and US Census.
- API health.data.ny.gov | Last Updated 2018-09-06T18:35:26.000Z
This dataset contains death counts by sex, age group, race/ethnicity, and selected cause of death. For more information, check out: http://www.health.ny.gov/statistics/vital_statistics/.
Rate of Hospitalizations for Opioid Overdose per 100,000 Residents by Demographics CY 2016- 2017 Statewide Health Care Cost Containment Council (PHC4)data.pa.gov | Last Updated 2019-01-18T20:03:25.000Z
Rate of hospitalization for opioid overdose per 100,000 PA Residents categorized by principal diagnosis of heroin or opioid pain medication overdose by year and demographic. This analysis is restricted to Pennsylvania residents age 15 and older who were hospitalized in Pennsylvania general acute care hospitals. Disclaimer: PHC4’s database contains statewide hospital discharge data submitted to PHC4 by Pennsylvania hospitals. Every reasonable effort has been made to ensure the accuracy of the information obtained from the Uniform Claims and Billing Form (UB-82/92/04) data elements. Computer collection edits and validation edits provide opportunity to correct specific errors that may have occurred prior to, during or after submission of data. The ultimate responsibility for data accuracy lies with individual providers. PHC4 agents and staff make no representation, guarantee, or warranty, expressed or implied that the data received from the hospitals are error-free, or that the use of this data will prevent differences of opinion or disputes with those who use published reports or purchased data. PHC4 will bear no responsibility or liability for the results or consequences of its use.