- What is the Population Count?
- 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 High School Graduation Rate?
- What is the Median Female Earnings?
- What is the Percent Employed?
- What is the Percent with an associate's degree?
- What is the Median Male Earnings?
- What is the College Graduation Rate?
The population rate of change of Crescent City Micro Area (CA) was -0.07% in 2018.
Demographics and Population Datasets Involving Crescent City Micro Area (CA)
- API healthstat.dph.sbcounty.gov | Last Updated 2019-03-13T19:07:43.000Z
Percent of People who Cannot Afford to Feed Themselves Sufficiently. U.S. Census Bureau, Current Population Survey, December Supplement (AKA USDA Food Security Supplement). Dissected by Year, Geographic Area, Age Category, and Race/Ethnicity.
- API data.cambridgema.gov | Last Updated 2019-09-17T17:16:51.000Z
This data set provides demographic and journey to work characteristics of the Cambridge Labor Force by primary mode of their journey to work. Attributes include age, presence of children, racial and ethnic minority status, vehicles available, time leaving home, time spent traveling, and annual household income. The data set originates from a special tabulation of the American Community Survey - the 2012 - 2016 version of the Census Transportation Planning Products (CTPP). The Cambridge Labor Force consist of all persons who live in Cambridge who work or are actively seeking employment. For more information on Journey to Work data in Cambridge, please see the full 2015 report (https://www.cambridgema.gov/~/media/Files/CDD/FactsandMaps/profiles/moving_forward_20150930.ashx?la=en).
- API data.cambridgema.gov | Last Updated 2019-09-17T17:17:39.000Z
This data set provides demographic and journey to work characteristics of the Cambridge Workforce by primary mode of their journey to work. Attributes include age, presence of children, racial and ethnic minority status, vehicles available, time arriving at work, time spent traveling, and annual household income. The data set originates from a special tabulation of the American Community Survey - the 2012 - 2016 version of the Census Transportation Planning Products (CTPP). The Cambridge Workforce consist of all persons who work in Cambridge, regardless of home location. For more information on Journey to Work data in Cambridge, please see the full 2015 report: https://www.cambridgema.gov/~/media/Files/CDD/FactsandMaps/profiles/moving_forward_20150930.ashx?la=en).
- API data.sfgov.org | Last Updated 2021-05-07T16:32:21.000Z
<strong>A. SUMMARY</strong> This dataset represents doses of COVID-19 vaccine administered in California to San Francisco residents over time. The data is broken down by multiple demographic slices. The three dose types are counted separately, i.e. (1) first doses administered as a part of a two-dose vaccination, (2) second doses administered as part of a two-dose vaccination, and (3) single-dose vaccines administered. <strong>B. HOW THE DATASET IS CREATED</strong> Information on doses administered to those who live in San Francisco is from the <a href="https://cairweb.org/about-cair/">California Immunization Registry (CAIR)</a>, run by the California Department of Public Health (CDPH). The information on individuals’ city of residence, age, race, and ethnicity are also recorded in CAIR and are self-reported at the time of administration. In order to estimate the percent of San Franciscans vaccinated, we provide <a href="https://data.census.gov/cedsci/table?q=popualtion%20age&g=0500000US06075&tid=ACSST5Y2019.S0101&hidePreview=false">the same 2019 five-year American Community Survey population estimates</a> that are used in <a href="https://data.sfgov.org/stories/s/COVID-19-Vaccinations-Progress/7mye-zncy/">our public dashboards</a>. <strong>C. UPDATE PROCESS</strong> Updated daily via automated process <strong>D. HOW TO USE THIS DATASET</strong> Before analysis, you must filter the dataset to the desired slice of data using the OVERALL_SEGMENT column. For example, filtering OVERALL_SEGMENT to "Ages 16+ by Age Bracket, Administered by All Providers" will filter the data to residents 16 and over whose vaccinations were administered by any provider. You can then further segment the data and calculate percentages by Age Brackets. If you filter OVERALL_SEGMENT to "Ages 65+ by Race/Ethnicity, Administered by DPH Only", you will see the race/ethnicity breakdown for residents aged 65+ who received vaccinations from San Francisco’s Department of Public Health (DPH).
- API data.bayareametro.gov | Last Updated 2019-08-13T16:16:34.000Z
VITAL SIGNS INDICATOR Income (EC4) FULL MEASURE NAME Household income by place of residence LAST UPDATED May 2019 DESCRIPTION Income reflects the median earnings of individuals and households from employment, as well as the income distribution by quintile. Income data highlight how employees are being compensated for their work on an inflation-adjusted basis. DATA SOURCE U.S. Census Bureau: Decennial Census Count 4Pb (1970) Form STF3 (1980-1990) Form SF3a (2000) https://nhgis.org U.S. Census Bureau: American Community Survey Form B19013 (2006-2017; place of residence) http://api.census.gov Bureau of Labor Statistics: Consumer Price Index All Urban Consumers Data Table (1970-2017; specific to each metro area) http://data.bls.gov CONTACT INFORMATION firstname.lastname@example.org METHODOLOGY NOTES (across all datasets for this indicator) Income data reported in a given year reflects the income earned in the prior year (decennial Census) or in the prior 12 months (American Community Survey); note that this inconsistency has a minor effect on historical comparisons (for more information, go to: http://www.census.gov/acs/www/Downloads/methodology/ASA_nelson.pdf). American Community Survey 1-year data is used for larger geographies – metropolitan areas and counties – while smaller geographies rely upon 5-year rolling average data due to their smaller sample sizes. Quintile income for 1970-2000 is imputed from Decennial Census data using methodology from the California Department of Finance (for more information, go to: http://www.dof.ca.gov/Forecasting/Demographics/Census_Data_Center_Network/documents/How_to_Recalculate_a_Median.pdf). Bay Area income is the population weighted average of county-level income. Income has been inflated using the Consumer Price Index specific to each metro area; however, some metro areas lack metro-specific CPI data back to 1970 and therefore adjusted data is unavailable for some historical data points. Note that current MSA boundaries were used for historical comparison by identifying counties included in today’s metro areas.
- API data.bayareametro.gov | Last Updated 2020-12-09T01:58:17.000Z
This data set represents all tracts within the San Francisco Bay Region, and contains attributes for the eight Metropolitan Transportation Commission (MTC) Communities of Concern (CoC) tract-level variables for exploratory purposes. MTC 2018 Communities of Concern (tract geography) is based on eight ACS 2014-2018 (ACS 2018) tract-level variables: ● Minority (70% threshold) ● Low-Income (less than 200% of Fed. poverty level, 28% threshold) ● Level of English Proficiency (12% threshold) ● Seniors 75 Years and Over (8% threshold) ● Zero-Vehicle Households (15% threshold) ● Single Parent Households (18% threshold) ● People with a Disability (12% threshold) ● Rent-Burdened Households (14% threshold) If a tract exceeds both threshold values for Low-Income and Minority shares OR exceeds the threshold value for Low-Income AND also exceeds the threshold values for three or more variables, it is a CoC. Detailed documentation on the production of this feature set can be found at https://github.com/BayAreaMetro/Spatial-Analysis-Mapping-Projects/blob/master/Project-Documentation/Communities-of-Concern/README.md
- API data.sonomacounty.ca.gov | Last Updated 2019-07-12T18:26:35.000Z
The County of Sonoma conducts an annual homeless count for the entire county. The survey data is derived from a sample of about 600 homeless persons countywide per year. The resulting information is statistically reliable only for the county as a whole, not for individual locations. The exception is the City of Santa Rosa, where the sample taken within the city is large enough to be predictive of the overall homeless population in that city.