Identification Information

Title Education by County 2016

Date 2020-03-06

Date Type Publication

Cited Responsible Party

Organization Name Geography Division, Bureau of the Census, U.S. Department of Commerce

Role identify

Presentation Form vector digital data

Abstract A broad and generalized selection of 2012-2016 US Census Bureau 2016 5-year American Community Survey education data estimates, obtained via Census API and joined to the appropriate geometry (in this case, New Mexico counties). The selection is not comprehensive, but allows a first-level characterization of educational attaiment by grade level and sex (for all persons 25 years and older), plus enrollment estimates at key educational levels (for the universe of all persons 3+ years old). The determination of which estimates to include was based upon level of interest and providing a manageable dataset for users. The U.S. Census Bureau's American Community Survey (ACS) is a nationwide, continuous survey designed to provide communities with reliable and timely demographic, housing, social, and economic data every year. The ACS collects long-form-type information throughout the decade rather than only once every 10 years. As in the decennial census, strict confidentiality laws protect all information that could be used to identify individuals or households.The ACS combines population or housing data from multiple years to produce reliable numbers for small counties, neighborhoods, and other local areas. To provide information for communities each year, the ACS provides 1-, 3-, and 5-year estimates. ACS 5-year estimates (multiyear estimates) are “period” estimates that represent data collected over a 60-month period of time (as opposed to “point-in-time” estimates, such as the decennial census, that approximate the characteristics of an area on a specific date). ACS data are released in the year immediately following the year in which they are collected. ACS estimates based on data collected from 2009–2014 should not be called “2009” or “2014” estimates. Multiyear estimates should be labeled to indicate clearly the full period of time. The primary advantage of using multiyear estimates is the increased statistical reliability of the data for less populated areas and small population subgroups. Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. While each full Data Profile contains margin of error (MOE) information, this dataset does not. Those individuals requiring more complete data are directed to download the more detailed datasets from the ACS American FactFinder website. This dataset is organized by New Mexico county boundaries.

Purpose Provide general users with a selection of education data available from the US Census Bureau's American Community Survey (ACS) 5-year estimates from 2012-2016.

Supplemental Information This work was influenced by the work of Todd Bleess at the Colorado State Demography Office, especially his renaming of the source (ACS) attributes into more human-readable names.

Data Set Credit U.S. Census Bureau; RGIS; Todd Bleess, Colorado State Demography Office

Status Complete

Point of Contact

Maintenance and Update Frequency Annually

Descriptive Keywords

Access Constraints None

Use Constraints None from RGIS. The source geometry for this dataset is a TIGER/Line shapefile. TIGER/Line Shapefile products are not copyrighted however TIGER/Line and Census TIGER are registered trademarks of the U.S. Census Bureau.The boundary information in the TIGER/Line Shapefiles are for statistical data collection and tabulation purposes only; their depiction and designation for statistical purposes does not constitute a determination of jurisdictional authority or rights of ownership or entitlement and they are not legal land descriptions.Coordinates in the TIGER/Line shapefiles have six implied decimal places, but the positional accuracy of these coordinates is not as great as the six decimal places suggest.

Language English

Topic Category society

Extent

Geographic Bounding Box

West Bound -109.05017
East Bound -103.00196
North Bound 37.000293
South Bound 31.33217

Temporal Extent

DateTime 2016

Data Quality Information

Logical Consistency Report All 33 counties are present

Completeness Report All 33 counties are present

Lineage

Source Information

Source Citation

Source Scale Denominator

Type of Source Media onLine

Source Time Period of Content

DateTime 2016
Source Currentness Reference Publication date

Source Citation Abbreviation Census Data

Source Contribution Derived from US Bureau of Census API

Process Step

Process Description Develop script to automate the entire process described below, from obtaining data to producing and validating metadata, for a group of datasets. The slightly more detailed steps given following this step.
Process Date 2020-01-14
Process Time
Process Contact

Process Step

Process Description Obtain a select group of Bureau of Census data from latest availalble ACS 5-year estimate using Census API. Census API calls are limited to 50 fields/attributes per call, and are typically run as an URL, using a browser, the curl command line too, or from within a script. The data from the Census API is serialized into a dataframe.
Process Date 2020-01-14
Process Time
Process Contact

Process Step

Process Description Format data as needed for usefulness and attribute label readability and deserialize for the next step.
Process Date 2020-01-14
Process Time
Process Contact

Process Step

Process Description Joined Census dataset to appropriate geometry (like Census TIGER/Line file for New Mexico counties), performed via scripting, based on common key field.
Process Date 2020-01-14
Process Time
Process Contact

Process Step

Process Description Edit metadata for completeness and for compatibility with FGDC standards for distribution via NM RGIS Clearinghouse.
Process Date 2020-01-14
Process Time
Process Contact

Education by County 2016

Metadata from the RGIS Metadata Repository

Identification Information

Distribution Information

Spatial Reference Information

Data Quality Information

Metadata Reference Information