The new usmcdcprofiles2006_2015 has the standard profile data for all geographic areas large enough to get single-year
ACS data (i.e. population at least 65,000) for each of the 10 years indicated. We got this by simply interleaving the ten
datasets named usmcdcprofiles in the 10 acs yearly directories (acs2006, acs2007, ...,acs2015). An alternate dataset
("_nomoes" appended to the set name) is the same as this one but has all the "moe" (margin of error) variables removed.
metadata page for details.
We also have added a 2015 vintage age by race/hispanic and sex (usagebysexraceh15) dataset - same idea as the
previous five years. These datasets are mostly for internal use, or for people who have statistical software that makes
it easier to build custom tables from data in this "cell" format.
We have also generated a series of reports based upon these
data that can be accessed at the population estimates Reports index page.
County Level Charts and Maps
Using these new data we have created a set of charts and maps showing some key variables measuring change in population between 2015 and 2016 at the county level.
These are the same bar charts and choropleth maps (one set per state) that we did last year.
You can access via Uexplore in the popcharts2016
subdirectory of the popests data directory. The
Menumap.html page can be used to
view a county level map for the entire U.S. that also doubles as a "menu map" where you click within a state to view
charts and maps for that state.
Regular users of this web site will recognize the fact that these 2016 vintage datasets, reports, charts, etc. are
the same products we have been producing for many years.
For more information and some analysis of these data see the Census Bureau web site for sahie data at
https://www.census.gov/did/www/sahie/. Note that we have
comparable trios of these sahie data sets for each year 2006 through 2015.
We have created a sample query for these data, stored as sahie_trends.htm (in the Queries subdirectory of the saipe data directory). This module demonstrates how to pull data from multiple years of the
sahie data to see trends in coverage over several years. This specific query does state level for all states, but
it can be readily adapted to work with other geography and/or with other time periods.