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httpSee also:*[[PostGIS Installation]]*[[Urban Start-up Agglomeration]] =Notes= The approach below, using American Fact Finder, seems to be the most standard. However, it does look like it works if you choose the right data year -- 2012 ACS 1-year estimates or 5 year estimates -- seems to have all of the information needed. See the [https://factfinder.census.gov/faces/nav/jsf/pages/download_center.xhtml Fact Finder Download Center]. Note that the 1 yr estimates are only available for places with populations of 65,000 people or more, the 1yr supplemental estimates cover down to places with 20,000 people or more, and the 5 yr estimates cover a whopping 29,573 places [https://www.census.gov/programs-surveys/acs/geography-acs/areas-published.html], as compared with just 630 for the 1yr and 2,323 or the 1yr supplements. One can download the PUMS data for 2017 here: https://www2.census.gov/programs-surveys/acs/data/pums/2017/1-Year/ However, PUMS is only available for places in the [https://mcnairen.bakerinstitutewikipedia.org/wiki/PostGIS_InstallationPublic_Use_Microdata_Area Public Use Microdata Areas], which have a population 100,000 or more. And state-by-state, it looks possible to get the latest data profiles (2013-2017 5 yr estimates) but not place by place as data, just as an aggregate:https://www.census.gov/acs/www/data/data-tables-and-tools/data-profiles/ For just population, also see: http://mcnaircensus.bakerinstituteire.org/wikidata/Urban_Start-up_Agglomerationbulkdata.html. This seems to be based on the 2000 or 2010 census data only. =File Location= =New Files= All of the corrected files and the Load.sql script are in: E:\projects\agglomeration\ACS\CleanFiles The Load.sql script was run against [[Vcdb4]] ==Old Files== Python Script to pull certain columns from excel file: *E:\McNair\Projects\Agglomeration\ACS_Downloaded_Data\pullCertainColumns.py SQL Commands to create tables and load data:*E:\McNair\Projects\Agglomeration\ACS_Downloaded_Data\DataLoading_SQL_Commands Excel files downloads from ACS website:*E:\McNair\Projects\Agglomeration\ACS_Downloaded_Data\csvFiles
S1401 SCHOOL ENROLLMENT
American Community Survey (ACS) Data (view source)
Revision as of 13:41, 21 September 2020
, 13:41, 21 September 2020no edit summary
{{Project|Has project output=Data|Has sponsor=McNair ProjectsCenter
|Has title=American Community Survey (ACS) Data
|Has owner=Jeemin Sim,
}}
=Steps to Obtain Data=
11) Press Next
For the new pull, I used 2017 5yr Estimates. =Tables to PullPulled=
S1501 EDUCATIONAL ATTAINMENT
S2301 EMPLOYMENT STATUS
B28011 INTERNET SUBSCRIPTIONS IN HOUSEHOLD
G001 GEOGRAPHIC IDENTIFIERS
At the end, I chose to have full descriptions but not geographic components.
=Notes on Data=
*Educational Attainment are based on population of age 25 years or higher (except for years 2010, 2011, and 2012 - that's why there are fewer entries in those tables)
=Loading to a Dbase=
The zip file from AFF was downloaded and extracted to E:\projects\agglomeration\ACS\AFFFiles
There are 13 files entitled ACS_17_5YR_table_with_ann.csv, where table is S1501, etc. The files have two header lines and are CSV, with quoted strings of the format "Abanda CDP, Alabama" for the display label. There are 5 columns in the first file:
*Geo.id e.g., 1600000US0100100
*GEO.id2 e.g., 0100100
*GEO.display-label e.g., "Abanda CDP, Alabama"
*HD01_VD01 (Estimate; Total) e.g., 174
*HD02_VD01 (Margin of Error; Total) e.g., 158
Geo.id2 appears to match our Geoids. Note the leading zero, so these fields should be converted varchars(7) with front padding.
Checking Geo.id2 of 0103076:
SELECT * from Tigerplaces WHERE geoid='0103076';
statecode statename gid statefp placefp placens geoid name namelsad lsad classfp pcicbsa pcinecta mtfcc funcstat aland awater intptlat intptlon geom
AL Alabama 380 01 03076 02403132 0103076 Auburn Auburn city 25 C1 Y N G4110 A 152375113 2646161 +32.6077220 -085.4895446
1600000US0103076,0103076,"Auburn city, Alabama",61462,65
All files are renamed table.txt and have their second header line removed. The first three columns are common to all files, but then files can have multiple estimate and margin columns. Redundant ones are deleted. The state is also split out. The following are kept:
*B01003 - Population - Total, margin
*B02001 - Race - Total, WhiteAlone, BlackAlone, IndianAlone, AsianAlone, IslanderAlone, OtherAlone, TwoPlus
*B07201 - Moving - Total, Same1yr, DiffinUS1yr, DiffinMSA1yr, Abroad1yr
*B08303 - Driving - Total, Lt5, Btw5And9, Btw10And14, Btw..., Btw60And89, Gt90
*B19013 - HHIncome - MedHHInc2017
*B19053 - SelfEmployment - Total, NumWSelfEmpIncome, NumWOSelfEmpInc
*B19083 - GiniIndex - Gini, margin
*B25003 - Accomodation - Total, Owner, Renter
*B25105 - Housing - monthlyhousingcost
*B28011 - Internet - Total, InternetSub, DialUp, Broadband, Satellite, Other, NoSub, NoInternet
*S1501 - Education - Total25plus, Male25Plus, Female25Plus, Assoc25Plus, Bach25Plus, Grad25Plus, HSOrHigher, BachOrHigher, PCPovertyDueToEdu, MedEarnings
*S2301 - Labor - Total, LFPR, EmpPopRatio, UnEmpRate
