~dricottone/chicago (8058818ab1775985000952de520bcbb8069b7528): data/README.md

#ACS 2021 PUMS

#IPUMS

The ACS databases used here were created and maintained by IPUMS USA, University of Minnesota. Credit for the data belongs with:

Steven Ruggles, Sarah Flood, Matthew Sobek, Danika Brockman, Grace Cooper, Stephanie Richards, and Megan Schouweiler. IPUMS USA: Version 13.0 [dataset]. Minneapolis, MN: IPUMS, 2023. https://doi.org/10.18128/D010.V13.0
Steven Ruggles, Catherine A. Fitch, Ronald Goeken, J. David Hacker, Matt A. Nelson, Evan Roberts, Megan Schouweiler and Matthew Sobek. IPUMS Ancestry Full Count Data: Version 3.0 [dataset]. Minneapolis, MN: IPUMS, 2021. https://doi.org/10.18128/D014.V3.0

#Household Records

Download a hierachical dataset from IPUMS containing these variables:

STATEFIP
PUMA
REPWT
ADJHSG
NP
TEN
VACS
VALP
SVAL
BLD

It should use the ACS 2021 5-year sample.

Optionally, subset the extraction to just Illinois cases (based on STATEFIP). I subset later the cases anyway.

Also collect the SAS read instructions and the basic codebook.

$ gunzip usa_00006.dat.gz
$ wc -l usa_00006.dat
293143 usa_00006.dat

Now I manipulate the codebook into something useful for awk(1).

$ sed -e '11,110!d' usa_00006.cbk | awk '{ print $4 }' | xargs echo
1 4 4 6 8 13 10 1 13 2 5 12 1 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 7 2 2 1 1 7 1

Examine the STATEFIP field. If I hadn't subset cases in the IPUMS portal, I would do that now.

$ awk 'BEGIN {FIELDWIDTHS="1 4 4 6 8 13 10 1 13 2 5 12 1 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 7 2 2 1 1 7 1"} {if ($1=="H"){print $10}}' usa_00006.dat | sort -n | uniq -c
 293143 17

Now subset cases based on the PUMA field.

$ awk 'BEGIN {FIELDWIDTHS="1 4 4 6 8 13 10 1 13 2 5 12 1 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 7 2 2 1 1 7 1"} $11~/035(0[1234]|2[0123456789]|3[012])/' usa_00006.dat >usa_00006_chi.dat
$ wc -l usa_00006_chi.dat
52097 usa_00006_chi.dat

With this, I have a household data file that is restricted to just Chicago.

#Person Records

Download a rectangular dataset from IPUMS containing these variables:

STATEIP
PUMA
REPWTP
HHT
ADJINC
AGEP
FER
JWMNP
JWRIP
JWTRNS
LANX
MAR
MIG
MLPA
MLPB
MLPCD
MLPE
MLPFG
MLPH
MLPJ
SCHL
SEX
HISP
LANP
MIGPUMA
MIGSP
NATIVITY
PINCP
POBP
POVPIP
RAC1P

Follow all the same preparation steps as with the household extraction.

$ wc -l usa_00007.dat
621164 usa_00007.dat
$ sed -e '11,132!d' usa_00007.cbk | awk '{ print $4 }' | xargs echo
4 4 6 8 13 10 13 2 5 12 1 1 4 10 1 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 7 2 1 3 2 2 1 1 1 1 1 1 1 1 1 1 2 1 2 4 5 3 1 7 3 3 1
$ awk 'BEGIN {FIELDWIDTHS="4 4 6 8 13 10 13 2 5 12 1 1 4 10 1 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 7 2 1 3 2 2 1 1 1 1 1 1 1 1 1 1 2 1 2 4 5 3 1 7 3 3 1"} {print $8}' usa_00007.dat | sort -n | uniq -c
 621164 17
$ awk 'BEGIN {FIELDWIDTHS="4 4 6 8 13 10 13 2 5 12 1 1 4 10 1 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 7 2 1 3 2 2 1 1 1 1 1 1 1 1 1 1 2 1 2 4 5 3 1 7 3 3 1"} $9~/035(0[1234]|2[0123456789]|3[012])/' usa_00007.dat >usa_00007_chi.dat
$ wc -l usa_00007_chi.dat 
101501 usa_00007_chi.dat