~dricottone/chicago

6c921d998317cd347436e0afc37b1654401ffb27 — Dominic Ricottone 1 year, 7 months ago
Initial commit

A more-or-less complete replication of the Census Report's Chicago
profile. (Issues are noted in the top-level README.)
A  => README.md +44 -0
@@ 1,44 @@
# Chicago

A demographic and socioeconomic profile of Chicago,
replicating the one displayed on
[Census Reporter](https://censusreporter.org/profiles/16000US1714000-chicago-il/).
Notably that portal uses ACS 1 year estimates, while 5 year estimates for
2021 are available and generally considered more reliable.


## Data

See the `data` directory for more information on obtaining data for this
project. I will not distribute data with this repository.


## Analysis

See the `src` directory for the source code used here.


## Issues and Notes

The continuous data for when a respondent moved into their current housing unit
is not publicly available, so I cannot recreate that table/chart.

I do not presently understand how to replicate *Number of housing units*,
or perhaps more accurately I don't understand how this quantity differs from
*Number of households* in any meaningful, Census-related way.

Something is wrong with the official profile's tabulation of house values.
(See *Value of owner-occupied housing units*).
The easiest way to demonstrate this is to look at the top bucket.
The *Over $1M* item's total is 14,010.
Following the link to Table B25075, however, reveals that 14,010 is the total
for just *$1,000,000 to $1,499,999*.
Potentially this is a matter of topcoding policy differing between the two
backends?

The pandemic caused a few rapid changes to demography.
It took me a while to convince myself that my recreation was not in error.
The most notable table is *Means of transportation*, especially as seen in the
*Worked at home* item.
But other Census Reporter tables corroborate my numbers.


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@@ 1,4 @@
*.dat
*.cbk
*.sas


A  => data/README.md +115 -0
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# 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.

```bash
$ 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)`.

```bash
$ 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.

```bash
$ 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.

```bash
$ 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.

```bash
$ 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
```


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@@ 1,1443 @@
/*
	This is a vendored copy of two import syntax files generated by IPUMS.
		- librefs and filenames are updated
		- duplicative formats are removed
		- scalar formats are removed
		- added some indentation
*/

/* NOTE: updated references */
libname IPUMS "~";
filename dat_h "~/usa_00006_chi.dat";
filename dat_p "~/usa_00007_chi.dat";

proc format cntlout = IPUMS.raw_h_f;
	
	/* NOTE: killed YEAR_f format */
	/* NOTE: killed SAMPLE_f format */
	
	value REPWT_f
	  0 = "Repwt not available"
	  1 = "Repwt available"
	;
	
	value STATEFIP_f
	  01 = "Alabama"
	  02 = "Alaska"
	  04 = "Arizona"
	  05 = "Arkansas"
	  06 = "California"
	  08 = "Colorado"
	  09 = "Connecticut"
	  10 = "Delaware"
	  11 = "District of Columbia"
	  12 = "Florida"
	  13 = "Georgia"
	  15 = "Hawaii"
	  16 = "Idaho"
	  17 = "Illinois"
	  18 = "Indiana"
	  19 = "Iowa"
	  20 = "Kansas"
	  21 = "Kentucky"
	  22 = "Louisiana"
	  23 = "Maine"
	  24 = "Maryland"
	  25 = "Massachusetts"
	  26 = "Michigan"
	  27 = "Minnesota"
	  28 = "Mississippi"
	  29 = "Missouri"
	  30 = "Montana"
	  31 = "Nebraska"
	  32 = "Nevada"
	  33 = "New Hampshire"
	  34 = "New Jersey"
	  35 = "New Mexico"
	  36 = "New York"
	  37 = "North Carolina"
	  38 = "North Dakota"
	  39 = "Ohio"
	  40 = "Oklahoma"
	  41 = "Oregon"
	  42 = "Pennsylvania"
	  44 = "Rhode Island"
	  45 = "South Carolina"
	  46 = "South Dakota"
	  47 = "Tennessee"
	  48 = "Texas"
	  49 = "Utah"
	  50 = "Vermont"
	  51 = "Virginia"
	  53 = "Washington"
	  54 = "West Virginia"
	  55 = "Wisconsin"
	  56 = "Wyoming"
	  61 = "Maine-New Hampshire-Vermont"
	  62 = "Massachusetts-Rhode Island"
	  63 = "Minnesota-Iowa-Missouri-Kansas-Nebraska-S.Dakota-N.Dakota"
	  64 = "Maryland-Delaware"
	  65 = "Montana-Idaho-Wyoming"
	  66 = "Utah-Nevada"
	  67 = "Arizona-New Mexico"
	  68 = "Alaska-Hawaii"
	  72 = "Puerto Rico"
	  97 = "Military/Mil. Reservation"
	  99 = "State not identified"
	;
	
	value GQ_f
	  0 = "Vacant unit"
	  1 = "Households under 1970 definition"
	  2 = "Additional households under 1990 definition"
	  3 = "Group quarters--Institutions"
	  4 = "Other group quarters"
	  5 = "Additional households under 2000 definition"
	  6 = "Fragment"
	;
	
	/* NOTE: killed US2021C_ADJHSG_f format */
	
	value $ US2021C_NP_f
	  "00" = "Vacant unit"
	  "01" = "One person in household or any person in group quarters"
	  "10" = "[no label]"
	  "11" = "[no label]"
	  "12" = "[no label]"
	  "13" = "[no label]"
	  "14" = "[no label]"
	  "15" = "[no label]"
	  "16" = "[no label]"
	  "17" = "[no label]"
	  "18" = "[no label]"
	  "19" = "[no label]"
	  "20" = "[no label]"
	  "B0" = "[no label]"
	  "B1" = "[no label]"
	  "B2" = "[no label]"
	  "B3" = "[no label]"
	  "B4" = "[no label]"
	  "B5" = "[no label]"
	  "B6" = "[no label]"
	  "B7" = "[no label]"
	  "B8" = "[no label]"
	  "B9" = "[no label]"
	  "02" = "[no label]"
	  "03" = "[no label]"
	  "04" = "[no label]"
	  "05" = "[no label]"
	  "06" = "[no label]"
	  "07" = "[no label]"
	  "08" = "[no label]"
	  "09" = "[no label]"
	;
	
	value $ US2021C_BLD_f
	  "BB" = "N/A (GQ)"
	  "01" = "Mobile home or trailer"
	  "02" = "One-family house detached"
	  "03" = "One-family house attached"
	  "04" = "2 Apartments"
	  "05" = "3-4 Apartments"
	  "06" = "5-9 Apartments"
	  "07" = "10-19 Apartments"
	  "08" = "20-49 Apartments"
	  "09" = "50 or more apartments"
	  "10" = "Boat, RV, van, etc."
	;
	
	value $ US2021C_TEN_f
	  "B" = "N/A (GQ/vacant)"
	  "1" = "Owned with mortgage or loan (include home equity loans)"
	  "2" = "Owned free and clear"
	  "3" = "Rented"
	  "4" = "Occupied without payment of rent"
	;
	
	value $ US2021C_VACS_f
	  "B" = "N/A (GQ/occupied)"
	  "1" = "For rent"
	  "2" = "Rented, not occupied"
	  "3" = "For sale only"
	  "4" = "Sold, not occupied"
	  "5" = "For seasonal/recreational/occasional use"
	  "6" = "For migrant workers"
	  "7" = "Other vacant"
	;
	
	value $ US2021C_SVAL_f
	  "B" = "N/A (GQ/ vacant units, except 'for-sale-only' and 'sold, not occupied'/not owned or being bought)"
	  "0" = "A single family home on 10 or more acres or any other type of building, including mobile homes, with"
	        " no regard to acreage."
	  "1" = "A single family home on less than 10 acres."
	;

run;

data IPUMS.raw_h;
	infile dat_h pad missover lrecl=581;
	
	input
	  RECTYPE        $ 1-1 @
	;
	
	if RECTYPE = "H" then do;
	input
	  RECTYPE        $ 1-1
	  YEAR             2-5
	  MULTYEAR         6-9
	  SAMPLE           10-15
	  SERIAL           16-23
	  CBSERIAL         24-36
	  HHWT             37-46 .2
	  REPWT            47-47
	  CLUSTER          48-60
	  STATEFIP         61-62
	  PUMA             63-67
	  STRATA           68-79
	  GQ               80-80
	  REPWT1           81-86
	  REPWT2           87-92
	  REPWT3           93-98
	  REPWT4           99-104
	  REPWT5           105-110
	  REPWT6           111-116
	  REPWT7           117-122
	  REPWT8           123-128
	  REPWT9           129-134
	  REPWT10          135-140
	  REPWT11          141-146
	  REPWT12          147-152
	  REPWT13          153-158
	  REPWT14          159-164
	  REPWT15          165-170
	  REPWT16          171-176
	  REPWT17          177-182
	  REPWT18          183-188
	  REPWT19          189-194
	  REPWT20          195-200
	  REPWT21          201-206
	  REPWT22          207-212
	  REPWT23          213-218
	  REPWT24          219-224
	  REPWT25          225-230
	  REPWT26          231-236
	  REPWT27          237-242
	  REPWT28          243-248
	  REPWT29          249-254
	  REPWT30          255-260
	  REPWT31          261-266
	  REPWT32          267-272
	  REPWT33          273-278
	  REPWT34          279-284
	  REPWT35          285-290
	  REPWT36          291-296
	  REPWT37          297-302
	  REPWT38          303-308
	  REPWT39          309-314
	  REPWT40          315-320
	  REPWT41          321-326
	  REPWT42          327-332
	  REPWT43          333-338
	  REPWT44          339-344
	  REPWT45          345-350
	  REPWT46          351-356
	  REPWT47          357-362
	  REPWT48          363-368
	  REPWT49          369-374
	  REPWT50          375-380
	  REPWT51          381-386
	  REPWT52          387-392
	  REPWT53          393-398
	  REPWT54          399-404
	  REPWT55          405-410
	  REPWT56          411-416
	  REPWT57          417-422
	  REPWT58          423-428
	  REPWT59          429-434
	  REPWT60          435-440
	  REPWT61          441-446
	  REPWT62          447-452
	  REPWT63          453-458
	  REPWT64          459-464
	  REPWT65          465-470
	  REPWT66          471-476
	  REPWT67          477-482
	  REPWT68          483-488
	  REPWT69          489-494
	  REPWT70          495-500
	  REPWT71          501-506
	  REPWT72          507-512
	  REPWT73          513-518
	  REPWT74          519-524
	  REPWT75          525-530
	  REPWT76          531-536
	  REPWT77          537-542
	  REPWT78          543-548
	  REPWT79          549-554
	  REPWT80          555-560
	  US2021C_ADJHSG   561-567 .6 /* NOTE: changed informat from string to 8.6 numeric */
	  US2021C_NP     $ 568-569
	  US2021C_BLD    $ 570-571
	  US2021C_TEN    $ 572-572
	  US2021C_VACS   $ 573-573
	  US2021C_VALP   $ 574-580
	  US2021C_SVAL   $ 581-581
	;
	output;
	end;
	
	label
	  RECTYPE        = "Record type"
	  YEAR           = "Census year"
	  MULTYEAR       = "Actual year of survey, multi-year ACS/PRCS"
	  SAMPLE         = "IPUMS sample identifier"
	  SERIAL         = "Household serial number"
	  CBSERIAL       = "Original Census Bureau household serial number"
	  HHWT           = "Household weight"
	  REPWT          = "Household replicate weights [80 variables]"
	  CLUSTER        = "Household cluster for variance estimation"
	  STATEFIP       = "State (FIPS code)"
	  PUMA           = "Public Use Microdata Area"
	  STRATA         = "Household strata for variance estimation"
	  GQ             = "Group quarters status"
	  REPWT1         = "Household replicate weight 1"
	  REPWT2         = "Household replicate weight 2"
	  REPWT3         = "Household replicate weight 3"
	  REPWT4         = "Household replicate weight 4"
	  REPWT5         = "Household replicate weight 5"
	  REPWT6         = "Household replicate weight 6"
	  REPWT7         = "Household replicate weight 7"
	  REPWT8         = "Household replicate weight 8"
	  REPWT9         = "Household replicate weight 9"
	  REPWT10        = "Household replicate weight 10"
	  REPWT11        = "Household replicate weight 11"
	  REPWT12        = "Household replicate weight 12"
	  REPWT13        = "Household replicate weight 13"
	  REPWT14        = "Household replicate weight 14"
	  REPWT15        = "Household replicate weight 15"
	  REPWT16        = "Household replicate weight 16"
	  REPWT17        = "Household replicate weight 17"
	  REPWT18        = "Household replicate weight 18"
	  REPWT19        = "Household replicate weight 19"
	  REPWT20        = "Household replicate weight 20"
	  REPWT21        = "Household replicate weight 21"
	  REPWT22        = "Household replicate weight 22"
	  REPWT23        = "Household replicate weight 23"
	  REPWT24        = "Household replicate weight 24"
	  REPWT25        = "Household replicate weight 25"
	  REPWT26        = "Household replicate weight 26"
	  REPWT27        = "Household replicate weight 27"
	  REPWT28        = "Household replicate weight 28"
	  REPWT29        = "Household replicate weight 29"
	  REPWT30        = "Household replicate weight 30"
	  REPWT31        = "Household replicate weight 31"
	  REPWT32        = "Household replicate weight 32"
	  REPWT33        = "Household replicate weight 33"
	  REPWT34        = "Household replicate weight 34"
	  REPWT35        = "Household replicate weight 35"
	  REPWT36        = "Household replicate weight 36"
	  REPWT37        = "Household replicate weight 37"
	  REPWT38        = "Household replicate weight 38"
	  REPWT39        = "Household replicate weight 39"
	  REPWT40        = "Household replicate weight 40"
	  REPWT41        = "Household replicate weight 41"
	  REPWT42        = "Household replicate weight 42"
	  REPWT43        = "Household replicate weight 43"
	  REPWT44        = "Household replicate weight 44"
	  REPWT45        = "Household replicate weight 45"
	  REPWT46        = "Household replicate weight 46"
	  REPWT47        = "Household replicate weight 47"
	  REPWT48        = "Household replicate weight 48"
	  REPWT49        = "Household replicate weight 49"
	  REPWT50        = "Household replicate weight 50"
	  REPWT51        = "Household replicate weight 51"
	  REPWT52        = "Household replicate weight 52"
	  REPWT53        = "Household replicate weight 53"
	  REPWT54        = "Household replicate weight 54"
	  REPWT55        = "Household replicate weight 55"
	  REPWT56        = "Household replicate weight 56"
	  REPWT57        = "Household replicate weight 57"
	  REPWT58        = "Household replicate weight 58"
	  REPWT59        = "Household replicate weight 59"
	  REPWT60        = "Household replicate weight 60"
	  REPWT61        = "Household replicate weight 61"
	  REPWT62        = "Household replicate weight 62"
	  REPWT63        = "Household replicate weight 63"
	  REPWT64        = "Household replicate weight 64"
	  REPWT65        = "Household replicate weight 65"
	  REPWT66        = "Household replicate weight 66"
	  REPWT67        = "Household replicate weight 67"
	  REPWT68        = "Household replicate weight 68"
	  REPWT69        = "Household replicate weight 69"
	  REPWT70        = "Household replicate weight 70"
	  REPWT71        = "Household replicate weight 71"
	  REPWT72        = "Household replicate weight 72"
	  REPWT73        = "Household replicate weight 73"
	  REPWT74        = "Household replicate weight 74"
	  REPWT75        = "Household replicate weight 75"
	  REPWT76        = "Household replicate weight 76"
	  REPWT77        = "Household replicate weight 77"
	  REPWT78        = "Household replicate weight 78"
	  REPWT79        = "Household replicate weight 79"
	  REPWT80        = "Household replicate weight 80"
	  US2021C_ADJHSG = "Adjustment factor for housing dollar amounts (6 implied decimal places)"
	  US2021C_NP     = "Number of persons in this household"
	  US2021C_BLD    = "Units in structure"
	  US2021C_TEN    = "Tenure"
	  US2021C_VACS   = "Vacancy status"
	  US2021C_VALP   = "Property value"
	  US2021C_SVAL   = "Specified owner unit"
	;
	
	format
	  REPWT           REPWT_f.
	  STATEFIP        STATEFIP_f.
	  GQ              GQ_f.
	  US2021C_NP      US2021C_NP_f.
	  US2021C_BLD     US2021C_BLD_f.
	  US2021C_TEN     US2021C_TEN_f.
	  US2021C_VACS    US2021C_VACS_f.
	  US2021C_SVAL    US2021C_SVAL_f.
	;
	
	format
	  CBSERIAL        13.
	  HHWT            11.2
	  CLUSTER         13.
	  STRATA          12.
	;

run;

proc format cntlout = IPUMS.raw_p_f;
	
	/* NOTE: killed YEAR_f format */
	/* NOTE: killed SAMPLE_f format */
	
	value STATEFIP_f
	  01 = "Alabama"
	  02 = "Alaska"
	  04 = "Arizona"
	  05 = "Arkansas"
	  06 = "California"
	  08 = "Colorado"
	  09 = "Connecticut"
	  10 = "Delaware"
	  11 = "District of Columbia"
	  12 = "Florida"
	  13 = "Georgia"
	  15 = "Hawaii"
	  16 = "Idaho"
	  17 = "Illinois"
	  18 = "Indiana"
	  19 = "Iowa"
	  20 = "Kansas"
	  21 = "Kentucky"
	  22 = "Louisiana"
	  23 = "Maine"
	  24 = "Maryland"
	  25 = "Massachusetts"
	  26 = "Michigan"
	  27 = "Minnesota"
	  28 = "Mississippi"
	  29 = "Missouri"
	  30 = "Montana"
	  31 = "Nebraska"
	  32 = "Nevada"
	  33 = "New Hampshire"
	  34 = "New Jersey"
	  35 = "New Mexico"
	  36 = "New York"
	  37 = "North Carolina"
	  38 = "North Dakota"
	  39 = "Ohio"
	  40 = "Oklahoma"
	  41 = "Oregon"
	  42 = "Pennsylvania"
	  44 = "Rhode Island"
	  45 = "South Carolina"
	  46 = "South Dakota"
	  47 = "Tennessee"
	  48 = "Texas"
	  49 = "Utah"
	  50 = "Vermont"
	  51 = "Virginia"
	  53 = "Washington"
	  54 = "West Virginia"
	  55 = "Wisconsin"
	  56 = "Wyoming"
	  61 = "Maine-New Hampshire-Vermont"
	  62 = "Massachusetts-Rhode Island"
	  63 = "Minnesota-Iowa-Missouri-Kansas-Nebraska-S.Dakota-N.Dakota"
	  64 = "Maryland-Delaware"
	  65 = "Montana-Idaho-Wyoming"
	  66 = "Utah-Nevada"
	  67 = "Arizona-New Mexico"
	  68 = "Alaska-Hawaii"
	  72 = "Puerto Rico"
	  97 = "Military/Mil. Reservation"
	  99 = "State not identified"
	;
	
	value GQ_f
	  0 = "Vacant unit"
	  1 = "Households under 1970 definition"
	  2 = "Additional households under 1990 definition"
	  3 = "Group quarters--Institutions"
	  4 = "Other group quarters"
	  5 = "Additional households under 2000 definition"
	  6 = "Fragment"
	;
	
	value $ US2021C_HHT_f
	  "B" = "N/A (GQ/vacant)"
	  "1" = "Married couple household"
	  "2" = "Other family household: Male householder, no spouse present"
	  "3" = "Other family household: Female householder, no spouse present"
	  "4" = "Nonfamily household: Male householder: Living alone"
	  "5" = "Nonfamily household: Male householder: Not living alone"
	  "6" = "Nonfamily household: Female householder: Living alone"
	  "7" = "Nonfamily household: Female householder: Not living alone"
	;
	
	value REPWTP_f
	  0 = "Repwtp not available"
	  1 = "Repwtp available"
	;
	
	/* NOTE: killed US2021C_ADJINCP_f format */
	
	/* NOTE: killed US2021C_AGEP_f format */
	
	value $ US2021C_FER_f
	  "B" = "N/A (less than 15 years/greater than 50 years/ male)"
	  "1" = "Yes"
	  "2" = "No"
	;
	
	/* NOTE: killed US2021C_JWMNP_f format */
	
	/* NOTE: killed US2021C_JWRIP_f format */
	
	value $ US2021C_JWTRNS_f
	  "BB" = "N/A (not a worker-not in the labor force, including persons under 16 years; unemployed; employed, wi"
	         "th a job but not at work; Armed Forces, with a job but not at work)"
	  "01" = "Car, truck, or van"
	  "02" = "Bus"
	  "03" = "Subway or elevated rail"
	  "04" = "Long-distance train or commuter rail"
	  "05" = "Light rail, streetcar, or trolley"
	  "06" = "Ferryboat"
	  "07" = "Taxicab"
	  "08" = "Motorcycle"
	  "09" = "Bicycle"
	  "10" = "Walked"
	  "11" = "Worked from home"
	  "12" = "Other method"
	;
	
	value $ US2021C_LANX_f
	  "B" = "N/A (less than 5 years old)"
	  "1" = "Yes, speaks another language"
	  "2" = "No, speaks only English"
	;
	
	value $ US2021C_MAR_f
	  "1" = "Married"
	  "2" = "Widowed"
	  "3" = "Divorced"
	  "4" = "Separated"
	  "5" = "Never married or under 15 years old"
	;
	
	value $ US2021C_MIG_f
	  "B" = "N/A (less than 1 year old)"
	  "1" = "Yes, same house (nonmovers)"
	  "2" = "No, outside US and Puerto Rico"
	  "3" = "No, different house in US or Puerto Rico"
	;
	
	value $ US2021C_MLPA_f
	  "B" = "N/A (less than 17 years old/no active duty)"
	  "0" = "Did not serve this period"
	  "1" = "Served this period"
	;
	
	value $ US2021C_MLPB_f
	  "B" = "N/A (less than 17 years old/no active duty)"
	  "0" = "Did not serve this period"
	  "1" = "Served this period"
	;
	
	value $ US2021C_MLPCD_f
	  "B" = "N/A (less than 17 years old/no active duty)"
	  "0" = "Did not serve this period"
	  "1" = "Served this period"
	;
	
	value $ US2021C_MLPE_f
	  "B" = "N/A (less than 17 years old/no active duty)"
	  "0" = "Did not serve this period"
	  "1" = "Served this period"
	;
	
	value $ US2021C_MLPFG_f
	  "B" = "N/A (less than 17 years old/no active duty)"
	  "0" = "Did not serve this period"
	  "1" = "Served this period"
	;
	
	value $ US2021C_MLPH_f
	  "B" = "N/A (less than 17 years old/no active duty)"
	  "0" = "Did not serve this period"
	  "1" = "Served this period"
	;
	
	value $ US2021C_MLPJ_f
	  "B" = "N/A (less than 17 years old/no active duty)"
	  "0" = "Did not serve this period"
	  "1" = "Served this period"
	;
	
	value $ US2021C_SCHL_f
	  "BB" = "N/A (less than 3 years old)"
	  "01" = "No schooling completed"
	  "02" = "Nursery school, preschool"
	  "03" = "Kindergarten"
	  "04" = "Grade 1"
	  "05" = "Grade 2"
	  "06" = "Grade 3"
	  "07" = "Grade 4"
	  "08" = "Grade 5"
	  "09" = "Grade 6"
	  "10" = "Grade 7"
	  "11" = "Grade 8"
	  "12" = "Grade 9"
	  "13" = "Grade 10"
	  "14" = "Grade 11"
	  "15" = "12th grade - no diploma"
	  "16" = "Regular high school diploma"
	  "17" = "GED or alternative credential"
	  "18" = "Some college, but less than 1 year"
	  "19" = "1 or more years of college credit, no degree"
	  "20" = "Associate's degree"
	  "21" = "Bachelor's degree"
	  "22" = "Master's degree"
	  "23" = "Professional degree beyond a bachelor's degree"
	  "24" = "Doctorate degree"
	;
	
	value $ US2021C_SEX_f
	  "1" = "Male"
	  "2" = "Female"
	;
	
	value $ US2021C_HISP_f
	  "01" = "Not Spanish/Hispanic/Latino"
	  "02" = "Mexican"
	  "03" = "Puerto Rican"
	  "04" = "Cuban"
	  "05" = "Dominican"
	  "06" = "Costa Rican"
	  "07" = "Guatemalan"
	  "08" = "Honduran"
	  "09" = "Nicaraguan"
	  "10" = "Panamanian"
	  "11" = "Salvadoran"
	  "12" = "Other Central American"
	  "13" = "Argentinean"
	  "14" = "Bolivian"
	  "15" = "Chilean"
	  "16" = "Colombian"
	  "17" = "Ecuadorian"
	  "18" = "Paraguayan"
	  "19" = "Peruvian"
	  "20" = "Uruguayan"
	  "21" = "Venezuelan"
	  "22" = "Other South American"
	  "23" = "Spaniard"
	  "24" = "All Other Spanish/Hispanic/Latino"
	;
	
	value $ US2021C_LANP_f
	  "BBBB" = "N/A (GQ/vacant)"
	  "1000" = "Jamaican Creole English"
	  "1025" = "Other English-based Creole languages"
	  "1055" = "Haitian"
	  "1069" = "Kabuverdianu"
	  "1110" = "German"
	  "1120" = "Swiss German"
	  "1125" = "Pennsylvania German"
	  "1130" = "Yiddish"
	  "1132" = "Dutch"
	  "1134" = "Afrikaans"
	  "1140" = "Swedish"
	  "1141" = "Danish"
	  "1142" = "Norwegian"
	  "1155" = "Italian"
	  "1170" = "French"
	  "1175" = "Cajun French"
	  "1200" = "Spanish"
	  "1210" = "Portuguese"
	  "1220" = "Romanian"
	  "1231" = "Irish"
	  "1235" = "Greek"
	  "1242" = "Albanian"
	  "1250" = "Russian"
	  "1260" = "Ukrainian"
	  "1262" = "Czech"
	  "1263" = "Slovak"
	  "1270" = "Polish"
	  "1273" = "Bulgarian"
	  "1274" = "Macedonian"
	  "1275" = "Serbocroatian"
	  "1276" = "Bosnian"
	  "1277" = "Croatian"
	  "1278" = "Serbian"
	  "1281" = "Lithuanian"
	  "1283" = "Latvian"
	  "1288" = "Armenian"
	  "1290" = "Farsi"
	  "1292" = "Dari"
	  "1315" = "Kurdish"
	  "1327" = "Pashto"
	  "1340" = "India N.E.C."
	  "1350" = "Hindi"
	  "1360" = "Urdu"
	  "1380" = "Bengali"
	  "1420" = "Punjabi"
	  "1435" = "Konkani"
	  "1440" = "Marathi"
	  "1450" = "Gujarati"
	  "1500" = "Nepali"
	  "1525" = "Pakistan N.E.C."
	  "1530" = "Sinhala"
	  "1540" = "Other Indo-Iranian languages"
	  "1564" = "Other Indo-European languages"
	  "1565" = "Finnish"
	  "1582" = "Hungarian"
	  "1675" = "Turkish"
	  "1690" = "Mongolian"
	  "1730" = "Telugu"
	  "1737" = "Kannada"
	  "1750" = "Malayalam"
	  "1765" = "Tamil"
	  "1900" = "Khmer"
	  "1960" = "Vietnamese"
	  "1970" = "Chinese"
	  "2000" = "Mandarin"
	  "2030" = "Min Nan Chinese"
	  "2050" = "Cantonese"
	  "2100" = "Tibetan"
	  "2160" = "Burmese"
	  "2270" = "Chin languages"
	  "2350" = "Karen languages"
	  "2430" = "Thai"
	  "2475" = "Lao"
	  "2525" = "Iu Mien"
	  "2535" = "Hmong"
	  "2560" = "Japanese"
	  "2575" = "Korean"
	  "2715" = "Malay"
	  "2770" = "Indonesian"
	  "2850" = "Other languages of Asia"
	  "2910" = "Filipino"
	  "2920" = "Tagalog"
	  "2950" = "Cebuano"
	  "3150" = "Ilocano"
	  "3190" = "Other Philippine languages"
	  "3220" = "Chamorro"
	  "3270" = "Marshallese"
	  "3350" = "Chuukese"
	  "3420" = "Samoan"
	  "3500" = "Tongan"
	  "3570" = "Hawaiian"
	  "3600" = "Other Eastern Malayo-Polynesian languages"
	  "4500" = "Arabic"
	  "4545" = "Hebrew"
	  "4560" = "Assyrian Neo-Aramaic"
	  "4565" = "Chaldean Neo-Aramaic"
	  "4590" = "Amharic"
	  "4640" = "Tigrinya"
	  "4830" = "Oromo"
	  "4840" = "Somali"
	  "4880" = "Other Afro-Asiatic languages"
	  "4900" = "Nilo-Saharan languages"
	  "5150" = "Swahili"
	  "5345" = "Ganda"
	  "5525" = "Shona"
	  "5645" = "Other Bantu languages"
	  "5845" = "Manding languages"
	  "5900" = "Other Mande languages"
	  "5940" = "Fulah"
	  "5950" = "Wolof"
	  "6120" = "Akan (incl. Twi)"
	  "6205" = "Ga"
	  "6230" = "Gbe languages"
	  "6290" = "Yoruba"
	  "6300" = "Edoid languages"
	  "6370" = "Igbo"
	  "6500" = "Other Niger-Congo languages"
	  "6795" = "Other languages of Africa"
	  "6800" = "Aleut languages"
	  "6839" = "Ojibwa"
	  "6930" = "Apache languages"
	  "6933" = "Navajo"
	  "7019" = "Dakota languages"
	  "7032" = "Muskogean languages"
	  "7039" = "Keres"
	  "7050" = "Cherokee"
	  "7060" = "Uto-Aztecan languages"
	  "7124" = "Other Native North American languages"
	  "7300" = "Other Central and South American languages"
	  "9999" = "Other and unspecified languages"
	;
	
	value $ US2021C_MIGSP_f
	  "BBB" = "N/A (person less than 1 year old/lived in same house 1 year ago)"
	  "001" = "Alabama/AL"
	  "002" = "Alaska/AK"
	  "004" = "Arizona/AZ"
	  "005" = "Arkansas/AR"
	  "006" = "California/CA"
	  "008" = "Colorado/CO"
	  "009" = "Connecticut/CT"
	  "010" = "Delaware/DE"
	  "011" = "District of Columbia/DC"
	  "012" = "Florida/FL"
	  "013" = "Georgia/GA"
	  "015" = "Hawaii/HI"
	  "016" = "Idaho/ID"
	  "017" = "Illinois/IL"
	  "018" = "Indiana/IN"
	  "019" = "Iowa/IA"
	  "020" = "Kansas/KS"
	  "021" = "Kentucky/KY"
	  "022" = "Louisiana/LA"
	  "023" = "Maine/ME"
	  "024" = "Maryland/MD"
	  "025" = "Massachusetts/MA"
	  "026" = "Michigan/MI"
	  "027" = "Minnesota/MN"
	  "028" = "Mississippi/MS"
	  "029" = "Missouri/MO"
	  "030" = "Montana/MT"
	  "031" = "Nebraska/NE"
	  "032" = "Nevada/NV"
	  "033" = "New Hampshire/NH"
	  "034" = "New Jersey/NJ"
	  "035" = "New Mexico/NM"
	  "036" = "New York/NY"
	  "037" = "North Carolina/NC"
	  "038" = "North Dakota/ND"
	  "039" = "Ohio/OH"
	  "040" = "Oklahoma/OK"
	  "041" = "Oregon/OR"
	  "042" = "Pennsylvania/PA"
	  "044" = "Rhode Island/RI"
	  "045" = "South Carolina/SC"
	  "046" = "South Dakota/SD"
	  "047" = "Tennessee/TN"
	  "048" = "Texas/TX"
	  "049" = "Utah/UT"
	  "050" = "Vermont/VT"
	  "051" = "Virginia/VA"
	  "053" = "Washington/WA"
	  "054" = "West Virginia/WV"
	  "055" = "Wisconsin/WI"
	  "056" = "Wyoming/WY"
	  "072" = "Puerto Rico"
	  "109" = "France"
	  "110" = "Germany"
	  "111" = "Northern Europe, Not Specified"
	  "113" = "Eastern Europe, Not Specified"
	  "114" = "Western Europe or Other Europe, Not Specified"
	  "120" = "Italy"
	  "134" = "Spain"
	  "138" = "United Kingdom, Excluding England"
	  "139" = "England"
	  "163" = "Russia"
	  "164" = "Ukraine"
	  "200" = "Afghanistan"
	  "207" = "China, Hong Kong, Macau And Paracel Islands"
	  "210" = "India"
	  "214" = "Israel"
	  "215" = "Japan"
	  "217" = "Korea"
	  "229" = "Nepal"
	  "231" = "Pakistan"
	  "233" = "Philippines"
	  "235" = "Saudi Arabia"
	  "240" = "Taiwan"
	  "242" = "Thailand"
	  "243" = "Turkey"
	  "245" = "United Arab Emirates"
	  "247" = "Vietnam"
	  "251" = "Eastern Asia, Not Specified"
	  "252" = "Western Asia, Not Specified"
	  "253" = "South Central Asia or Asia, Not Specified"
	  "301" = "Canada"
	  "303" = "Mexico"
	  "312" = "El Salvador"
	  "313" = "Guatemala"
	  "314" = "Honduras"
	  "317" = "Central America, Not Specified"
	  "327" = "Cuba"
	  "329" = "Dominican Republic"
	  "332" = "Haiti"
	  "333" = "Jamaica"
	  "344" = "Caribbean and North America, Not Specified"
	  "362" = "Brazil"
	  "364" = "Colombia"
	  "365" = "Ecuador"
	  "370" = "Peru"
	  "373" = "Venezuela"
	  "374" = "South America, Not Specified"
	  "414" = "Egypt"
	  "416" = "Ethiopia"
	  "427" = "Kenya"
	  "440" = "Nigeria"
	  "467" = "Western Africa, Not Specified"
	  "468" = "Other Africa, Not Specified"
	  "469" = "Eastern Africa, Not Specified"
	  "501" = "Australia"
	  "555" = "Other US Island Areas, Oceania, Not Specified, or At Sea"
	;
	
	value $ US2021C_NATIVITY_f
	  "1" = "Native"
	  "2" = "Foreign born"
	;
	
	value $ US2021C_POBP_f
	  "001" = "Alabama/AL"
	  "002" = "Alaska/AK"
	  "004" = "Arizona/AZ"
	  "005" = "Arkansas/AR"
	  "006" = "California/CA"
	  "008" = "Colorado/CO"
	  "009" = "Connecticut/CT"
	  "010" = "Delaware/DE"
	  "011" = "District of Columbia/DC"
	  "012" = "Florida/FL"
	  "013" = "Georgia/GA"
	  "015" = "Hawaii/HI"
	  "016" = "Idaho/ID"
	  "017" = "Illinois/IL"
	  "018" = "Indiana/IN"
	  "019" = "Iowa/IA"
	  "020" = "Kansas/KS"
	  "021" = "Kentucky/KY"
	  "022" = "Louisiana/LA"
	  "023" = "Maine/ME"
	  "024" = "Maryland/MD"
	  "025" = "Massachusetts/MA"
	  "026" = "Michigan/MI"
	  "027" = "Minnesota/MN"
	  "028" = "Mississippi/MS"
	  "029" = "Missouri/MO"
	  "030" = "Montana/MT"
	  "031" = "Nebraska/NE"
	  "032" = "Nevada/NV"
	  "033" = "New Hampshire/NH"
	  "034" = "New Jersey/NJ"
	  "035" = "New Mexico/NM"
	  "036" = "New York/NY"
	  "037" = "North Carolina/NC"
	  "038" = "North Dakota/ND"
	  "039" = "Ohio/OH"
	  "040" = "Oklahoma/OK"
	  "041" = "Oregon/OR"
	  "042" = "Pennsylvania/PA"
	  "044" = "Rhode Island/RI"
	  "045" = "South Carolina/SC"
	  "046" = "South Dakota/SD"
	  "047" = "Tennessee/TN"
	  "048" = "Texas/TX"
	  "049" = "Utah/UT"
	  "050" = "Vermont/VT"
	  "051" = "Virginia/VA"
	  "053" = "Washington/WA"
	  "054" = "West Virginia/WV"
	  "055" = "Wisconsin/WI"
	  "056" = "Wyoming/WY"
	  "060" = "American Samoa"
	  "066" = "Guam"
	  "069" = "Commonwealth of the Northern Mariana Islands"
	  "072" = "Puerto Rico"
	  "078" = "US Virgin Islands"
	  "100" = "Albania"
	  "102" = "Austria"
	  "103" = "Belgium"
	  "104" = "Bulgaria"
	  "105" = "Czechoslovakia"
	  "106" = "Denmark"
	  "108" = "Finland"
	  "109" = "France"
	  "110" = "Germany"
	  "116" = "Greece"
	  "117" = "Hungary"
	  "118" = "Iceland"
	  "119" = "Ireland"
	  "120" = "Italy"
	  "126" = "Netherlands"
	  "127" = "Norway"
	  "128" = "Poland"
	  "129" = "Portugal"
	  "130" = "Azores Islands"
	  "132" = "Romania"
	  "134" = "Spain"
	  "136" = "Sweden"
	  "137" = "Switzerland"
	  "138" = "United Kingdom, Not Specified"
	  "139" = "England"
	  "140" = "Scotland"
	  "142" = "Northern Ireland"
	  "147" = "Yugoslavia"
	  "148" = "Czech Republic"
	  "149" = "Slovakia"
	  "150" = "Bosnia and Herzegovina"
	  "151" = "Croatia"
	  "152" = "Macedonia"
	  "154" = "Serbia"
	  "156" = "Latvia"
	  "157" = "Lithuania"
	  "158" = "Armenia"
	  "159" = "Azerbaijan"
	  "160" = "Belarus"
	  "161" = "Georgia"
	  "162" = "Moldova"
	  "163" = "Russia"
	  "164" = "Ukraine"
	  "165" = "USSR"
	  "166" = "Europe"
	  "167" = "Kosovo"
	  "168" = "Montenegro"
	  "169" = "Other Europe, Not Specified"
	  "200" = "Afghanistan"
	  "202" = "Bangladesh"
	  "203" = "Bhutan"
	  "205" = "Myanmar"
	  "206" = "Cambodia"
	  "207" = "China"
	  "209" = "Hong Kong"
	  "210" = "India"
	  "211" = "Indonesia"
	  "212" = "Iran"
	  "213" = "Iraq"
	  "214" = "Israel"
	  "215" = "Japan"
	  "216" = "Jordan"
	  "217" = "Korea"
	  "218" = "Kazakhstan"
	  "219" = "Kyrgyzstan"
	  "222" = "Kuwait"
	  "223" = "Laos"
	  "224" = "Lebanon"
	  "226" = "Malaysia"
	  "228" = "Mongolia"
	  "229" = "Nepal"
	  "231" = "Pakistan"
	  "233" = "Philippines"
	  "235" = "Saudi Arabia"
	  "236" = "Singapore"
	  "238" = "Sri Lanka"
	  "239" = "Syria"
	  "240" = "Taiwan"
	  "242" = "Thailand"
	  "243" = "Turkey"
	  "245" = "United Arab Emirates"
	  "246" = "Uzbekistan"
	  "247" = "Vietnam"
	  "248" = "Yemen"
	  "249" = "Asia"
	  "253" = "South Central Asia, Not Specified"
	  "254" = "Other Asia, Not Specified"
	  "300" = "Bermuda"
	  "301" = "Canada"
	  "303" = "Mexico"
	  "310" = "Belize"
	  "311" = "Costa Rica"
	  "312" = "El Salvador"
	  "313" = "Guatemala"
	  "314" = "Honduras"
	  "315" = "Nicaragua"
	  "316" = "Panama"
	  "321" = "Antigua and Barbuda"
	  "323" = "Bahamas"
	  "324" = "Barbados"
	  "327" = "Cuba"
	  "328" = "Dominica"
	  "329" = "Dominican Republic"
	  "330" = "Grenada"
	  "332" = "Haiti"
	  "333" = "Jamaica"
	  "338" = "St. Kitts-Nevis"
	  "339" = "St. Lucia"
	  "340" = "St. Vincent and the Grenadines"
	  "341" = "Trinidad and Tobago"
	  "343" = "West Indies"
	  "344" = "Caribbean, Not Specified"
	  "360" = "Argentina"
	  "361" = "Bolivia"
	  "362" = "Brazil"
	  "363" = "Chile"
	  "364" = "Colombia"
	  "365" = "Ecuador"
	  "368" = "Guyana"
	  "369" = "Paraguay"
	  "370" = "Peru"
	  "372" = "Uruguay"
	  "373" = "Venezuela"
	  "374" = "South America"
	  "399" = "Americas, Not Specified"
	  "400" = "Algeria"
	  "407" = "Cameroon"
	  "408" = "Cabo Verde"
	  "412" = "Congo"
	  "414" = "Egypt"
	  "416" = "Ethiopia"
	  "417" = "Eritrea"
	  "420" = "Gambia"
	  "421" = "Ghana"
	  "423" = "Guinea"
	  "425" = "Ivory Coast"
	  "427" = "Kenya"
	  "429" = "Liberia"
	  "430" = "Libya"
	  "436" = "Morocco"
	  "440" = "Nigeria"
	  "442" = "Rwanda"
	  "444" = "Senegal"
	  "447" = "Sierra Leone"
	  "448" = "Somalia"
	  "449" = "South Africa"
	  "451" = "Sudan"
	  "453" = "Tanzania"
	  "454" = "Togo"
	  "456" = "Tunisia"
	  "457" = "Uganda"
	  "459" = "Democratic Republic of Congo (Zaire)"
	  "460" = "Zambia"
	  "461" = "Zimbabwe"
	  "462" = "Africa"
	  "463" = "South Sudan"
	  "464" = "Northern Africa, Not Specified"
	  "467" = "Western Africa, Not Specified"
	  "468" = "Other Africa, Not Specified"
	  "469" = "Eastern Africa, Not Specified"
	  "501" = "Australia"
	  "508" = "Fiji"
	  "511" = "Marshall Islands"
	  "512" = "Micronesia"
	  "515" = "New Zealand"
	  "523" = "Tonga"
	  "527" = "Samoa"
	  "554" = "Other US Island Areas, Oceania, Not Specified, or at Sea"
	;
	
	value $ US2021C_RAC1P_f
	  "1" = "White alone"
	  "2" = "Black or African American alone"
	  "3" = "American Indian alone"
	  "4" = "Alaska Native alone"
	  "5" = "American Indian and Alaska Native tribes specified; or American Indian or Alaska Native, not specifi"
	        "ed and no other races"
	  "6" = "Asian alone"
	  "7" = "Native Hawaiian and Other Pacific Islander alone"
	  "8" = "Some Other Race alone"
	  "9" = "Two or More Races"
	;

run;

data IPUMS.raw_p;
	infile dat_p pad missover lrecl=633;
	
	input
	  YEAR               1-4
	  MULTYEAR           5-8
	  SAMPLE             9-14
	  SERIAL             15-22
	  CBSERIAL           23-35
	  HHWT               36-45 .2
	  CLUSTER            46-58
	  STATEFIP           59-60
	  PUMA               61-65
	  STRATA             66-77
	  GQ                 78-78
	  US2021C_HHT      $ 79-79
	  PERNUM             80-83
	  PERWT              84-93 .2
	  REPWTP             94-94
	  REPWTP1            95-100
	  REPWTP2            101-106
	  REPWTP3            107-112
	  REPWTP4            113-118
	  REPWTP5            119-124
	  REPWTP6            125-130
	  REPWTP7            131-136
	  REPWTP8            137-142
	  REPWTP9            143-148
	  REPWTP10           149-154
	  REPWTP11           155-160
	  REPWTP12           161-166
	  REPWTP13           167-172
	  REPWTP14           173-178
	  REPWTP15           179-184
	  REPWTP16           185-190
	  REPWTP17           191-196
	  REPWTP18           197-202
	  REPWTP19           203-208
	  REPWTP20           209-214
	  REPWTP21           215-220
	  REPWTP22           221-226
	  REPWTP23           227-232
	  REPWTP24           233-238
	  REPWTP25           239-244
	  REPWTP26           245-250
	  REPWTP27           251-256
	  REPWTP28           257-262
	  REPWTP29           263-268
	  REPWTP30           269-274
	  REPWTP31           275-280
	  REPWTP32           281-286
	  REPWTP33           287-292
	  REPWTP34           293-298
	  REPWTP35           299-304
	  REPWTP36           305-310
	  REPWTP37           311-316
	  REPWTP38           317-322
	  REPWTP39           323-328
	  REPWTP40           329-334
	  REPWTP41           335-340
	  REPWTP42           341-346
	  REPWTP43           347-352
	  REPWTP44           353-358
	  REPWTP45           359-364
	  REPWTP46           365-370
	  REPWTP47           371-376
	  REPWTP48           377-382
	  REPWTP49           383-388
	  REPWTP50           389-394
	  REPWTP51           395-400
	  REPWTP52           401-406
	  REPWTP53           407-412
	  REPWTP54           413-418
	  REPWTP55           419-424
	  REPWTP56           425-430
	  REPWTP57           431-436
	  REPWTP58           437-442
	  REPWTP59           443-448
	  REPWTP60           449-454
	  REPWTP61           455-460
	  REPWTP62           461-466
	  REPWTP63           467-472
	  REPWTP64           473-478
	  REPWTP65           479-484
	  REPWTP66           485-490
	  REPWTP67           491-496
	  REPWTP68           497-502
	  REPWTP69           503-508
	  REPWTP70           509-514
	  REPWTP71           515-520
	  REPWTP72           521-526
	  REPWTP73           527-532
	  REPWTP74           533-538
	  REPWTP75           539-544
	  REPWTP76           545-550
	  REPWTP77           551-556
	  REPWTP78           557-562
	  REPWTP79           563-568
	  REPWTP80           569-574
	  US2021C_ADJINCP    575-581 .6 /* NOTE: changed informat from string to 8.6 numeric */
	  US2021C_AGEP     $ 582-583
	  US2021C_FER      $ 584-584
	  US2021C_JWMNP    $ 585-587
	  US2021C_JWRIP    $ 588-589
	  US2021C_JWTRNS   $ 590-591
	  US2021C_LANX     $ 592-592
	  US2021C_MAR      $ 593-593
	  US2021C_MIG      $ 594-594
	  US2021C_MLPA     $ 595-595
	  US2021C_MLPB     $ 596-596
	  US2021C_MLPCD    $ 597-597
	  US2021C_MLPE     $ 598-598
	  US2021C_MLPFG    $ 599-599
	  US2021C_MLPH     $ 600-600
	  US2021C_MLPJ     $ 601-601
	  US2021C_SCHL     $ 602-603
	  US2021C_SEX      $ 604-604
	  US2021C_HISP     $ 605-606
	  US2021C_LANP     $ 607-610
	  US2021C_MIGPUMA  $ 611-615
	  US2021C_MIGSP    $ 616-618
	  US2021C_NATIVITY $ 619-619
	  US2021C_PINCP    $ 620-626
	  US2021C_POBP     $ 627-629
	  US2021C_POVPIP   $ 630-632
	  US2021C_RAC1P    $ 633-633
	;
	
	label
	  YEAR             = "Census year"
	  MULTYEAR         = "Actual year of survey, multi-year ACS/PRCS"
	  SAMPLE           = "IPUMS sample identifier"
	  SERIAL           = "Household serial number"
	  CBSERIAL         = "Original Census Bureau household serial number"
	  HHWT             = "Household weight"
	  CLUSTER          = "Household cluster for variance estimation"
	  STATEFIP         = "State (FIPS code)"
	  PUMA             = "Public Use Microdata Area"
	  STRATA           = "Household strata for variance estimation"
	  GQ               = "Group quarters status"
	  US2021C_HHT      = "Household/family type"
	  PERNUM           = "Person number in sample unit"
	  PERWT            = "Person weight"
	  REPWTP           = "Person replicate weights [80 variables]"
	  REPWTP1          = "Person replicate weight 1"
	  REPWTP2          = "Person replicate weight 2"
	  REPWTP3          = "Person replicate weight 3"
	  REPWTP4          = "Person replicate weight 4"
	  REPWTP5          = "Person replicate weight 5"
	  REPWTP6          = "Person replicate weight 6"
	  REPWTP7          = "Person replicate weight 7"
	  REPWTP8          = "Person replicate weight 8"
	  REPWTP9          = "Person replicate weight 9"
	  REPWTP10         = "Person replicate weight 10"
	  REPWTP11         = "Person replicate weight 11"
	  REPWTP12         = "Person replicate weight 12"
	  REPWTP13         = "Person replicate weight 13"
	  REPWTP14         = "Person replicate weight 14"
	  REPWTP15         = "Person replicate weight 15"
	  REPWTP16         = "Person replicate weight 16"
	  REPWTP17         = "Person replicate weight 17"
	  REPWTP18         = "Person replicate weight 18"
	  REPWTP19         = "Person replicate weight 19"
	  REPWTP20         = "Person replicate weight 20"
	  REPWTP21         = "Person replicate weight 21"
	  REPWTP22         = "Person replicate weight 22"
	  REPWTP23         = "Person replicate weight 23"
	  REPWTP24         = "Person replicate weight 24"
	  REPWTP25         = "Person replicate weight 25"
	  REPWTP26         = "Person replicate weight 26"
	  REPWTP27         = "Person replicate weight 27"
	  REPWTP28         = "Person replicate weight 28"
	  REPWTP29         = "Person replicate weight 29"
	  REPWTP30         = "Person replicate weight 30"
	  REPWTP31         = "Person replicate weight 31"
	  REPWTP32         = "Person replicate weight 32"
	  REPWTP33         = "Person replicate weight 33"
	  REPWTP34         = "Person replicate weight 34"
	  REPWTP35         = "Person replicate weight 35"
	  REPWTP36         = "Person replicate weight 36"
	  REPWTP37         = "Person replicate weight 37"
	  REPWTP38         = "Person replicate weight 38"
	  REPWTP39         = "Person replicate weight 39"
	  REPWTP40         = "Person replicate weight 40"
	  REPWTP41         = "Person replicate weight 41"
	  REPWTP42         = "Person replicate weight 42"
	  REPWTP43         = "Person replicate weight 43"
	  REPWTP44         = "Person replicate weight 44"
	  REPWTP45         = "Person replicate weight 45"
	  REPWTP46         = "Person replicate weight 46"
	  REPWTP47         = "Person replicate weight 47"
	  REPWTP48         = "Person replicate weight 48"
	  REPWTP49         = "Person replicate weight 49"
	  REPWTP50         = "Person replicate weight 50"
	  REPWTP51         = "Person replicate weight 51"
	  REPWTP52         = "Person replicate weight 52"
	  REPWTP53         = "Person replicate weight 53"
	  REPWTP54         = "Person replicate weight 54"
	  REPWTP55         = "Person replicate weight 55"
	  REPWTP56         = "Person replicate weight 56"
	  REPWTP57         = "Person replicate weight 57"
	  REPWTP58         = "Person replicate weight 58"
	  REPWTP59         = "Person replicate weight 59"
	  REPWTP60         = "Person replicate weight 60"
	  REPWTP61         = "Person replicate weight 61"
	  REPWTP62         = "Person replicate weight 62"
	  REPWTP63         = "Person replicate weight 63"
	  REPWTP64         = "Person replicate weight 64"
	  REPWTP65         = "Person replicate weight 65"
	  REPWTP66         = "Person replicate weight 66"
	  REPWTP67         = "Person replicate weight 67"
	  REPWTP68         = "Person replicate weight 68"
	  REPWTP69         = "Person replicate weight 69"
	  REPWTP70         = "Person replicate weight 70"
	  REPWTP71         = "Person replicate weight 71"
	  REPWTP72         = "Person replicate weight 72"
	  REPWTP73         = "Person replicate weight 73"
	  REPWTP74         = "Person replicate weight 74"
	  REPWTP75         = "Person replicate weight 75"
	  REPWTP76         = "Person replicate weight 76"
	  REPWTP77         = "Person replicate weight 77"
	  REPWTP78         = "Person replicate weight 78"
	  REPWTP79         = "Person replicate weight 79"
	  REPWTP80         = "Person replicate weight 80"
	  US2021C_ADJINCP  = "Adjustment factor for income and earnings dollar amounts (6 implied decimal places)"
	  US2021C_AGEP     = "Age"
	  US2021C_FER      = "Gave birth to child within the past 12 months"
	  US2021C_JWMNP    = "Travel time to work"
	  US2021C_JWRIP    = "Vehicle occupancy"
	  US2021C_JWTRNS   = "Means of transportation to work"
	  US2021C_LANX     = "Language other than English spoken at home"
	  US2021C_MAR      = "Marital status"
	  US2021C_MIG      = "Mobility status (lived here 1 year ago)"
	  US2021C_MLPA     = "Served September 2001 or later"
	  US2021C_MLPB     = "Served August 1990 - August 2001 (including Persian Gulf War)"
	  US2021C_MLPCD    = "Served May 1975 - July 1990"
	  US2021C_MLPE     = "Served Vietnam era (August 1964 - April 1975)"
	  US2021C_MLPFG    = "Served February 1955 - July 1964"
	  US2021C_MLPH     = "Served Korean War (July 1950 - January 1955)"
	  US2021C_MLPJ     = "Served World War II (December 1941 - December 1946)"
	  US2021C_SCHL     = "Educational attainment"
	  US2021C_SEX      = "Sex"
	  US2021C_HISP     = "Recoded detailed Hispanic origin"
	  US2021C_LANP     = "Language spoken at home"
	  US2021C_MIGPUMA  = "Migration PUMA based on 2010 Census definition"
	  US2021C_MIGSP    = "Migration recode - State or foreign country code"
	  US2021C_NATIVITY = "Nativity"
	  US2021C_PINCP    = "Total person's income (signed, use ADJINC to adjust to constant dollars)"
	  US2021C_POBP     = "Place of birth (Recode)"
	  US2021C_POVPIP   = "Income-to-poverty ratio recode"
	  US2021C_RAC1P    = "Recoded detailed race code"
	;
	
	format
	  STATEFIP          STATEFIP_f.
	  GQ                GQ_f.
	  US2021C_HHT       US2021C_HHT_f.
	  REPWTP            REPWTP_f.
	  US2021C_FER       US2021C_FER_f.
	  US2021C_JWTRNS    US2021C_JWTRNS_f.
	  US2021C_LANX      US2021C_LANX_f.
	  US2021C_MAR       US2021C_MAR_f.
	  US2021C_MIG       US2021C_MIG_f.
	  US2021C_MLPA      US2021C_MLPA_f.
	  US2021C_MLPB      US2021C_MLPB_f.
	  US2021C_MLPCD     US2021C_MLPCD_f.
	  US2021C_MLPE      US2021C_MLPE_f.
	  US2021C_MLPFG     US2021C_MLPFG_f.
	  US2021C_MLPH      US2021C_MLPH_f.
	  US2021C_MLPJ      US2021C_MLPJ_f.
	  US2021C_SCHL      US2021C_SCHL_f.
	  US2021C_SEX       US2021C_SEX_f.
	  US2021C_HISP      US2021C_HISP_f.
	  US2021C_LANP      US2021C_LANP_f.
	  US2021C_MIGSP     US2021C_MIGSP_f.
	  US2021C_NATIVITY  US2021C_NATIVITY_f.
	  US2021C_POBP      US2021C_POBP_f.
	  US2021C_RAC1P     US2021C_RAC1P_f.
	;
	
	format
	  CBSERIAL          13.
	  HHWT              11.2
	  CLUSTER           13.
	  STRATA            12.
	  PERWT             11.2
	;

run;

A  => src/02_Prepare.sas +842 -0
@@ 1,842 @@
libname IPUMS "/home/u44593168";

data IPUMS.houses;
	set IPUMS.raw_h;

	/*
		VACANT
		1: Occuped
		2: Vacant
		
		Recoded from VACS
		1 (For rent) -> 2
		2 (Rented, not occupied) -> 2
		3 (For sale only) -> 2
		4 (Sold, not occupied) -> 2
		5 (For seasonal/recreational/occasional use) -> 2
		6 (For migrant workers) -> 2
		7 (Other vacant) -> 2
		Also recoded from TEN
		1 (Owned with mortgage or loan (include home equity loans)) -> 1
		2 (Owned free and clear) -> 1
		3 (Rented) -> 1
		4 (Occupied without payment of rent) -> 1
	*/
	if US2021C_VACS in ("1" "2" "3" "4" "5" "6" "7") then VACANT=2;
	else if US2021C_TEN in ("1" "2" "3" "4") then VACANT=1;

	/*
		NP_NUM
		Numeric NP if occupied
	*/
	if US2021C_NP in ("B0" "B1" "B2" "B3" "B4" "B5" "B6" "B7" "B8" "B9") then NP_NUM=.;
	else if VACANT in (. 2) then NP_NUM=.;
	else NP_NUM=input(US2021C_NP, 2.);

	/*
		OWN
		Ownership of an occupied housing unit
		1: Owned
		2: Rented

		Recoded from TEN
		1 (Owned with mortgage or loan (include home equity loans)) -> 1
		2 (Owned free and clear) -> 1
		3 (Rented) -> 2
		4 (Occupied without payment of rent) -> 2
	*/
	if US2021C_TEN in ("B") then OWN=.;
	else if US2021C_TEN in ("1" "2") then OWN=1;
	else if US2021C_TEN in ("3" "4") then OWN=2;

	/*
		BLD_CAT
		housing units category
		1: Single unit
		2: Multi-unit
		3: Mobile home
		4: Boat, RV, van, etc.
		
		Recoded from BLD
		1 (Mobile home or trailer) -> 3
		2 (One-family house detached) -> 1
		3 (One-family house attached) -> 1
		4 (2 Apartments) -> 2
		5 (3-4 Apartments) -> 2
		6 (5-9 Apartments) -> 2
		7 (10-19 Apartments) -> 2
		8 (20-49 Apartments) -> 2
		9 (50 or more apartments) -> 2
		10 (Boat, RV, van, etc.) -> 4
	*/
	if US2021C_BLD="BB" then BLD_CAT=.;
	else if US2021C_BLD="01" then BLD_CAT=3;
	else if US2021C_BLD in ("02" "03") then BLD_CAT=1;
	else if US2021C_BLD in ("04" "05" "06" "07" "08" "09") then BLD_CAT=2;
	else if US2021C_BLD="10" then BLD_CAT=4;

	/*
		year moved in category
		1: Before 1990
		2: 1990s
		3: 2000s
		4: 2010-2014
		5: 2015-2016
		6: Since 2017
	*/

	/*
		VALP_NUM
		Numeric VALP
	*/
	if US2021C_VALP="BBBBBBB" then VALP_NUM=.;
	else VALP_NUM=input(US2021C_VALP, 7.);

	/*
		VAL
		Property value adjusted for current year
	*/
	if VALP_NUM=. then VAL=.;
	else if US2021C_ADJHSG in (. 0) then VAL=.;
	else VAL=VALP_NUM*US2021C_ADJHSG;

	/*
		VAL_OWN
		Property value of a housing unit if owner occupied, less than 10 acres, and not a mobile home
	*/
	if VAL=. then VAL_OWN=.;
	else if OWN in (. 0) then VAL_OWN=.;
	else if US2021C_SVAL in ("B" "0") then VAL_OWN=.;
	else VAL_OWN=VAL;

	/*
		VAL_OWN_CAT
		Categories of property value if owner occupied, less than 10 acres, and not a mobile home
		1: Up to $100k
		2: $100k-$200k
		3: $200k-$300k
		4: $300k-$400k
		5: $400k-$500k
		6: $500k-$1m
		7: $1m+
	*/
	if VAL=. then VAL_OWN=.;
	else if OWN in (. 2) then VAL_OWN_CAT=.;
	else if US2021C_SVAL in ("B" "0") then VAL_OWN=.;
	else if VAL_OWN<=99999 then VAL_OWN_CAT=1;
	else if 100000<=VAL_OWN<=199999 then VAL_OWN_CAT=2;
	else if 200000<=VAL_OWN<=299999 then VAL_OWN_CAT=3;
	else if 300000<=VAL_OWN<=399999 then VAL_OWN_CAT=4;
	else if 400000<=VAL_OWN<=499999 then VAL_OWN_CAT=5;
	else if 500000<=VAL_OWN<=999999 then VAL_OWN_CAT=6;
	else if 1000000<=VAL_OWN then VAL_OWN_CAT=7;
run;

data IPUMS.people;
	set IPUMS.raw_p;
	/*
		AGEP_NUM
		Numeric AGEP
		
		Recoded from AGEP
		B0-B9 -> .
	*/
	if US2021C_AGEP in ("B0" "B1" "B2" "B3" "B4" "B5" "B6" "B7" "B8" "B9") then AGEP_NUM=.;
	else AGEP_NUM = input(US2021C_AGEP, 2.);

	/*
		AGEP_CAT
		Categories of AGEP
		1: Under 10
		2: 10-19
		3: 20-29
		4: 30-39
		5: 40-49
		6: 50-59
		7: 60-69
		8: 70-79
		9: 80 and over
	*/
	if AGEP_NUM=. then AGEP_CAT=.;
	else if AGEP_NUM<=9 then AGEP_CAT=1;
	else if 10<=AGEP_NUM<=19 then AGEP_CAT=2;
	else if 20<=AGEP_NUM<=29 then AGEP_CAT=3;
	else if 30<=AGEP_NUM<=39 then AGEP_CAT=4;
	else if 40<=AGEP_NUM<=49 then AGEP_CAT=5;
	else if 50<=AGEP_NUM<=59 then AGEP_CAT=6;
	else if 60<=AGEP_NUM<=69 then AGEP_CAT=7;
	else if 70<=AGEP_NUM<=79 then AGEP_CAT=8;
	else if 80<=AGEP_NUM then AGEP_CAT=9;

	/*
		AGEP_CAT2
		Categories of AGEP
		1: Under 18
		2: 18-64
		3: 65 and over
	*/
	if AGEP_NUM=. then AGEP_CAT2=.;
	else if AGEP_NUM<=17 then AGEP_CAT2=1;
	else if 18<=AGEP_NUM<=64 then AGEP_CAT2=2;
	else if 65<=AGEP_NUM then AGEP_CAT2=3;

	/*
		AGEP_CAT3
		Categories of AGEP
		1: Under 18
		2: 18 and over
	*/
	if AGEP_NUM=. then AGEP_CAT3=.;
	else if AGEP_NUM<=17 then AGEP_CAT3=1;
	else if 18<=AGEP_NUM then AGEP_CAT3=2;

	/*
		SEX
		Categories of sex
		1: Male
		2: Female
	*/
	if US2021C_SEX="B" then SEX=.;
	else if US2021C_SEX="1" then SEX=1;
	else if US2021C_SEX="2" then SEX=2;

	/*
		RACE_ETH - combined race and ethnicity
		1: White
		2: Black
		3: American Indian/Alaska Native
		4: Asian
		5: Native Hawaiian/Pacific Islander
		6: Other
		7: Multiple
		8: Hispanic
	
		Recoded from RAC1P
		1 (White alone) -> 1
		2 (Black or African American alone) -> 2
		3 (American Indian alone) -> 3
		4 (Alaska Native alone) -> 3
		5 (American Indian and/or Alaska Native tribes alone) -> 3
		6 (Asian alone) -> 4
		7 (Native Hawaiian and Other Pacific Islander alone) -> 5
		8 (Some Other Race alone) -> 6
		9 (Two or More Races) -> 7
		. -> .
		Also recoded from HISP
		1 (Not Spanish/Hispanic/Latino) -> keep RAC1P recode
		2-24 (any of 23 different Hispanic categories) -> 8
	*/
	if US2021C_RAC1P="B" then RACE_ETH=.;
	else if US2021C_RAC1P="1" then RACE_ETH=1;
	else if US2021C_RAC1P="2" then RACE_ETH=2;
	else if US2021C_RAC1P in ("3" "4" "5") then RACE_ETH=3;
	else if US2021C_RAC1P="6" then RACE_ETH=4;
	else if US2021C_RAC1P="7" then RACE_ETH=5;
	else if US2021C_RAC1P="8" then RACE_ETH=6;
	else if US2021C_RAC1P="9" then RACE_ETH=7;
	if US2021C_HISP in ("02" "03" "04" "05" "06" "07" "08" "09" "10" "11" "12" "13" "14" "15" "16" "17" "18" "19" "20" "21" "22" "23" "24") then RACE_ETH=8;

	/*
		PINCP_NUM
		Numeric PINCP
	*/
	if US2021C_PINCP="BBBBBBB" then PINCP_NUM=.;
	else PINCP_NUM=input(US2021C_PINCP, 7.);

	/*
		INC
		Personal income adjusted for current year
	*/
	if PINCP_NUM=. then INC=.;
	else if US2021C_ADJINCP in (. 0) then INC=.;
	else INC=PINCP_NUM*US2021C_ADJINCP;

	/*
		POV
		Poverty status
		1: Poverty
		2: Non-poverty
	*/
	if US2021C_POVPIP="BBB" then POV=.;
	else if US2021C_POVPIP<100 then POV=1;
	else POV=2;

	/*
		COMM
		Commute minutes if 16 or older
	*/
	if US2021C_JWMNP="BBB" then COMM=.;
	else if AGEP_NUM<16 then COMM=.;
	else COMM=input(US2021C_JWMNP, 3.);

	/*
		COMM_CAT
		Commute categories if 16 or older
		1: Drove alone
		2: Carpooled
		3: Public transit
		4: Bicycle
		5: Walked
		6: Other
		7: Worked at home
		
		Recoded from JWTRNS
		1 (Car, truck, or van) -> 1
		2 (Bus) -> 3
		3 (Subway or elevated rail) -> 3
		4 (Long-distance train or commuter rail) -> 3
		5 (Light rail, streetcar, or trolley) -> 3
		6 (Ferryboat) -> 3
		7 (Taxicab) -> 6
		8 (Motorcycle) -> 6
		9 (Bicycle) -> 4
		10 (Walked) -> 5
		11 (Worked from home) -> 7
		12 (Other method) -> 6
		Also recoded from JWRIP
		1 (Drove alone) -> 1
		2-10 (In 2+ person carpool) -> 2
	*/
	if US2021C_JWTRNS="BB" then COMM_CAT=.;
	else if US2021C_JWTRNS="01" then COMM_CAT=1;
	else if US2021C_JWTRNS in ("02" "03" "04" "05" "06") then COMM_CAT=3;
	else if US2021C_JWTRNS="07" then COMM_CAT=6;
	else if US2021C_JWTRNS="08" then COMM_CAT=6;
	else if US2021C_JWTRNS="09" then COMM_CAT=4;
	else if US2021C_JWTRNS="10" then COMM_CAT=5;
	else if US2021C_JWTRNS="11" then COMM_CAT=7;
	else if US2021C_JWTRNS="12" then COMM_CAT=6;
	if US2021C_JWTRNS="01" and US2021C_JWRIP="01" then COMM_CAT=1;
	else if US2021C_JWTRNS="01" and US2021C_JWRIP in ("02" "03" "04" "05" "06" "07" "08" "09" "10") then COMM_CAT=2;
	if AGEP_NUM<16 then COMM_CAT=.;

	/*
		HHT_CAT
		House type category
		1: Married couples
		2: Male householder
		3: Female householder
		4: Non-family
		
		Recoded from HHT
		1 (Married couple household) -> 1
		2 (Other family household: Male householder, no spouse present) -> 2
		3 (Other family household: Female householder, no spouse present) -> 3
		4 (Nonfamily household: Male householder: Living alone) -> 4
		5 (Nonfamily household: Male householder: Not living alone) -> 4
		6 (Nonfamily household: Female householder: Living alone) -> 4
		7 (Nonfamily household: Female householder: Not living alone) -> 4
	*/
	if US2021C_HHT="B" then HHT_CAT=.;
	else if US2021C_HHT="1" then HHT_CAT=1;
	else if US2021C_HHT="2" then HHT_CAT=2;
	else if US2021C_HHT="3" then HHT_CAT=3;
	else if US2021C_HHT in ("4" "5" "6" "7") then HHT_CAT=4;

	/*
		MARRIED
		Marital status if 15 or older
		1: Married
		2: Not married
		
		Recoded from MAR
		1 (Married) -> 1
		2 (Widowed) -> 2
		3 (Divorced) -> 2
		4 (Separated) -> 2
		5 (Never married or under 15 years old) -> 2
	*/
	if US2021C_MAR="B" then MARRIED=.;
	else if AGEP_NUM=. or AGEP_NUM<15 then MARRIED=.;
	else if US2021C_MAR="1" then MARRIED=1;
	else if US2021C_MAR in ("2" "3" "4" "5") then MARRIED=2;

	/*
		MAR_CAT
		Categories of marital status if 15 or older
		1: Never married
		2: Married
		3: Divorced or separated
		4: Widowed
		
		Recoded from MAR
		1 (Married) -> 2
		2 (Widowed) -> 4
		3 (Divorced) -> 3
		4 (Separated) -> 3
		5 (Never married or under 15 years old) -> 1
	*/
	if US2021C_MAR="B" then MAR_CAT=.;
	else if AGEP_NUM=. or AGEP_NUM<15 then MARRIED=.;
	else if US2021C_MAR="5" then MAR_CAT=1;
	else if US2021C_MAR="1" then MAR_CAT=2;
	else if US2021C_MAR in ("3" "4") then MAR_CAT=3;
	else if US2021C_MAR="2" then MAR_CAT=4;

	/*
		BIRTH
		Gave birth in last year if woman and 15-50
		1: Gave birth in last year
		2: Did not give birth in last year
		
		Recoded from FER
		1 (Yes) -> 1
		2 (No) -> 2
	*/
	if US2021C_FER="B" then BIRTH=.;
	else if US2021C_FER="1" then BIRTH=1;
	else if US2021C_FER="2" then BIRTH=2;

	/*
		AGEP_CAT_BIRTH
		Age categories if woman and 15-50
		1: 15-19
		2: 20-24
		3: 25-29
		4: 30-35
		5: 35-39
		6: 40-44
		7: 45-50
	*/
	if SEX in (. 1) then AGEP_CAT_BIRTH=.;
	else if AGEP_NUM=. then AGEP_CAT_BIRTH=.;
	else if 15<=AGEP_NUM<=19 then AGEP_CAT_BIRTH=1;
	else if 20<=AGEP_NUM<=24 then AGEP_CAT_BIRTH=2;
	else if 25<=AGEP_NUM<=29 then AGEP_CAT_BIRTH=3;
	else if 30<=AGEP_NUM<=34 then AGEP_CAT_BIRTH=4;
	else if 35<=AGEP_NUM<=39 then AGEP_CAT_BIRTH=5;
	else if 40<=AGEP_NUM<=44 then AGEP_CAT_BIRTH=6;
	else if 45<=AGEP_NUM<=50 then AGEP_CAT_BIRTH=7;

	/*
		MIG_CAT
		moved in last year
		1: Moved in last year
		2: Did not move in last year
		
		Recoded from MIG
		1 (Yes, same house (nonmovers)) -> 2
		2 (No, outside US and Puerto Rico) -> 1
		3 (No, different house in US or Puerto Rico) -> 1
	*/
	if US2021C_MIG="B" then MIG_CAT=.;
	else if US2021C_MIG="1" then MIG_CAT=2;
	else if US2021C_MIG in ("2" "3") then MIG_CAT=1;

	/*
		MIGSP_NUM
		Numeric MIGSP
	*/
	if US2021C_MIGSP="BBB" then MIGSP_NUM=.;
	else MIGSP_NUM=input(US2021C_MIGSP, 3.);
	
	/*
		MIGPUMA_NUM
		Numeric MIGPUMA
	*/
	if US2021C_MIGPUMA="BBBBB" then MIGPUMA_NUM=.;
	else MIGPUMA_NUM=input(US2021C_MIGPUMA, 5.);
	
	/*
		MIG_CAT2
		lived last year categories
		1: Same house year ago
		2: From same county
		3: From different county
		4: From different state
		5: From abroad
		
		Recoded from MIG
		1 (Yes, same house (nonmovers)) -> 1
		2 (No, outside US and Puerto Rico) -> 5
		3 (No, different house in US or Puerto Rico) ...
			- If MIGSP~=17 (Illinois) -> 4
			- If MIGSP=17 but MIGPUMA~=03400 (Cook county) -> 3
			- If MIGSP=17 and MIGPUMA=03400 -> 2
	*/
	if US2021C_MIG="B" then MIG_CAT2=.;
	else if US2021C_MIG="1" then MIG_CAT2=1;
	else if US2021C_MIG="3" and MIGSP_NUM=17 and MIGPUMA_NUM=3400 then MIG_CAT2=2;
	else if US2021C_MIG="3" and MIGSP_NUM=17 then MIG_CAT2=3;
	else if US2021C_MIG="3" then MIG_CAT2=4;
	else if US2021C_MIG="2" then MIG_CAT2=5;

	/*
		HS
		1: High school graduate
		2: Not a high school graduate
		
		Recoded from SCHL
		1-15 (up to 12th grade no diploma) -> 2
		16-24 (Regular high school diploma or more) -> 1
	*/
		if US2021C_SCHL="BB" then HS=.;
		else if AGEP_NUM<25 then SCHL_CAT=.;
		else if US2021C_SCHL in ("01" "02" "03" "04" "05" "06" "07" "08" "09" "10" "11" "12" "13" "14" "15") then HS=2;
		else if US2021C_SCHL in ("16" "17" "18" "19" "20" "21" "22" "23" "24") then HS=1;

	/*
		COLLEGE
		1: Bachelor's degree
		2: No bachelor's degree
		
		Recoded from SCHL
		1-20 (up to Associate's degree) -> 2
		21-24 (Bachelor's degree or more) -> 1
	*/
		if US2021C_SCHL="BB" then COLLEGE=.;
		else if AGEP_NUM<25 then SCHL_CAT=.;
		else if US2021C_SCHL in ("01" "02" "03" "04" "05" "06" "07" "08" "09" "10" "11" "12" "13" "14" "15" "16" "17" "18" "19" "20") then COLLEGE=2;
		else if US2021C_SCHL in ("21" "22" "23" "24") then COLLEGE=1;

	/*
		SCHL_CAT
		Education categories if 25 or older
		1: No degree
		2: High school
		3: Some college
		4: Bachelor's
		5: Post-grad
		
		Recoded from SCHL
		1-15 (up to 12th grade no diploma) -> 1
		16 (Regular high school diploma) -> 2
		17 (GED or alternative credential) -> 2
		18 (Some college, but less than 1 year) -> 3
		19 (1 or more years of college credit, no degree) -> 3
		20 (Associate's degree) -> 3
		21 (Bachelor's degree) -> 4
		22 (Master's degree) -> 5
		23 (Professional degree beyond a bachelor's degree) -> 5
		24 (Doctorate degree) -> 5
	*/
		if US2021C_SCHL="BB" then SCHL_CAT=.;
		else if AGEP_NUM<25 then SCHL_CAT=.;
		else if US2021C_SCHL in ("01" "02" "03" "04" "05" "06" "07" "08" "09" "10" "11" "12" "13" "14" "15") then SCHL_CAT=1;
		else if US2021C_SCHL in ("16" "17") then SCHL_CAT=2;
		else if US2021C_SCHL in ("18" "19" "20") then SCHL_CAT=3;
		else if US2021C_SCHL in ("21") then SCHL_CAT=4;
		else if US2021C_SCHL in ("22" "23" "24") then SCHL_CAT=5;

	/*
		LAN_CAT
		Language spoken in home categories
		1: Language other than English spoken at home
		2: English only
		
		Recoded from LANX
		1 (Yes, speaks another language) -> 1
		2 (No, speaks only English) -> 2
	*/
	if US2021C_LANX="B" then LAN_CAT=.;
	else if US2021C_LANX="1" then LAN_CAT=1;
	else if US2021C_LANX="2" then LAN_CAT=2;

	/*
		LANP_NUM
		Numeric LANP
	*/
	if US2021C_LANP="BBBB" then LANP_NUM=.;
	else LANP_NUM=input(US2021C_LANP,4.);
	
	/*
		LAN_CAT2
		Language spoken in home categories
		1: English only
		2: Spanish
		3: Indo-European
		4: Asian/Islander
		5: Other
		
		Recoded from LANX
		2 (No, speaks only English) -> 1
		Also recoded from LANP
		1200-1205 -> 2
		1053-1056, 1069-1073, 1110-1564, 1711-1799 -> 3
		1643-1710, 1800-3798 -> 4
		1000-1052, 1057-1063, 1074-1109, 1565-1642, 3799-9499, 9600-9999 -> 5
	*/
	if US2021C_LANX="B" then LAN_CAT2=.;
	else if US2021C_LANX="2" then LAN_CAT2=1;
	else if 1200<=US2021C_LANP<=1205 then LAN_CAT2=2;
	else if 1053<=US2021C_LANP<=1056 or 1069<=US2021C_LANP<=1073 or 1110<=US2021C_LANP<=1564 or 1711<=US2021C_LANP<=1799 then LAN_CAT2=3;
	else if 1643<=US2021C_LANP<=1710 or 1800<=US2021C_LANP<=3798 then LAN_CAT2=4;
	else if 1000<=US2021C_LANP<=1052 or 1057<=US2021C_LANP<=1063 or 1074<=US2021C_LANP<=1109 or 1565<=US2021C_LANP<=1642 or 3799<=US2021C_LANP<=9499 or 9600<=US2021C_LANP<=9999 then LAN_CAT2=5;

	/*
		FOREIGN
		Foreign-born status
		1: Foreign-born
		2: Not foreign-born
		
		Recoded from NATIVITY
		1 (Native) -> 2
		2 (Foreign born) -> 1
	*/
	if US2021C_NATIVITY="B" then FOREIGN=.;
	else if US2021C_NATIVITY="1" then FOREIGN=2;
	else if US2021C_NATIVITY="2" then FOREIGN=1;

	/*
		POBP_NUM
		Numeric POBP if foreign-born
	*/
	if US2021C_POBP="BBB" then POBP_NUM=.;
	else if US2021C_NATIVITY="1" then POBP_NUM=.;
	else POBP_NUM=input(US2021C_POBP, 3.);

	/*
		POBP_CAT
		Place of birth categories if foreign-born
		1: Europe
		2: Asia
		3: Africa
		4: Oceania
		5: Latin America
		6: North America
	*/
	if POBP_NUM=. then POBP_CAT=.;
	else if 100<=POBP_NUM<=169 then POBP_CAT=1;
	else if 200<=POBP_NUM<=254 then POBP_CAT=2;
	else if POBP_NUM=300 or 302<=POBP_NUM<=399 then POBP_CAT=5;
	else if POBP_NUM=301 then POBP_CAT=6;
	else if 400<=POBP_NUM<=469 then POBP_CAT=3;
	else if 501<=POBP_NUM<=554 then POBP_CAT=4;

	/*
		MLPJ2
		WW2 Veteran status
		1: Veteran
	*/
	if US2021C_MLPJ in ("B" "0") then MLPJ2=.;
	else if US2021C_MLPJ="1" then MLPJ2=1;

	/*
		MLPH2
		Korea Veteran status
		1: Veteran
	*/
	if US2021C_MLPH in ("B" "0") then MLPH2=.;
	else if US2021C_MLPH="1" then MLPH2=1;

	/*
		MLPFG2
		February 1955 - July 1964 Veteran status
		1: Veteran
	*/
	if US2021C_MLPFG in ("B" "0") then MLPFG2=.;
	else if US2021C_MLPFG="1" then MLPFG2=1;

	/*
		MLPE2
		Vietnam Veteran status
		1: Veteran
	*/
	if US2021C_MLPE in ("B" "0") then MLPE2=.;
	else if US2021C_MLPE="1" then MLPE2=1;

	/*
		MLPCD2
		May 1975 - July 1990 Veteran status
		1: Veteran
	*/
	if US2021C_MLPCD in ("B" "0") then MLPCD2=.;
	else if US2021C_MLPCD="1" then MLPCD2=1;

	/*
		MLPB2
		Gulf (1990s) Veteran status
		1: Veteran
	*/
	if US2021C_MLPB in ("B" "0") then MLPB2=.;
	else if US2021C_MLPB="1" then MLPB2=1;

	/*
		MLPA2
		Gulf (2001-) Veteran status
		1: Veteran
	*/
	if US2021C_MLPA in ("B" "0") then MLPA2=.;
	else if US2021C_MLPA="1" then MLPA2=1;

	/*
		VET
		Veteran status
		1: Veteran
		2: Not veteran
	*/
	if MLPJ2=1 or MLPH2=1 or MLPFG2=1 or MLPE2=1 or MLPCD2=1 or MLPB2=1 or MLPA2=1 then VET=1;
	else VET=2;
run;

proc summary data=IPUMS.people;
	class SERIAL;
	var INC;
	output out=IPUMS.sumpeople sum=HHINC;
run;

data IPUMS.mergehouses;
	/*
		HHINC
		Household income
		
		Merged from an aggregation of the person-level data table
	*/
	merge
		IPUMS.houses (keep=SERIAL HHWT STRATA REPWT1-REPWT80 in=HOUSE)
		IPUMS.sumpeople (keep=SERIAL HHINC);
	by SERIAL;
	if HOUSE;
	if HHINC=0 then HHINC=.;

	/*
		HHINC_CAT
		Household income categories
		1: Under $50K
		2: $50K - $100K
		3: $100K - $200K
		4: Over $200K
	*/
	if HHINC=. then HHINC_CAT=.;
	else if HHINC<50000 then HHINC_CAT=1;
	else if 50000<=HHINC<100000 then HHINC_CAT=2;
	else if 100000<=HHINC<200000 then HHINC_CAT=3;
	else if 200000<=HHINC then HHINC_CAT=4;
run;

proc datasets library=IPUMS nolist;
   delete sumpeople;
run;

proc format;
	value SEX_f 	1="Male"
					2="Female";

	value AGEP_CAT_f 	1="0-9"
						2="10-19"
						3="20-29"
						4="30-39"
						5="40-49"
						6="50-59"
						7="60-69"
						8="70-79"
						9="80+";

	value AGEP_CAT2_f 	1="Under 18"
						2="18 to 64"
						3="65 and over";

	value AGEP_CAT3_f 	1="Under 18"
						2="18 and over";

	value RACE_ETH_f 	1="White"
						2="Black"
						3="Native"
						4="Asian"
						5="Islander"
						6="Other"
						7="Two+"
						8="Hispanic";

	value HHT_CAT_f 	1="Married couples"
						2="Male householder"
						3="Female householder"
						4="Non-family";

	value MARRIED_f 	1="Married"
						2="Single";

	value MAR_CAT_f 	1="Never married"
						2="Now married"
						3="Divorced"
						4="Widowed";

	value BIRTH_f 	1="Gave birth in last year"
					2="Did not give birth in last year";

	value AGEP_CAT_BIRTH_f 	1="15-19"
							2="20-24"
							3="25-29"
							4="30-34"
							5="35-39"
							6="40-44"
							7="45-50";

	value VACANT_f 	1="Occuped"
					2="Vacant";

	value OWN_f 	1="Owner occupied"
					2="Renter occupied";

	value VAL_OWN_CAT_f 	1="Under $100K"
							2="$100K-$200K"
							3="$200K-$300K"
							4="$300K-$400K"
							5="$400K-$500K"
							6="$500K-$1M"
							7="Over $1M";

	value HS_f 	1="High school grad or higher"
				2="Not a high school grad";

	value COLLEGE_f 	1="Bachelor's degree or higher"
						2="No Bachelor's degree";

	value SCHL_CAT_f 	1="No degree"
						2="High school"
						3="Some college"
						4="Bachelor's"
						5="Post-grad";

	value LAN_CAT_f 	1="Language other than English spoken at home"
						2="English only";

	value LAN_CAT2_f 	1="English only"
						2="Spanish"
						3="Indo-European"
						4="Asian/Islander"
						5="Other";

	value FB_f 	1="Foreign-born"
				2="Not foreign-born";

	value POBP_CAT_f 	1="Europe"
						2="Asia"
						3="Africa"
						4="Oceania"
						5="Latin America"
						6="North America";

	value VET_f 	1="Veteran"
					2="Not a veteran";

	value HHINC_CAT_f 	1="Under $50K"
						2="$50K - $100K"
						3="$100K - $200K"
						4="Over $200K";

	value POV_f 	1="Below poverty line"
					2="Above poverty line";

	value COMM_CAT_f 	1="Drove alone"
						2="Carpooled"
						3="Public transit"
						4="Bicycle"
						5="Walked"
						6="Other"
						7="Worked at home";

	value BLD_CAT_f 	1="Single unit"
						2="Multi-unit"
						3="Mobile home"
						4="Boat, RV, van, etc.";

	value MIG_CAT_f 	1="Moved in last year"
						2="Did not move in last year";

	value MIG_CAT2_f 	1="Same house year ago"
						2="From same county"
						3="From different county"
						4="From different state"
						5="From abroad";
run;

A  => src/03_Demographics.sas +42 -0
@@ 1,42 @@
libname IPUMS "/home/u44593168";

/* Population */
proc means data=IPUMS.people sum;
	var PERWT;
run;

/* Median Age */
proc means data=IPUMS.people median maxdec=1;
	var AGEP_NUM;
	weight PERWT;
run;

/* Population by age range */
ods select freqplot;
proc freq data=IPUMS.people;
	format AGEP_CAT AGEP_CAT_f.;
	tables AGEP_CAT / plots=freqplot(orient=vertical scale=percent);
	weight PERWT;
run;

/* Population by age category */
proc gchart data=IPUMS.people;
	format AGEP_CAT2 AGEP_CAT2_f.;
	donut AGEP_CAT2 / discrete clockwise slice=outside value=none percent=outside freq=PERWT;
run;
quit;

/* Sex */
proc gchart data=IPUMS.people;
	format SEX SEX_f.;
	donut SEX / discrete clockwise slice=outside value=none percent=outside freq=PERWT;
run;
quit;

/* Race & Ethnicity */
ods select freqplot;
proc freq data=IPUMS.people;
	format RACE_ETH RACE_ETH_f.;
	tables RACE_ETH / plots=freqplot(orient=vertical scale=percent);
	weight PERWT;
run;

A  => src/04_Economics.sas +73 -0
@@ 1,73 @@
libname IPUMS "/home/u44593168";

/* Per capita income */
proc means data=IPUMS.people sum noprint;
	var INC;
	weight PERWT;
	output out=IPUMS.sumproduct sum=GDP;
run;
proc means data=IPUMS.people sum noprint;
	var PERWT;
	output out=IPUMS.sumpopulation sum=POP;
run;
data IPUMS.productpercapita;
	merge
		IPUMS.sumproduct (keep=GDP)
		IPUMS.sumpopulation (keep=POP);
	INCOME_PER_CAPITA=GDP/POP;
run;
proc print data=IPUMS.productpercapita;
	var INCOME_PER_CAPITA;
run;
proc datasets library=IPUMS nolist;
   delete sumproduct sumpopulation productpercapita;
run;

/* Median household income */
proc means data=IPUMS.mergehouses median;
	var HHINC;
	weight HHWT;
run;

/* Household income */
ods select freqplot;
proc freq data=IPUMS.mergehouses;
	format HHINC_CAT HHINC_CAT_f.;
	tables HHINC_CAT / plots=freqplot(orient=vertical scale=percent);
	weight HHWT;
run;

/* Persons below poverty line */
proc freq data=IPUMS.people;
	format POV POV_f.;
	tables POV / plots=freqplot(orient=vertical scale=percent);
	weight PERWT;
run;

/* Persons below poverty line - Children (Under 18) - Seniors (65 and over) */
proc sort data=IPUMS.people
		out=IPUMS.sortpeople;
	by AGEP_CAT2;
run;
proc gchart data=IPUMS.sortpeople;
	format POV POV_f. AGEP_CAT2 AGEP_CAT2_f.;
	by AGEP_CAT2;
	donut POV / discrete clockwise slice=outside value=none percent=outside freq=PERWT;
run;
quit;
proc datasets library=IPUMS nolist;
	delete sortpeople;
run;

/* Mean travel time to work */
proc means data=IPUMS.people mean;
	var COMM;
	weight PERWT;
run;

/* Means of transportation to work */
proc freq data=IPUMS.people;
	format COMM_CAT COMM_CAT_f.;
	tables COMM_CAT / plots=freqplot(orient=vertical scale=percent);
	weight PERWT;
run;

A  => src/05_Families.sas +57 -0
@@ 1,57 @@
libname IPUMS "/home/u44593168";

/* Number of households */
proc means data=IPUMS.houses sum;
	var HHWT;
run;

/* Persons per household */
proc means data=IPUMS.houses mean maxdec=1;
	var NP_NUM;
	weight HHWT;
run;

/* Population by household type */
proc gchart data=IPUMS.people;
	format HHT_CAT HHT_CAT_f.;
	donut HHT_CAT / discrete clockwise slice=outside value=none percent=outside freq=PERWT;
run;
quit;

/* Marital Status */
proc gchart data=IPUMS.people;
	format MARRIED MARRIED_f.;
	donut MARRIED / discrete clockwise slice=outside value=none percent=outside freq=PERWT;
run;
quit;

/* Marital status, by sex */
proc sort data=IPUMS.people
		out=IPUMS.sortpeople;
	by SEX;
run;
ods select freqplot;
proc freq data=IPUMS.sortpeople;
	format SEX SEX_f. MAR_CAT MAR_CAT_f.;
	by SEX;
	tables MAR_CAT / plots=freqplot(orient=vertical scale=percent);
	weight PERWT;
run;
proc datasets library=IPUMS nolist;
	delete sortpeople;
run;

/* Fertility */
proc freq data=IPUMS.people;
	format BIRTH BIRTH_f.;
	tables BIRTH;
	weight PERWT;
run;

/* Women who gave birth during past year, by age group */
ods select freqplot;
proc freq data=IPUMS.people;
	format BIRTH BIRTH_f. AGEP_CAT_BIRTH AGEP_CAT_BIRTH_f.;
	tables BIRTH*AGEP_CAT_BIRTH / plots=freqplot(orient=vertical scale=grouppercent);
	weight PERWT;
run;

A  => src/06_Housing.sas +56 -0
@@ 1,56 @@
libname IPUMS "/home/u44593168";

/* Number of housing units */

/* Occupied vs. Vacant */
proc gchart data=IPUMS.houses;
	format VACANT VACANT_f.;
	donut VACANT / discrete clockwise slice=outside value=none percent=outside freq=HHWT;
run;
quit;

/* Ownership of occupied units */
proc gchart data=IPUMS.houses;
	format OWN OWN_f.;
	donut OWN / discrete clockwise slice=outside value=none percent=outside freq=HHWT;
run;
quit;

/* Types of structure */
proc gchart data=IPUMS.houses;
	format BLD_CAT BLD_CAT_f.;
	donut BLD_CAT / discrete clockwise slice=outside value=none percent=outside freq=HHWT;
run;
quit;

/* Year moved in, by percentage of population */
/* NOTE: Continuous data not available publicly */

/* Median value of owner-occupied housing units */
proc means data=IPUMS.houses median;
	var VAL_OWN;
	weight HHWT;
run;

/* Value of owner-occupied housing units */
ods select freqplot;
proc freq data=IPUMS.houses;
	format VAL_OWN_CAT VAL_OWN_CAT_f.;
	tables VAL_OWN_CAT / plots=freqplot(orient=vertical scale=percent);
	weight HHWT;
run;

/* Moved since previous year */
proc freq data=IPUMS.people;
	format MIG_CAT MIG_CAT_f.;
	tables MIG_CAT;
	weight PERWT;
run;

/* Population migration since previous year */
ods select freqplot;
proc freq data=IPUMS.people;
	format MIG_CAT2 MIG_CAT2_f.;
	tables MIG_CAT2 / plots=freqplot(orient=vertical scale=percent);
	weight PERWT;
run;

A  => src/07_Social.sas +81 -0
@@ 1,81 @@
libname IPUMS "/home/u44593168";

/* High school grad or higher */
proc freq data=IPUMS.people;
	format HS HS_f.;
	tables HS;
	weight PERWT;
run;

/* Bachelor's degree or higher */
proc freq data=IPUMS.people;
	format COLLEGE COLLEGE_f.;
	tables COLLEGE;
	weight PERWT;
run;

/* Population by highest level of education */
ods select freqplot;
proc freq data=IPUMS.people;
	format SCHL_CAT SCHL_CAT_f.;
	tables SCHL_CAT / plots=freqplot(orient=vertical scale=percent);
	weight PERWT;
run;

/* Persons with language other than English spoken at home */
proc freq data=IPUMS.people;
	format LAN_CAT LAN_CAT_f.;
	tables LAN_CAT;
	weight PERWT;
run;

/* Language at home, children 5-17 - adults 18+ */
proc sort data=IPUMS.people
		out=IPUMS.sortpeople;
	by AGEP_CAT3;
run;
ods select freqplot;
proc freq data=IPUMS.sortpeople;
	format LAN_CAT2 LAN_CAT2_f. AGEP_CAT3 AGEP_CAT3_f.;
	by AGEP_CAT3;
	tables LAN_CAT2 / plots=freqplot(orient=vertical scale=percent);
	weight PERWT;
run;
proc datasets library=IPUMS nolist;
	delete sortpeople;
run;

/* Foreign-born population */
proc freq data=IPUMS.people;
	format FOREIGN FOREIGN_f.;
	tables FOREIGN;
	weight PERWT;
run;

/* Place of birth for foreign-born population */
ods select freqplot;
proc freq data=IPUMS.people;
	format POBP_CAT POBP_CAT_f.;
	tables POBP_CAT / plots=freqplot(orient=vertical scale=percent);
	weight PERWT;
run;

/* Veteran status */
proc freq data=IPUMS.people;
	format VET VET_f.;
	tables VET;
	weight PERWT;
run;

/* Veterans by wartime service */
proc freq data=IPUMS.people;
	tables MLPJ2 MLPH2 MLPE2 MLPB2 MLPA2;
	weight PERWT;
run;

/*  Total veterans - Male - Female */
proc freq data=IPUMS.people;
	format VET VET_f. SEX SEX_f.; 
	tables VET*SEX / nopercent nocol norow nocum;
	weight PERWT;
run;