*--This is /pub/sascode/sf12000x.sas: The essence of the data step used to create a sf1 2000 standard extract data set (filetype sf12000x) from a full sf1 2000 data set (sf12000 filetype). See the sf12000x/Tools directory for samples of how this gets used in a conversion run. ----; *-- Coding by Shiva Kumar and John Blodgett, OSEDA, U. of Missouri Outreach and Extension, under contract with the Missouri Census Data Center. --*; *---Attrib statement(s) generated by genattr macro---; Attrib TotPop length= 5 label='Total Persons' TotPop90 length=5 label='Total Pop 1990' Change length=4 label='Pop Change, 1990-2000' PctChange length=3 format=5.1 label='% Change in Pop 1990-2000' Male length= 5 label='Male' pct_Male length=3 format=5.1 label='% Male' Female length= 5 label='Female' pct_Female length=3 format=5.1 label='% Female' ; Attrib Age0_4 length= 5 label='Under 5 Yrs' pct_Age0_4 length=3 format=5.1 label='% Under 5 Yrs' Age5_9 length= 5 label='5 to 9' pct_Age5_9 length=3 format=5.1 label='% 5 to 9' Age10_14 length= 5 label='10 to 14' pct_Age10_14 length=3 format=5.1 label='% 10 to 14' Age15_19 length= 5 label='15 to 19' pct_Age15_19 length=3 format=5.1 label='% 15 to 19' Age15_17 length= 5 label='15 to 17' pct_Age15_17 length=3 format=5.1 label='% 15 to 17' Age18_19 length= 5 label='18 to 19' pct_Age18_19 length=3 format=5.1 label='% 18 to 19' Age18_24 length= 5 label='18 to 24' pct_Age18_24 length=3 format=5.1 label='% 18 to 24' Age20_24 length= 5 label='20 to 24' pct_Age20_24 length=3 format=5.1 label='% 20 to 24' Age25_44 length= 5 label='25 to 44' pct_Age25_44 length=3 format=5.1 label='% 25 to 44' Age45_64 length= 5 label='45 to 64' pct_Age45_64 length=3 format=5.1 label='% 45 to 64' Age25_34 length= 5 label='25 to 34' pct_Age25_34 length=3 format=5.1 label='% 25 to 34' Age35_44 length= 5 label='35 to 44' pct_Age35_44 length=3 format=5.1 label='% 35 to 44' Age45_54 length= 5 label='45 to 54' pct_Age45_54 length=3 format=5.1 label='% 45 to 54' Age55_59 length= 5 label='55 to 59' pct_Age55_59 length=3 format=5.1 label='% 55 to 59' Age60_64 length= 5 label='60 to 64' pct_Age60_64 length=3 format=5.1 label='% 60 to 64' ; Attrib Age65_74 length= 5 label='65 to 74' pct_Age65_74 length=3 format=5.1 label='% 65 to 74' Age75_84 length= 5 label='75 to 84' pct_Age75_84 length=3 format=5.1 label='% 75 to 84' Over85 length= 5 label='Over 85' pct_Over85 length=3 format=5.1 label='% Over 85' Median_Age length= 5 label='Median age' age17_down length= 5 label='17 and Under' pct_age17_down length=3 format=5.1 label='% 17 and Under' Over18 length= 5 label='Over 18' pct_Over18 length=3 format=5.1 label='% Over 18' Over18_Male length= 5 label='Over 18 Male' pct_Over18_Male length=3 format=5.1 label='% Over 18 Male' Over18_Female length= 5 label='Over 18 Female' pct_Over18_Female length=3 format=5.1 label='% Over 18 Female' Over21 length= 5 label='Over 21' pct_Over21 length=3 format=5.1 label='% Over 21' Over62 length= 5 label='Over 62' pct_Over62 length=3 format=5.1 label='% Over 62' Over65 length= 5 label='Over 65' pct_Over65 length=3 format=5.1 label='% Over 65' Over65_Male length= 5 label='Over 65 Male' ; Attrib pct_Over65_Male length=3 format=5.1 label='% Over 65 Male' Over65_Female length= 5 label='Over 65 Female' pct_Over65_Female length=3 format=5.1 label='% Over 65 Female' One_race_Total length= 5 label='One Race: Total' pct_One_race_Total length=3 format=5.1 label='% One Race: Total' White1 length= 5 label='White Alone' pct_White1 length=3 format=5.1 label='% White Alone' Black1 length= 5 label='Black or African American Alone' pct_Black1 length=3 format=5.1 label='% Black or African American Alone' Indian length= 5 label='American Indian or Alaska Native Alone' pct_Indian length=3 format=5.1 label='% American Indian or Alaska Native Alone' Asian1 length= 5 label='Asian Alone' pct_Asian1 length=3 format=5.1 label='% Asian Alone' Asian_Indian length= 5 label='Asian Indian' pct_Asian_Indian length=3 format=5.1 label='% Asian Indian' Chinese length= 5 label='Chinese' pct_Chinese length=3 format=5.1 label='% Chinese' Filipino length= 5 label='Filipino' pct_Filipino length=3 format=5.1 label='% Filipino' Japanese length= 5 label='Japanese' ; Attrib pct_Japanese length=3 format=5.1 label='% Japanese' Korean length= 5 label='Korean' pct_Korean length=3 format=5.1 label='% Korean' Vietnamese length= 5 label='Vietnamese' pct_Vietnamese length=3 format=5.1 label='% Vietnamese' Other_Asian length= 5 label='Other Asian' pct_Other_Asian length=3 format=5.1 label='% Other Asian' HawnPI1 length= 5 label='Hawaiian and Other Pac Islndr Alone' pct_HawnPI1 length=3 format=5.1 label='% Hawaiian and Other Pac Islndr Alone' Hawaiian length= 5 label='Native Hawaiian' pct_Hawaiian length=3 format=5.1 label='% Native Hawaiian' Guam_or_Cham length= 5 label='Guamanian or Chamorro' pct_Guam_or_Cham length=3 format=5.1 label='% Guamanian or Chamorro' Samoan length= 5 label='Samoan' pct_Samoan length=3 format=5.1 label='% Samoan' Other_Pac_Islander length= 5 label='Other Pacific Islander Alone' pct_Other_Pac_Islander length=3 format=5.1 label='% Other Pacific Islander Alone' Other1 length= 5 label='Some other race Alone' pct_Other1 length=3 format=5.1 label='% Some other race Alone' MultRace length= 5 label='Multi Racial' ; Attrib pct_MultRace length=3 format=5.1 label='% Multi Racial' White2 length= 5 label='White Alone or in Combination' pct_White2 length=3 format=5.1 label='% White Alone or in Combination' Black2 length= 5 label='Black or African American Alone or in Comb' pct_Black2 length=3 format=5.1 label='% Black or African American Alone or in Comb' Indian2 length= 5 label='American Indian or Alaska Native Alone or in Comb' pct_Indian2 length=3 format=5.1 label='% American Indian or Alaska Native Alone or in Comb' Asian2 length= 5 label='Asian Alone or in Comb' pct_Asian2 length=3 format=5.1 label='% Asian Alone or in Comb' Hawnpi2 length= 5 label='Hawaiian and Other Pac Islndr Alone or in Comb' pct_Hawnpi2 length=3 format=5.1 label='% Hawaiian and Other Pac Islndr Alone or in Comb' Other2 length= 5 label='Other race Alone or in Comb' pct_Other2 length=3 format=5.1 label='% Other race Alone or in Comb' HispPop length= 5 label='Total Hispanic or Latino (any Race)' pct_HispPop length=3 format=5.1 label='% Total Hispanic or Latino (any Race)' Mexican length= 5 label='Mexican' pct_Mexican length=3 format=5.1 label='% Mexican' Puerto_Rican length= 5 label='Puerto Rican' pct_Puerto_Rican length=3 format=5.1 label='% Puerto Rican' Cuban length= 5 label='Cuban' ; Attrib pct_Cuban length=3 format=5.1 label='% Cuban' Other_Hisp length= 5 label='Other Hispanic or Latino' pct_Other_Hisp length=3 format=5.1 label='% Other Hispanic or Latino' Non_Hispanic length= 5 label='Not Hispanic or Latino' pct_Non_Hispanic length=3 format=5.1 label='% Not Hispanic or Latino' White_Non_Hispanic length= 5 label='White Alone Non Hispanic' pct_White_Non_Hispanic length=3 format=5.1 label='% White Alone Non Hispanic' HHPop length= 5 label='Persons In households' pct_HHPop length=3 format=5.1 label='% Persons In households' Householder length= 5 label='Householder' pct_Householder length=3 format=5.1 label='% Householder' Spouse length= 5 label='Spouse' pct_Spouse length=3 format=5.1 label='% Spouse' Child length= 5 label='Child' pct_Child length=3 format=5.1 label='% Child' OwnChild_Under18 length= 5 label='Own child under 18' pct_OwnChild_Under18 length=3 format=5.1 label='% Own child under 18' Other_relatives length= 5 label='Other Relatives' pct_Other_relatives length=3 format=5.1 label='% Other Relatives' Other_Under18 length= 5 label='Other Relatives under 18' ; Attrib pct_Other_Under18 length=3 format=5.1 label='% Other Relatives under 18' Nonrelatives length= 5 label='Nonrelatives' pct_Nonrelatives length=3 format=5.1 label='% Nonrelatives' Unmarried_partner length= 5 label='Unmarried Partner' pct_Unmarried_partner length=3 format=5.1 label='% Unmarried Partner' GQPop length= 5 label='Group Quarters' pct_GQPop length=3 format=5.1 label='% Group Quarters' Institution_Pop length= 5 label='Institutionalized Pop' pct_Institution_Pop length=3 format=5.1 label='% Institutionalized Pop' NonInstitution_Pop length= 5 label='Non Institutionalized GQ Pop' pct_NonInstitution_Pop length=3 format=5.1 label='% Non Institutionalized GQ Pop' TotHHs length= 5 label='Total Households' Families length= 5 label='Family Households' pct_Families length=3 format=5.1 label='% Family Households' Fam_ChildUnder18 length= 5 label='Families with own children < 18' pct_Fam_ChildUnder18 length=3 format=5.1 label='% Families with own children < 18' Married_Couple length= 5 label='Married Couple Family' pct_Married_Couple length=3 format=5.1 label='% Married Couple Family' MarrCouple_ChildUnder18 length= 5 label='Married Couple Own Children < 18' pct_MarrCouple_ChildUnder18 length=3 format=5.1 label='% Married Couple Own Children < 18' ; Attrib FemaleHouseholder length= 5 label='Female Householder No Husband' pct_FemaleHouseholder length=3 format=5.1 label='% Female Householder No Husband' Fem_ChildUnder18 length= 5 label='Female Householder With Own Child < 18' pct_Fem_ChildUnder18 length=3 format=5.1 label='% Female Householder With Own Child < 18' NonFamily_Households length= 5 label='Non Family Households' pct_NonFamily_Households length=3 format=5.1 label='% Non Family Households' LivingAlone length= 5 label='Persons Living Alone' pct_LivingAlone length=3 format=5.1 label='% Persons Living Alone' Householder_Over65 length= 5 label='Householder 65+' pct_Householder_Over65 length=3 format=5.1 label='% Householder 65+' House_IndvUnder18 length= 5 label='Households w. Individuals Under 18' pct_House_IndvUnder18 length=3 format=5.1 label='% Households w. Individuals Under 18' House_IndvOver65 length= 5 label='Households w. Individuals Over 65' pct_House_IndvOver65 length=3 format=5.1 label='% Households w. Individuals Over 65' Avg_HouseSize length= 5 label='Avg Household Size' Avg_FamSize length= 5 label='Avg Family Size' Same_sex_partner_hhs_male length=5 label='Same Sex partner Households - Male' pct_Same_sex_partner_hhs_male length=3 format=5.1 label='Same Sex partner Households - Male' Same_sex_partner_hhs_female length=5 label='Same Sex partner Households - Female' pct_Same_sex_partner_hhs_female length=3 format=5.1 label='Same Sex partner Households - Female' Tot_Units length= 5 label='Total Housing Units' Occupied_Units length= 5 label='Occupied Housing Units' pct_Occupied_Units length=3 format=5.1 label='% Occupied Housing Units' Vacant_Units length= 5 label='Vacant Housing Units' ; Attrib gqpop length= 5 label ='Population in Group quarters' pct_gqpop length=3 format=5.1 label='% Population in Group quarters' Institution_pop length= 5 label='Institutionalized population' pct_Institution_pop length=3 format=5.1 label='% Institutionalized population' correction_institutions length= 5 label='Correctional Institutions' pct_correction_institutions length=3 format=5.1 label='% Correctional Institutions' Nursing_homes length= 5 label='Nursing Homes' pct_Nursing_homes length=3 format=5.1 label='% Nursing Homes' Other_institutions length= 5 label='Other Institutions' pct_Other_institutions length=3 format=5.1 label='% Other Institutions' NonInstitution_pop length= 5 label='Noninstitutionalized population' pct_NonInstitution_pop length=3 format=5.1 label='% Noninstitutionalized population' military_quarters length= 5 label='Military Quarters' pct_military_quarters length=3 format=5.1 label='% Military Quarters' College_dormitories length= 5 label='College dormitories (includes college quarters off campus)' pct_College_dormitories length=3 format=5.1 label='% College dormitories' other_noninstitution_gp length= 5 label='Other noninstitutional group quarters' pct_other_noninstitution_gp length=3 format=5.1 label='% Other noninstitutional group quarters' ; Attrib pct_Vacant_Units length=3 format=5.1 label='% Vacant Housing Units' vacantforrent length= 5 label='Units - Vacant for Rent' pct_vacantforrent length=3 format=5.1 label='% Units - Vacant for Rent' vacantforsale length= 5 label='Units - Vacant for Sale' pct_vacantforsale length=3 format=5.1 label='% Units - Vacant for Sale' Seas_Rec_Use length= 5 label='Units - Seasonal, Rec or Occasional Use' pct_Seas_Rec_Use length=3 format=5.1 label='% Units - Seasonal, Rec or Occasional Use' OwnerVacRate length= 5 label='Owner Unit Vacancy Rate' RentalVacRate length= 5 label='Rental Unit Vacancy Rate' Occupied_Units length= 5 label='Occupied Housing Units' Owner_Occupied length= 5 label='Owner-occupied Units' pct_Owner_Occupied length=3 format=5.1 label='% Owner-occupied Units' Renter_Occupied length= 5 label='Renter-occupied Units' pct_Renter_Occupied length=3 format=5.1 label='% Renter-occupied Units' AvgSize_Owner length= 5 label='Avg Size of Owner-occupied Units' AvgSize_Renter length= 5 label='Avg Size of Renter-occupied Units' ; attrib poppsqmi length=5 format=7.1 label='Persons Per Sq Mile'; *-general population--; esriid=compress(geocode,'-.'); totpop=p1i1; if areasqmi gt 0 then poppsqmi=totpop/areasqmi; male=p12i2; female=p12i26; %macro percent(compvar= , basevar= ); if &basevar gt 0 then pct_&compvar=(&compvar/&basevar)*100; %mend percent; %percent(compvar=male,basevar=totpop); %percent(compvar=female,basevar=totpop); *--persons by age--; age0_4 = p12i3+p12i27; age5_9 = p12i4+p12i28; age10_14=p12i5+p12i29 ; age15_19=p12i6+p12i7+p12i30+p12i31; age15_17=p12i6+p12i30; age18_19=p12i7+p12i31; age20_24=sum(of p12i8-p12i10)+sum(of p12i32-p12i34); age25_34=(p12i11 + p12i12)+(p12i35+p12i36); age35_44=(p12i13+p12i14)+(p12i37+p12i38); age45_54=(p12i15 + p12i16)+(p12i39+p12i40); age55_59=p12i17+p12i41; age60_64=(p12i18 +p12i19) +(p12i42 + p12i43); age65_74=(p12i20+p12i21+p12i22) + (p12i44+p12i45+p12i46); age75_84=(p12i23 + p12i24)+(p12i47+p12i48); over85=p12i25+p12i49; median_age=p13i1; age17_down=sum (of p12i3-p12i6) +sum (of p12i27-p12i30); over18=sum(of p12i7-p12i25)+sum(of p12i31-p12i49); over18_male=sum(of p12i7-p12i25); over18_female=sum(of p12i31-p12i49); over21=sum(of p12i9-p12i25)+sum(of p12i33-p12i49); age18_24=sum(of p12i7-p12i10)+ sum(of p12i31-p12i34); age25_44=sum( of p12i11-p12i14)+sum(of p12i35-p12i38); age45_64=sum( of p12i15-p12i19)+sum(of p12i39-p12i43); over62=sum(of p12i19 - p12i25)+ sum(of p12i43-p12i49); over65=sum(of p12i20 - p12i25)+ sum(of p12i44-p12i49); over65_male=sum(of p12i20 - p12i25); over65_female=sum(of p12i44-p12i49); %percent(compvar=age0_4,basevar=totpop); %percent(compvar=age5_9 ,basevar=totpop); %percent(compvar=age10_14,basevar=totpop); %percent(compvar=age15_19,basevar=totpop); %percent(compvar=age15_17,basevar=totpop); %percent(compvar=age18_19,basevar=totpop); %percent(compvar=age20_24,basevar=totpop); %percent(compvar=age25_34,basevar=totpop); %percent(compvar=age35_44,basevar=totpop); %percent(compvar=age45_54,basevar=totpop); %percent(compvar=age55_59,basevar=totpop); %percent(compvar=age60_64,basevar=totpop); %percent(compvar=age65_74,basevar=totpop); %percent(compvar=age75_84,basevar=totpop); %percent(compvar=over85,basevar=totpop); *percent(compvar=median_age,basevar=totpop); %percent(compvar=age17_down,basevar=totpop); %percent(compvar=over18,basevar=totpop); %percent(compvar=over18_male,basevar=totpop); %percent(compvar=over18_female,basevar=totpop); %percent(compvar=over21,basevar=totpop); %percent(compvar=age18_24,basevar=totpop); %percent(compvar=age25_44,basevar=totpop); %percent(compvar=age45_64,basevar=totpop); %percent(compvar=over62,basevar=totpop); %percent(compvar=over65,basevar=totpop); %percent(compvar=over65_male,basevar=totpop); %percent(compvar=over65_female,basevar=totpop); *--persons by race--*; one_race_total=p3i2; white1=p3i3; black1=p3i4; indian=p3i5; asian1=p3i6; *<--initially this was p3i6 + p3i7 (sic)--; asian_indian=pct5i2; chinese=pct5i5+pct5i15; filipino=pct5i6; japanese=pct5i9; korean=pct5i10; vietnamese=pct5i17; other_asian=p3i6-(pct5i2+pct5i5+pct5i15+pct5i6+pct5i9+pct5i10+pct5i17); hawnpi1=p3i7; hawaiian=pct8i3; guam_or_cham=pct8i8; samoan=pct8i4; other_pac_islander=p3i7-(pct8i3+pct8i8+pct8i4); other1=p3i2-(p3i3+p3i4+p3i5+p3i6+p3i7); %percent(compvar=one_race_total,basevar=totpop); %percent(compvar=white1,basevar=totpop); %percent(compvar=black1,basevar=totpop); %percent(compvar=indian,basevar=totpop); %percent(compvar=asian1,basevar=totpop); %percent(compvar=asian_indian,basevar=totpop); %percent(compvar=chinese,basevar=totpop); %percent(compvar=filipino,basevar=totpop); %percent(compvar=japanese,basevar=totpop); %percent(compvar=korean,basevar=totpop); %percent(compvar=vietnamese,basevar=totpop); %percent(compvar=other_asian,basevar=totpop); %percent(compvar=hawnpi1,basevar=totpop); %percent(compvar=hawaiian,basevar=totpop); %percent(compvar=guam_or_cham,basevar=totpop); %percent(compvar=samoan,basevar=totpop); %percent(compvar=other_pac_islander,basevar=totpop); %percent(compvar=other1,basevar=totpop); multrace=p3i9; %percent(compvar=multrace,basevar=totpop); * Race alone or in combination with one or more other races *; white2=p9i2; black2=p9i3; indian2=p9i4; asian2=p9i5; hawnpi2=p9i6; other2=p9i7; HispPop=p11i1; mexican=pct11i4; puerto_rican=pct11i5; cuban=pct11i6; other_hisp=pct11i3-(pct11i4+pct11i5+pct11i6); non_hispanic=pct11i2; white_non_hispanic=p4i5; %percent(compvar=white2,basevar=totpop); %percent(compvar=black2,basevar=totpop); %percent(compvar=indian2,basevar=totpop); %percent(compvar=asian2,basevar=totpop); %percent(compvar=hawnpi2,basevar=totpop); %percent(compvar=other2,basevar=totpop); %percent(compvar=hisppop,basevar=totpop); %percent(compvar=mexican,basevar=totpop); %percent(compvar=puerto_rican,basevar=totpop); %percent(compvar=cuban,basevar=totpop); %percent(compvar=other_hisp,basevar=totpop); %percent(compvar=non_hispanic,basevar=totpop); %percent(compvar=white_non_hispanic,basevar=totpop); *-- relationship --; hhpop=p27i2; householder=p15i1; spouse=p27i7; child=p27i8; ownchild_under18=p28i6+p28i7; other_relatives=sum (of p27i11- p27i14); other_under18=p28i10; nonrelatives=p27i15+p27i23; unmarried_partner=pct15i5+pct15i11; %percent(compvar=hhpop,basevar=totpop); %percent(compvar=householder,basevar=totpop); %percent(compvar=spouse,basevar=totpop); %percent(compvar=child,basevar=totpop); %percent(compvar=ownchild_under18,basevar=totpop); %percent(compvar=other_relatives,basevar=totpop); %percent(compvar=other_under18,basevar=totpop); %percent(compvar=nonrelatives,basevar=totpop); %percent(compvar=unmarried_partner,basevar=totpop); *--households by type--; tothhs=p15i1; families=p18i6; fam_childunder18=p18i8+p18i12+p18i15; married_couple=p18i7; marrcouple_childunder18=p18i8; femalehouseholder=p18i14; *-female headed family non-mc hhs; fem_childunder18=p18i15; *--female headed hh no husband w kids; nonfamily_households=p18i17+p18i2; livingalone=p18i2; householder_over65=p20i30; house_indvunder18=p19i2; *-- households with individuals under 18 yrs; house_indvover65=p23i2; *-- household with individuals 65 years and over; if p15i1 gt 0 then avg_housesize= p27i2/p15i1; format avg_housesize 4.2; avg_famsize=p33i1; format avg_famsize 4.2; *percent(compvar=tothhs,basevar=tothhs); %percent(compvar=families,basevar=tothhs); %percent(compvar=fam_childunder18,basevar=tothhs); %percent(compvar=married_couple,basevar=tothhs); %percent(compvar=marrcouple_childunder18,basevar=tothhs); %percent(compvar=femalehouseholder,basevar=tothhs); %percent(compvar=fem_childunder18,basevar=tothhs); %percent(compvar=nonfamily_households,basevar=tothhs); %percent(compvar=livingalone,basevar=tothhs); %percent(compvar=householder_over65,basevar=tothhs); %percent(compvar=house_indvunder18,basevar=tothhs); %percent(compvar=house_indvover65,basevar=tothhs); *--Group Quarters ----------------; gqpop=p37i1; Institution_pop=p37i2; correction_institutions=p37i3; Nursing_homes=p37i4; Other_institutions=p37i5; NonInstitution_pop=p37i6; College_dormitories=p37i7; Military_quarters=p37i8; other_noninstitution_gp=p37i9; %percent(compvar=gqpop,basevar=totpop); %percent(compvar=Institution_pop,basevar=totpop); %percent(compvar= correction_institutions,basevar=totpop); %percent(compvar=Nursing_homes,basevar=totpop); %percent(compvar=Other_institutions,basevar=totpop); %percent(compvar=NonInstitution_pop,basevar=totpop); %percent(compvar=College_dormitories,basevar=totpop); %percent(compvar=Military_quarters,basevar=totpop); %percent(compvar=other_noninstitution_gp,basevar=totpop); *--housing occupancy and tenure--; tot_units=h1i1; occupied_units=h3i2; owner_occupied=h4i2; renter_occupied=h4i3; vacant_units=h5i1; vacantforrent=h5i2; vacantforsale=h5i3; seas_rec_use=h5i5; if (h5i3+h4i2) gt 0 then ownervacrate=(h5i3/(h5i3+h4i2))*100; format ownervacrate 5.2; if (h5i2+h4i3) gt 0 then rentalvacrate=(h5i2/(h5i2+h4i3))*100; format rentalvacrate 5.2; * label tot_units = 'total housing units' occupied_units='occupied housing units' vacant_units='vacant housing units' vacantforrent='Vacant for rent' vacantforsale='Vacant for Sale only' seas_rec_use= 'For Seasonal, recrtnl, or occasnl use' ownervacrate='homeowner vacancy rate' rentalvacrate='rental vacancy rate'; avgsize_owner=h12i2; format avgsize_owner 5.2; avgsize_renter=h12i3; format avgsize_renter 5.2; *percent(compvar=tot_units,basevar=tot_units); %percent(compvar=occupied_units,basevar=tot_units); %percent(compvar=owner_occupied,basevar=tot_units); %percent(compvar=renter_occupied,basevar=tot_units); %percent(compvar=vacant_units,basevar=tot_units); %percent(compvar=vacantforrent,basevar=tot_units); %percent(compvar=vacantforsale,basevar=tot_units); %percent(compvar=seas_rec_use,basevar=tot_units); * label owner_occupied='owner occupied housing units' renter_occupied='renter occupied housing units' avgsize_owner='avg household size of oou' avgsize_renter='avg household size of rou'; retain year '2000'; *keep sumlev geo_id geocode geocomp state stab areaname county tract bg block cousubfp placefp areasqmi landsqmi intptlon intptlat esriid ; *<----suggested additional keeps. The including step will need a second keep statement for id variables.--; keep totpop -- avgsize_renter poppsqmi--year; *<---these are the data vars and these we always keep;