def _save_wp_as_txt_with_reordering_columns(wp_csv):
# csv columns (input):
# 0 longitude,latitude,"","workplace_id","stcotr",
# 5 "employees","placed","wkb_geometry"
# text columns (output):
# sp_id,workers,latitude,longitude
aid.reorder_and_check_header(wp_csv, [4, 6, 2, 1], 'workplaces.txt-us')
def _save_sc_as_txt_with_reordering_columns(sc_csv):
# csv columns (input):
# 0 "","School","ID","CoNo","StNo",
# 5 "Long","Lat","Low","High","Students",
# 10 made-empty
# text columns (output):
# sp_id,name,stabbr,address,city,
# county,zipcode,zip4,nces_id,total,
# prek,kinder,gr01_gr1
sc_columns = [
3, 2, 5, 11, 11, 4, 11, 11, 11, 10, 11, 11, 11, 11, 7, 6, 11, 11
]
aid.reorder_and_check_header(sc_csv, sc_columns, 'schools.txt-us')
def _save_hh_as_txt_with_reordering_columns(hh_csv, gq_csv):
""" csv columns (input):
0 SERIALNO,puma_id,place_id,SYNTHETIC_HID,longitude,
5 latitude,AGEGRP,HRSWRK,IMMSTAT,INCTAX,
10 MODE,OCC,POB,RELIGION,SEX,
15 SYNTHETIC_PID,made-empty,made-persons
text columns (output):
sp_id,serialno,stcotrbg,hh_race,hh_income,
hh_size,hh_age,latitude,longitude """
hh_columns = [4, 1, 3, 17, 17, 18, 17, 6, 5]
aid.reorder_and_check_header(hh_csv, hh_columns, 'synth_households.txt-ca')
# text columns (output):
# sp_id,gq_type,persons,stcotrbg,
# latitude,longitude
gq_columns = [4, 17, 17, 3, 6, 5]
aid.reorder_and_check_header(gq_csv, gq_columns, 'synth_gq.txt-ca')
def _save_pp_as_txt_with_reordering_columns(pp_csv, gq_pp_csv):
""" csv columns (input):
0 SERIALNO,puma_id,place_id,SYNTHETIC_HID,longitude,
5 latitude,AGEGRP,HRSWRK,IMMSTAT,INCTAX,
10 MODE,OCC,POB,RELIGION,SEX,
15 SYNTHETIC_PID,made-sporder,made-empty,made-sex,made-age
text columns (output):
sp_id,sp_hh_id,serialno,stcotrbg,age,
sex,race,sporder,relate,sp_school_id,
sp_work_id """
pp_columns = [16, 4, 1, 3, 20, 19, 18, 17, 18, 18, 18]
aid.reorder_and_check_header(pp_csv, pp_columns, 'synth_people.txt-ca')
# text columns (output):
# sp_id,sp_gq_id,sporder,age,sex
gq_pp_columns = [16, 4, 17, 20, 19]
aid.reorder_and_check_header(gq_pp_csv, gq_pp_columns,
'synth_gq_people.txt-ca')
def _save_hh_as_txt_with_reordering_columns(hh_csv, gq_csv):
# csv columns (input):
# 0 RT,TYPE,SERIALNO,puma_id,HINCP,
# 5 NP,place_id,SYNTHETIC_HID,longitude,latitude,
# 10 RT,puma_id,ST,SEX,AGEP,
# 15 SCH,SCHG,RELP,HISP,ESR,
# 20 PINCP,NATIVITY,OCCP,POBP,RAC1P,
# 25 SYNTHETIC_PID,school_id,workplace_id,made-gq_type
# text columns (output):
# sp_id,serialno,stcotrbg,hh_race,hh_income,
# hh_size,hh_age,latitude,longitude
hh_columns = [8, 3, 7, 25, 5, 6, 15, 10, 9]
aid.reorder_and_check_header(hh_csv, hh_columns, 'synth_households.txt-us')
# text columns (output):
# sp_id,gq_type,persons,stcotrbg,latitude,longitude
gq_columns = [8, 29, 6, 7, 10, 9]
aid.reorder_and_check_header(gq_csv, gq_columns, 'synth_gq.txt-us')
def _save_hh_as_txt_with_reordering_columns(hh_csv, gq_csv):
""" csv columns (input):
0 COUNTRY,YEAR,SERIALNO,PERSONS,puma_id,
5 HHTYPE,PERNUM,place_id,SYNTHETIC_HID,longitude,
10 latitude,AGE,SEX,RACE,SCHOOL,
15 INCTOT,SYNTHETIC_PID+made-age,made-race,made-income,
20 made-empty
text columns (output):
sp_id,serialno,stcotrbg,hh_race,hh_income,
hh_size,hh_age,latitude,longitude """
hh_columns = [9, 3, 8, 19, 20, 4, 18, 11, 10]
aid.reorder_and_check_header(hh_csv, hh_columns,
'synth_households.txt-ipums')
# text columns (output):
# sp_id,gq_type,persons,stcotrbg,latitude,longitude
gq_columns = [9, 21, 4, 8, 11, 10]
aid.reorder_and_check_header(gq_csv, gq_columns, 'synth_gq.txt-ipums')
def _save_pp_as_txt_with_reordering_columns(pp_csv, gq_pp_csv):
""" csv columns (input):
0 COUNTRY,YEAR,SERIALNO,PERSONS,puma_id,
5 HHTYPE,PERNUM,place_id,SYNTHETIC_HID,longitude,
10 latitude,AGE,SEX,RACE,SCHOOL,
15 INCTOT,SYNTHETIC_PID+made-sporder,made-age,made-empty,
20 made-race
text columns (output):
sp_id,sp_hh_id,serialno,stcotrbg,age,
sex,race,sporder,relate,sp_school_id,
sp_work_id """
pp_columns = [17, 9, 3, 8, 19, 13, 21, 18, 20, 20, 20]
aid.reorder_and_check_header(pp_csv, pp_columns, 'synth_people.txt-ipums')
# text columns (output):
# sp_id,sp_gq_id,sporder,age,sex
gq_pp_columns = [17, 9, 18, 19, 13]
aid.reorder_and_check_header(gq_pp_csv, gq_pp_columns,
'synth_gq_people.txt-ipums')
def _save_pp_as_txt_with_reordering_columns(pp_csv, gq_pp_csv):
# csv columns (input):
# 0 RT,TYPE,SERIALNO,puma_id,HINCP,
# 5 NP,place_id,SYNTHETIC_HID,longitude,latitude,
# 10 RT,puma_id,ST,SEX,AGEP,
# 15 SCH,SCHG,RELP,HISP,ESR,
# 20 PINCP,NATIVITY,OCCP,POBP,RAC1P,
# 25 SYNTHETIC_PID,school_id,workplace_id+made-sporder
# text columns (output):
# sp_id,sp_hh_id,serialno,stcotrbg,age,
# sex,race,sporder,relate,sp_school_id,
# sp_work_id
pp_columns = [26, 8, 3, 7, 15, 14, 25, 29, 18, 27, 28]
aid.reorder_and_check_header(pp_csv, pp_columns, 'synth_people.txt-us')
# text columns (output):
# sp_id,sp_gq_id,sporder,age,sex
gp_columns = [26, 8, 29, 15, 14]
aid.reorder_and_check_header(gq_pp_csv, gp_columns,
'synth_gq_people.txt-us')