2019-01-26 09:04:50 2019-01-26 09:04:50 R version 3.5.1 (2018-07-02) -- "Feather Spray" 2019-01-26 09:04:50 Copyright (C) 2018 The R Foundation for Statistical Computing 2019-01-26 09:04:50 Platform: x86_64-pc-linux-gnu (64-bit) 2019-01-26 09:04:50 2019-01-26 09:04:50 R is free software and comes with ABSOLUTELY NO WARRANTY. 2019-01-26 09:04:50 You are welcome to redistribute it under certain conditions. 2019-01-26 09:04:50 Type 'license()' or 'licence()' for distribution details. 2019-01-26 09:04:50 2019-01-26 09:04:50 Natural language support but running in an English locale 2019-01-26 09:04:50 2019-01-26 09:04:50 R is a collaborative project with many contributors. 2019-01-26 09:04:50 Type 'contributors()' for more information and 2019-01-26 09:04:50 'citation()' on how to cite R or R packages in publications. 2019-01-26 09:04:50 2019-01-26 09:04:50 Type 'demo()' for some demos, 'help()' for on-line help, or 2019-01-26 09:04:50 'help.start()' for an HTML browser interface to help. 2019-01-26 09:04:50 Type 'q()' to quit R. 2019-01-26 09:04:50 2019-01-26 09:04:50 > setwd( Sys.getenv( "RWD" ) ) 2019-01-26 09:04:50 > a <- lodown::get_catalog("censo") 2019-01-26 09:04:50 building catalog for censo 2019-01-26 09:04:50 2019-01-26 09:04:56 > # don't do 2000 it's been broken forever 2019-01-26 09:04:56 > lodown::lodown("censo", catalog=a[a$year == 2010,], output_dir= getwd()) 2019-01-26 09:04:56 locally downloading censo 2019-01-26 09:04:56 2019-01-26 09:04:59 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/AC.zip' 2019-01-26 09:04:59 cached in 2019-01-26 09:04:59 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/8d33c41dcfde91034b1afbc3105bd061.Rcache' 2019-01-26 09:04:59 copying to 2019-01-26 09:04:59 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpRKTtH7/file6a5019e5ecdc' 2019-01-26 09:04:59 2019-01-26 09:05:13 censo catalog entry 1 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1548489882/MonetDB' 2019-01-26 09:05:13 2019-01-26 09:11:53 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/AL.zip' 2019-01-26 09:11:53 cached in 2019-01-26 09:11:53 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/675d0405924a1b73a6f889f953a759ab.Rcache' 2019-01-26 09:11:53 copying to 2019-01-26 09:11:53 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpRKTtH7/file6a5019e5ecdc' 2019-01-26 09:11:53 2019-01-26 09:30:11 censo catalog entry 2 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1548489882/MonetDB' 2019-01-26 09:30:11 2019-01-26 09:33:05 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/AM.zip' 2019-01-26 09:33:05 cached in 2019-01-26 09:33:05 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/8a1e7a9111551585f7cec0b7b767e0c7.Rcache' 2019-01-26 09:33:05 copying to 2019-01-26 09:33:05 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpRKTtH7/file6a5019e5ecdc' 2019-01-26 09:33:05 2019-01-26 09:41:01 censo catalog entry 3 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1548489882/MonetDB' 2019-01-26 09:41:01 2019-01-26 10:00:52 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/AP.zip' 2019-01-26 10:00:52 cached in 2019-01-26 10:00:52 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/6eeff2ce0144bb14d5a56c6ca27fcdf9.Rcache' 2019-01-26 10:00:52 copying to 2019-01-26 10:00:52 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpRKTtH7/file6a5019e5ecdc' 2019-01-26 10:00:52 2019-01-26 10:01:09 censo catalog entry 4 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1548489882/MonetDB' 2019-01-26 10:01:09 2019-01-26 10:26:13 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/BA.zip' 2019-01-26 10:26:13 cached in 2019-01-26 10:26:13 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/f12488e852651d05e153bb9f21b670ed.Rcache' 2019-01-26 10:26:13 copying to 2019-01-26 10:26:13 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpRKTtH7/file6a5019e5ecdc' 2019-01-26 10:26:13 2019-01-26 10:42:03 censo catalog entry 5 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1548489882/MonetDB' 2019-01-26 10:42:03 2019-01-26 10:46:59 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/CE.zip' 2019-01-26 10:46:59 cached in 2019-01-26 10:46:59 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/6e5d97ea080321a3f736da278ccb0c36.Rcache' 2019-01-26 10:46:59 copying to 2019-01-26 10:46:59 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpRKTtH7/file6a5019e5ecdc' 2019-01-26 10:46:59 2019-01-26 11:06:52 censo catalog entry 6 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1548489882/MonetDB' 2019-01-26 11:06:52 2019-01-26 11:11:00 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/DF.zip' 2019-01-26 11:11:00 cached in 2019-01-26 11:11:00 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/31c64b57fe5442cb7c07b351e8c5a51c.Rcache' 2019-01-26 11:11:00 copying to 2019-01-26 11:11:00 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpRKTtH7/file6a5019e5ecdc' 2019-01-26 11:11:00 2019-01-26 11:11:36 censo catalog entry 7 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1548489882/MonetDB' 2019-01-26 11:11:36 2019-01-26 12:36:53 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/ES.zip' 2019-01-26 12:36:53 cached in 2019-01-26 12:36:53 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/b751b8a9e5ee7aa58c52b86c25bd041e.Rcache' 2019-01-26 12:36:53 copying to 2019-01-26 12:36:53 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpRKTtH7/file6a5019e5ecdc' 2019-01-26 12:36:53 2019-01-26 13:34:58 censo catalog entry 8 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1548489882/MonetDB' 2019-01-26 13:34:58 2019-01-26 13:39:09 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/GO.zip' 2019-01-26 13:39:09 cached in 2019-01-26 13:39:09 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/f29a3850a4b737df7e2e8ea62f0007b9.Rcache' 2019-01-26 13:39:09 copying to 2019-01-26 13:39:09 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpRKTtH7/file6a5019e5ecdc' 2019-01-26 13:39:09 2019-01-26 13:48:49 censo catalog entry 9 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1548489882/MonetDB' 2019-01-26 13:48:49 2019-01-26 13:51:46 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/MA.zip' 2019-01-26 13:51:46 cached in 2019-01-26 13:51:46 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/362a6e810463c8a0e38517f5163cc222.Rcache' 2019-01-26 13:51:46 copying to 2019-01-26 13:51:46 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpRKTtH7/file6a5019e5ecdc' 2019-01-26 13:51:46 2019-01-26 14:03:00 censo catalog entry 10 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1548489882/MonetDB' 2019-01-26 14:03:00 2019-01-26 14:05:44 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/MG.zip' 2019-01-26 14:05:44 cached in 2019-01-26 14:05:44 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/90c71c4f917ad6d89d0f453c2e3c2dc9.Rcache' 2019-01-26 14:05:44 copying to 2019-01-26 14:05:44 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpRKTtH7/file6a5019e5ecdc' 2019-01-26 14:05:44 2019-01-26 14:29:43 censo catalog entry 11 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1548489882/MonetDB' 2019-01-26 14:29:43 2019-01-26 14:35:38 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/MS.zip' 2019-01-26 14:35:38 cached in 2019-01-26 14:35:38 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/b5e5b1b9e2e979e74c9ec72feec10865.Rcache' 2019-01-26 14:35:38 copying to 2019-01-26 14:35:38 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpRKTtH7/file6a5019e5ecdc' 2019-01-26 14:35:38 2019-01-26 14:56:21 censo catalog entry 12 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1548489882/MonetDB' 2019-01-26 14:56:21 2019-01-26 15:17:05 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/MT.zip' 2019-01-26 15:17:05 cached in 2019-01-26 15:17:05 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/86f0b09d2b55f9efa586af32e4f2314a.Rcache' 2019-01-26 15:17:05 copying to 2019-01-26 15:17:05 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpRKTtH7/file6a5019e5ecdc' 2019-01-26 15:17:05 2019-01-26 15:42:24 censo catalog entry 13 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1548489882/MonetDB' 2019-01-26 15:42:24 2019-01-26 15:46:28 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/PA.zip' 2019-01-26 15:46:28 cached in 2019-01-26 15:46:28 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/738b3f4e5c93d2280a8b0a744134c648.Rcache' 2019-01-26 15:46:28 copying to 2019-01-26 15:46:28 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpRKTtH7/file6a5019e5ecdc' 2019-01-26 15:46:28 2019-01-26 17:28:18 censo catalog entry 14 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1548489882/MonetDB' 2019-01-26 17:28:18 2019-01-26 18:04:57 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/PB.zip' 2019-01-26 18:05:00 cached in 2019-01-26 18:05:00 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/8bd47199975bdf2964c09aa4e21648e1.Rcache' 2019-01-26 18:05:00 copying to 2019-01-26 18:05:00 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpRKTtH7/file6a5019e5ecdc' 2019-01-26 18:05:00 2019-01-26 18:31:23 censo catalog entry 15 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1548489882/MonetDB' 2019-01-26 18:31:23 2019-01-26 18:33:31 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/PE.zip' 2019-01-26 18:33:31 cached in 2019-01-26 18:33:31 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/eac1739962da73a00dfb693f03377c92.Rcache' 2019-01-26 18:33:31 copying to 2019-01-26 18:33:31 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpRKTtH7/file6a5019e5ecdc' 2019-01-26 18:33:31 2019-01-26 18:56:48 censo catalog entry 16 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1548489882/MonetDB' 2019-01-26 18:56:48 2019-01-26 18:59:07 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/PI.zip' 2019-01-26 18:59:07 cached in 2019-01-26 18:59:07 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/06c1460710d6b2b70933afe955bf06ee.Rcache' 2019-01-26 18:59:07 copying to 2019-01-26 18:59:07 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpRKTtH7/file6a5019e5ecdc' 2019-01-26 18:59:07 2019-01-26 19:08:25 censo catalog entry 17 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1548489882/MonetDB' 2019-01-26 19:08:25 2019-01-26 19:09:31 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/PR.zip' 2019-01-26 19:09:31 cached in 2019-01-26 19:09:31 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/409a9525b7a91b4618baf65cc89dce07.Rcache' 2019-01-26 19:09:31 copying to 2019-01-26 19:09:31 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpRKTtH7/file6a5019e5ecdc' 2019-01-26 19:09:31 2019-01-26 19:54:01 censo catalog entry 18 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1548489882/MonetDB' 2019-01-26 19:54:01 2019-01-26 20:17:20 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/RJ.zip' 2019-01-26 20:17:20 cached in 2019-01-26 20:17:20 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/5b82d082ec19bfb478942334dee06362.Rcache' 2019-01-26 20:17:20 copying to 2019-01-26 20:17:20 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpRKTtH7/file6a5019e5ecdc' 2019-01-26 20:17:20 2019-01-26 20:42:21 censo catalog entry 19 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1548489882/MonetDB' 2019-01-26 20:42:21 2019-01-26 20:46:26 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/RN.zip' 2019-01-26 20:46:26 cached in 2019-01-26 20:46:26 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/791786e4d34a82d9602a9782cfcf56ee.Rcache' 2019-01-26 20:46:26 copying to 2019-01-26 20:46:26 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpRKTtH7/file6a5019e5ecdc' 2019-01-26 20:46:26 2019-01-26 21:02:01 censo catalog entry 20 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1548489882/MonetDB' 2019-01-26 21:02:01 2019-01-26 21:07:07 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/RO.zip' 2019-01-26 21:07:07 cached in 2019-01-26 21:07:07 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/d1e8db0e4c49bf7785e6765a73a0ef97.Rcache' 2019-01-26 21:07:07 copying to 2019-01-26 21:07:07 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpRKTtH7/file6a5019e5ecdc' 2019-01-26 21:07:07 2019-01-26 21:13:23 censo catalog entry 21 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1548489882/MonetDB' 2019-01-26 21:13:23 2019-01-26 21:20:58 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/RR.zip' 2019-01-26 21:20:58 cached in 2019-01-26 21:20:58 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/30da4639719883b3e680399fe5f3f7c5.Rcache' 2019-01-26 21:20:58 copying to 2019-01-26 21:20:58 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpRKTtH7/file6a5019e5ecdc' 2019-01-26 21:20:58 2019-01-26 21:24:44 censo catalog entry 22 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1548489882/MonetDB' 2019-01-26 21:24:44 2019-01-26 21:49:06 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/RS.zip' 2019-01-26 21:49:08 cached in 2019-01-26 21:49:08 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/989abcab6ef8f4cc0482c4da694d254e.Rcache' 2019-01-26 21:49:08 copying to 2019-01-26 21:49:08 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpRKTtH7/file6a5019e5ecdc' 2019-01-26 21:49:08 2019-01-26 22:07:35 censo catalog entry 23 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1548489882/MonetDB' 2019-01-26 22:07:35 2019-01-26 23:03:56 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/SC.zip' 2019-01-26 23:03:58 cached in 2019-01-26 23:03:58 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/5aa8eea1b7368218b7503d61f196b586.Rcache' 2019-01-26 23:03:58 copying to 2019-01-26 23:03:58 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpRKTtH7/file6a5019e5ecdc' 2019-01-26 23:03:58 2019-01-26 23:46:52 censo catalog entry 24 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1548489882/MonetDB' 2019-01-26 23:46:52 2019-01-26 23:48:14 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/SE.zip' 2019-01-26 23:48:14 cached in 2019-01-26 23:48:14 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/af4222637a1c8e705f816d7a78284a2f.Rcache' 2019-01-26 23:48:14 copying to 2019-01-26 23:48:14 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpRKTtH7/file6a5019e5ecdc' 2019-01-26 23:48:14 2019-01-26 23:50:14 censo catalog entry 25 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1548489882/MonetDB' 2019-01-26 23:50:14 2019-01-26 23:52:10 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/SP1.zip' 2019-01-26 23:52:10 cached in 2019-01-26 23:52:10 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/5493bb945da3b02e07808de8b2c38054.Rcache' 2019-01-26 23:52:10 copying to 2019-01-26 23:52:10 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpRKTtH7/file6a5019e5ecdc' 2019-01-26 23:52:10 2019-01-26 23:55:48 censo catalog entry 26 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1548489882/MonetDB' 2019-01-26 23:55:48 2019-01-26 23:58:24 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/SP2_RM.zip' 2019-01-26 23:58:24 cached in 2019-01-26 23:58:24 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/688c1a930ab09e425507f8e308e0d3cc.Rcache' 2019-01-26 23:58:24 copying to 2019-01-26 23:58:24 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpRKTtH7/file6a5019e5ecdc' 2019-01-26 23:58:24 2019-01-27 00:05:58 censo catalog entry 27 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1548489882/MonetDB' 2019-01-27 00:05:58 2019-01-27 00:11:23 'ftp://ftp.ibge.gov.br/Censos/Censo_Demografico_2010/Resultados_Gerais_da_Amostra/Microdados/TO.zip' 2019-01-27 00:11:23 cached in 2019-01-27 00:11:23 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/319c75b43a1d30166e3a0185c3a7d1ad.Rcache' 2019-01-27 00:11:23 copying to 2019-01-27 00:11:23 '/export/scratch1/home/hannes/eanthony/r-tmp/censo/RtmpRKTtH7/file6a5019e5ecdc' 2019-01-27 00:11:23 2019-01-27 00:23:38 censo catalog entry 28 of 28 stored in '/export/scratch1/home/hannes/eanthony/r-wd/censo-1548489882/MonetDB' 2019-01-27 00:23:38 2019-01-27 01:25:58 censo survey design entry 1 of 2 stored at '/export/scratch1/home/hannes/eanthony/r-wd/censo-1548489882/dom 2010 design.rds' 2019-01-27 01:25:58 2019-01-27 05:08:37 censo survey design entry 2 of 2 stored at '/export/scratch1/home/hannes/eanthony/r-wd/censo-1548489882/pes 2010 design.rds' 2019-01-27 05:08:38 2019-01-27 05:08:38 censo local download completed 2019-01-27 05:08:38 2019-01-27 05:08:39 Warning message: 2019-01-27 05:08:39 In .Internal(gc(verbose, reset, full)) : 2019-01-27 05:08:39 Connection is garbage-collected, use dbDisconnect() to avoid this. 2019-01-27 05:08:39 > setup return code=0 2019-01-27 05:09:37 2019-01-27 05:09:37 R version 3.5.1 (2018-07-02) -- "Feather Spray" 2019-01-27 05:09:37 Copyright (C) 2018 The R Foundation for Statistical Computing 2019-01-27 05:09:37 Platform: x86_64-pc-linux-gnu (64-bit) 2019-01-27 05:09:37 2019-01-27 05:09:37 R is free software and comes with ABSOLUTELY NO WARRANTY. 2019-01-27 05:09:37 You are welcome to redistribute it under certain conditions. 2019-01-27 05:09:37 Type 'license()' or 'licence()' for distribution details. 2019-01-27 05:09:37 2019-01-27 05:09:37 Natural language support but running in an English locale 2019-01-27 05:09:37 2019-01-27 05:09:37 R is a collaborative project with many contributors. 2019-01-27 05:09:37 Type 'contributors()' for more information and 2019-01-27 05:09:37 'citation()' on how to cite R or R packages in publications. 2019-01-27 05:09:37 2019-01-27 05:09:37 Type 'demo()' for some demos, 'help()' for on-line help, or 2019-01-27 05:09:37 'help.start()' for an HTML browser interface to help. 2019-01-27 05:09:37 Type 'q()' to quit R. 2019-01-27 05:09:37 2019-01-27 05:09:38 > setwd( Sys.getenv( "RWD" ) ) 2019-01-27 05:09:38 > 2019-01-27 05:09:38 > machine_specific_replacements <- 2019-01-27 05:09:38 + list( 2019-01-27 05:09:38 + 2019-01-27 05:09:38 + # replace the folder path on macnix 2019-01-27 05:09:38 + c( 'path.expand( \"~\" ) , \"CENSO\"' , paste0( '"' , getwd() , '"' ) ) , 2019-01-27 05:09:38 + 2019-01-27 05:09:38 + # change other things in the script to be run 2019-01-27 05:09:38 + c( "hello" , "howdy" ) 2019-01-27 05:09:38 + 2019-01-27 05:09:38 + ) 2019-01-27 05:09:38 > 2019-01-27 05:09:38 > source( lodown::syntaxtractor( "censo" , replacements = machine_specific_replacements , setup_test = "test" ) , echo = TRUE ) 2019-01-27 05:09:40 2019-01-27 05:09:40 > library(lodown) 2019-01-27 05:09:40 2019-01-27 05:09:40 > censo_cat <- get_catalog("censo", output_dir = file.path("/export/scratch1/home/hannes/eanthony/r-wd/censo-1548489882")) 2019-01-27 05:09:40 building catalog for censo 2019-01-27 05:09:40 2019-01-27 05:09:48 2019-01-27 05:09:48 > censo_cat <- subset(censo_cat, year == 2010) 2019-01-27 05:09:48 2019-01-27 05:09:48 > stopifnot(nrow(censo_cat) > 0) 2019-01-27 05:09:48 2019-01-27 05:09:48 > library(DBI) 2019-01-27 05:09:53 2019-01-27 05:09:53 > library(MonetDBLite) 2019-01-27 05:09:57 2019-01-27 05:09:57 > library(survey) 2019-01-27 05:09:58 Loading required package: grid 2019-01-27 05:09:58 Loading required package: Matrix 2019-01-27 05:10:00 Loading required package: survival 2019-01-27 05:10:01 2019-01-27 05:10:01 Attaching package: ‘survey’ 2019-01-27 05:10:01 2019-01-27 05:10:01 The following object is masked from ‘package:graphics’: 2019-01-27 05:10:01 2019-01-27 05:10:01 dotchart 2019-01-27 05:10:01 2019-01-27 05:10:01 2019-01-27 05:10:01 > options(survey.lonely.psu = "adjust") 2019-01-27 05:10:01 2019-01-27 05:10:01 > censo_design <- readRDS(file.path("/export/scratch1/home/hannes/eanthony/r-wd/censo-1548489882", 2019-01-27 05:10:01 + "pes 2010 design.rds")) 2019-01-27 05:10:27 2019-01-27 05:10:27 > censo_design <- open(censo_design, driver = MonetDBLite()) 2019-01-27 05:13:48 2019-01-27 05:13:48 > censo_design <- update(censo_design, nmorpob1 = ifelse(v6531 >= 2019-01-27 05:13:48 + 0, as.numeric(v6531 < 70), NA), nmorpob2 = ifelse(v6531 >= 2019-01-27 05:13:48 + 0, as.numer .... [TRUNCATED] 2019-01-27 05:13:48 2019-01-27 05:13:48 > sum(weights(censo_design, "sampling") != 0) 2019-01-27 05:13:48 [1] 20635472 2019-01-27 05:13:48 2019-01-27 05:13:48 > svyby(~one, ~state_name, censo_design, unwtd.count) 2019-01-27 05:13:48 QQ: 'SELECT 1' 2019-01-27 05:13:48 II: Finished in 0s 2019-01-27 05:13:48 QQ: 'select one from c10' 2019-01-27 05:13:48 II: Finished in 0s 2019-01-27 05:13:48 QQ: 'SELECT 1' 2019-01-27 05:13:48 II: Finished in 0s 2019-01-27 05:13:48 QQ: 'select v0001 from c10' 2019-01-27 05:13:55 II: Finished in 6.3s 2019-01-27 05:18:26 state_name counts se 2019-01-27 05:18:26 Rondonia Rondonia 195607 0 2019-01-27 05:18:26 Acre Acre 93675 0 2019-01-27 05:18:26 Amazonas Amazonas 295034 0 2019-01-27 05:18:26 Roraima Roraima 63765 0 2019-01-27 05:18:26 Para Para 729094 0 2019-01-27 05:18:26 Amapa Amapa 78344 0 2019-01-27 05:18:26 Tocantins Tocantins 267745 0 2019-01-27 05:18:26 Maranhao Maranhao 793241 0 2019-01-27 05:18:26 Piaui Piaui 496477 0 2019-01-27 05:18:26 Ceara Ceara 846164 0 2019-01-27 05:18:26 Rio Grande do Norte Rio Grande do Norte 424586 0 2019-01-27 05:18:26 Paraiba Paraiba 571631 0 2019-01-27 05:18:26 Pernambuco Pernambuco 892250 0 2019-01-27 05:18:26 Alagoas Alagoas 349966 0 2019-01-27 05:18:26 Sergipe Sergipe 245354 0 2019-01-27 05:18:26 Bahia Bahia 1550842 0 2019-01-27 05:18:26 Minas Gerais Minas Gerais 2506265 0 2019-01-27 05:18:26 Espirito Santo Espirito Santo 400130 0 2019-01-27 05:18:26 Rio de Janeiro Rio de Janeiro 1143650 0 2019-01-27 05:18:26 Sao Paulo Sao Paulo 3651181 0 2019-01-27 05:18:26 Parana Parana 1293034 0 2019-01-27 05:18:26 Santa Catarina Santa Catarina 872242 0 2019-01-27 05:18:26 Rio Grande do Sul Rio Grande do Sul 1388443 0 2019-01-27 05:18:26 Mato Grosso do Sul Mato Grosso do Sul 276714 0 2019-01-27 05:18:26 Mato Grosso Mato Grosso 386537 0 2019-01-27 05:18:26 Goias Goias 707043 0 2019-01-27 05:18:26 Distrito Federal Distrito Federal 116458 0 2019-01-27 05:18:26 2019-01-27 05:18:26 > svytotal(~one, censo_design) 2019-01-27 05:18:26 QQ: 'SELECT 1' 2019-01-27 05:18:48 II: Finished in 22.28s 2019-01-27 05:18:48 QQ: 'select one from c10' 2019-01-27 05:18:48 II: Finished in 0s 2019-01-27 05:19:17 total SE 2019-01-27 05:19:17 one 190755799 45515 2019-01-27 05:19:17 2019-01-27 05:19:17 > svyby(~one, ~state_name, censo_design, svytotal) 2019-01-27 05:19:17 QQ: 'SELECT 1' 2019-01-27 05:19:17 II: Finished in 0s 2019-01-27 05:19:17 QQ: 'select one from c10' 2019-01-27 05:19:17 II: Finished in 0s 2019-01-27 05:19:17 QQ: 'SELECT 1' 2019-01-27 05:19:17 II: Finished in 0s 2019-01-27 05:19:17 QQ: 'select v0001 from c10' 2019-01-27 05:19:18 II: Finished in 0.2s 2019-01-27 05:23:20 state_name one se 2019-01-27 05:23:20 Rondonia Rondonia 1562409 4139.002 2019-01-27 05:23:20 Acre Acre 733559 2816.812 2019-01-27 05:23:20 Amazonas Amazonas 3483985 8497.475 2019-01-27 05:23:20 Roraima Roraima 450479 2715.777 2019-01-27 05:23:20 Para Para 7581051 10704.230 2019-01-27 05:23:20 Amapa Amapa 669526 3682.070 2019-01-27 05:23:20 Tocantins Tocantins 1383445 3564.304 2019-01-27 05:23:20 Maranhao Maranhao 6574789 10401.338 2019-01-27 05:23:20 Piaui Piaui 3118360 5851.780 2019-01-27 05:23:20 Ceara Ceara 8452381 11610.387 2019-01-27 05:23:20 Rio Grande do Norte Rio Grande do Norte 3168027 6870.938 2019-01-27 05:23:20 Paraiba Paraiba 3766528 6555.848 2019-01-27 05:23:20 Pernambuco Pernambuco 8796448 11235.871 2019-01-27 05:23:20 Alagoas Alagoas 3120494 6253.875 2019-01-27 05:23:20 Sergipe Sergipe 2068017 5506.618 2019-01-27 05:23:20 Bahia Bahia 14016906 12341.668 2019-01-27 05:23:20 Minas Gerais Minas Gerais 19597330 15527.714 2019-01-27 05:23:20 Espirito Santo Espirito Santo 3514952 6144.154 2019-01-27 05:23:20 Rio de Janeiro Rio de Janeiro 15989929 15918.107 2019-01-27 05:23:20 Sao Paulo Sao Paulo 41262199 18373.152 2019-01-27 05:23:20 Parana Parana 10444526 9467.072 2019-01-27 05:23:20 Santa Catarina Santa Catarina 6248436 6984.844 2019-01-27 05:23:20 Rio Grande do Sul Rio Grande do Sul 10693929 9797.274 2019-01-27 05:23:20 Mato Grosso do Sul Mato Grosso do Sul 2449024 5306.033 2019-01-27 05:23:20 Mato Grosso Mato Grosso 3035122 7025.334 2019-01-27 05:23:20 Goias Goias 6003788 9171.911 2019-01-27 05:23:20 Distrito Federal Distrito Federal 2570160 7524.124 2019-01-27 05:23:20 2019-01-27 05:23:20 > svymean(~v6033, censo_design) 2019-01-27 05:23:20 QQ: 'SELECT 1' 2019-01-27 05:23:20 II: Finished in 0s 2019-01-27 05:23:20 QQ: 'select v6033 from c10' 2019-01-27 05:23:20 II: Finished in 0s 2019-01-27 05:24:00 mean SE 2019-01-27 05:24:00 v6033 44.532 0.027 2019-01-27 05:24:00 2019-01-27 05:24:00 > svyby(~v6033, ~state_name, censo_design, svymean) 2019-01-27 05:24:00 QQ: 'SELECT 1' 2019-01-27 05:24:00 II: Finished in 0s 2019-01-27 05:24:00 QQ: 'select v6033 from c10' 2019-01-27 05:24:00 II: Finished in 0s 2019-01-27 05:24:00 QQ: 'SELECT 1' 2019-01-27 05:24:00 II: Finished in 0s 2019-01-27 05:24:00 QQ: 'select v0001 from c10' 2019-01-27 05:24:01 II: Finished in 0.21s 2019-01-27 05:27:43 state_name v6033 se 2019-01-27 05:27:43 Rondonia Rondonia 43.47609 0.26288751 2019-01-27 05:27:43 Acre Acre 44.14539 0.36886548 2019-01-27 05:27:43 Amazonas Amazonas 44.89294 0.27012795 2019-01-27 05:27:43 Roraima Roraima 44.61115 0.52593285 2019-01-27 05:27:43 Para Para 44.06793 0.13521800 2019-01-27 05:27:43 Amapa Amapa 44.36371 0.39784164 2019-01-27 05:27:43 Tocantins Tocantins 44.08827 0.27967332 2019-01-27 05:27:43 Maranhao Maranhao 44.39162 0.13861694 2019-01-27 05:27:43 Piaui Piaui 44.23805 0.17762998 2019-01-27 05:27:43 Ceara Ceara 43.97193 0.14687828 2019-01-27 05:27:43 Rio Grande do Norte Rio Grande do Norte 44.05621 0.18014194 2019-01-27 05:27:43 Paraiba Paraiba 45.40817 0.14591457 2019-01-27 05:27:43 Pernambuco Pernambuco 44.35515 0.12709112 2019-01-27 05:27:43 Alagoas Alagoas 44.39060 0.22423277 2019-01-27 05:27:43 Sergipe Sergipe 43.67018 0.24654787 2019-01-27 05:27:43 Bahia Bahia 44.00062 0.10321527 2019-01-27 05:27:43 Minas Gerais Minas Gerais 44.22639 0.07185371 2019-01-27 05:27:43 Espirito Santo Espirito Santo 44.43069 0.15153763 2019-01-27 05:27:43 Rio de Janeiro Rio de Janeiro 45.11529 0.09207557 2019-01-27 05:27:43 Sao Paulo Sao Paulo 44.86147 0.06474417 2019-01-27 05:27:43 Parana Parana 44.88411 0.09895079 2019-01-27 05:27:43 Santa Catarina Santa Catarina 44.42404 0.12380128 2019-01-27 05:27:43 Rio Grande do Sul Rio Grande do Sul 45.18820 0.09633780 2019-01-27 05:27:43 Mato Grosso do Sul Mato Grosso do Sul 45.08575 0.20559708 2019-01-27 05:27:43 Mato Grosso Mato Grosso 43.70309 0.21651840 2019-01-27 05:27:43 Goias Goias 44.16120 0.13667909 2019-01-27 05:27:43 Distrito Federal Distrito Federal 43.61118 0.28911335 2019-01-27 05:27:43 2019-01-27 05:27:43 > svymean(~sexo, censo_design) 2019-01-27 05:27:43 QQ: 'SELECT 1' 2019-01-27 05:27:43 II: Finished in 0s 2019-01-27 05:27:43 QQ: 'select v0601 from c10' 2019-01-27 05:27:45 II: Finished in 1.27s 2019-01-27 05:28:19 mean SE 2019-01-27 05:28:19 sexomasculino 0.48967 1e-04 2019-01-27 05:28:19 sexofeminino 0.51033 1e-04 2019-01-27 05:28:19 2019-01-27 05:28:19 > svyby(~sexo, ~state_name, censo_design, svymean) 2019-01-27 05:28:19 QQ: 'SELECT 1' 2019-01-27 05:28:19 II: Finished in 0s 2019-01-27 05:28:19 QQ: 'select v0601 from c10' 2019-01-27 05:28:19 II: Finished in 0.11s 2019-01-27 05:28:19 QQ: 'SELECT 1' 2019-01-27 05:28:19 II: Finished in 0s 2019-01-27 05:28:19 QQ: 'select v0001 from c10' 2019-01-27 05:28:20 II: Finished in 0.14s 2019-01-27 05:32:04 state_name sexomasculino sexofeminino se1 2019-01-27 05:32:04 Rondonia Rondonia 0.5089301 0.4910699 0.0008077172 2019-01-27 05:32:04 Acre Acre 0.5021055 0.4978945 0.0013448422 2019-01-27 05:32:04 Amazonas Amazonas 0.5032108 0.4967892 0.0007410689 2019-01-27 05:32:04 Roraima Roraima 0.5080348 0.4919652 0.0019040632 2019-01-27 05:32:04 Para Para 0.5041302 0.4958698 0.0005426885 2019-01-27 05:32:04 Amapa Amapa 0.5005556 0.4994444 0.0013983607 2019-01-27 05:32:04 Tocantins Tocantins 0.5077354 0.4922646 0.0008925904 2019-01-27 05:32:04 Maranhao Maranhao 0.4960638 0.5039362 0.0005539068 2019-01-27 05:32:04 Piaui Piaui 0.4901365 0.5098635 0.0007275960 2019-01-27 05:32:04 Ceara Ceara 0.4874470 0.5125530 0.0004426686 2019-01-27 05:32:04 Rio Grande do Norte Rio Grande do Norte 0.4889122 0.5110878 0.0007395122 2019-01-27 05:32:04 Paraiba Paraiba 0.4843662 0.5156338 0.0006785847 2019-01-27 05:32:04 Pernambuco Pernambuco 0.4809533 0.5190467 0.0004696961 2019-01-27 05:32:04 Alagoas Alagoas 0.4844640 0.5155360 0.0008064715 2019-01-27 05:32:04 Sergipe Sergipe 0.4859926 0.5140074 0.0009212660 2019-01-27 05:32:04 Bahia Bahia 0.4907121 0.5092879 0.0003402313 2019-01-27 05:32:04 Minas Gerais Minas Gerais 0.4919995 0.5080005 0.0002878725 2019-01-27 05:32:04 Espirito Santo Espirito Santo 0.4925296 0.5074704 0.0006152315 2019-01-27 05:32:04 Rio de Janeiro Rio de Janeiro 0.4769051 0.5230949 0.0004201821 2019-01-27 05:32:04 Sao Paulo Sao Paulo 0.4865924 0.5134076 0.0002332859 2019-01-27 05:32:04 Parana Parana 0.4912615 0.5087385 0.0003754640 2019-01-27 05:32:04 Santa Catarina Santa Catarina 0.4961818 0.5038182 0.0004275229 2019-01-27 05:32:04 Rio Grande do Sul Rio Grande do Sul 0.4867301 0.5132699 0.0003890406 2019-01-27 05:32:04 Mato Grosso do Sul Mato Grosso do Sul 0.4981282 0.5018718 0.0007656303 2019-01-27 05:32:04 Mato Grosso Mato Grosso 0.5105350 0.4894650 0.0007608733 2019-01-27 05:32:04 Goias Goias 0.4966243 0.5033757 0.0005728599 2019-01-27 05:32:04 Distrito Federal Distrito Federal 0.4781337 0.5218663 0.0012292089 2019-01-27 05:32:04 se2 2019-01-27 05:32:04 Rondonia 0.0008077172 2019-01-27 05:32:04 Acre 0.0013448422 2019-01-27 05:32:04 Amazonas 0.0007410689 2019-01-27 05:32:04 Roraima 0.0019040632 2019-01-27 05:32:04 Para 0.0005426885 2019-01-27 05:32:04 Amapa 0.0013983607 2019-01-27 05:32:04 Tocantins 0.0008925904 2019-01-27 05:32:04 Maranhao 0.0005539068 2019-01-27 05:32:04 Piaui 0.0007275960 2019-01-27 05:32:04 Ceara 0.0004426686 2019-01-27 05:32:04 Rio Grande do Norte 0.0007395122 2019-01-27 05:32:04 Paraiba 0.0006785847 2019-01-27 05:32:04 Pernambuco 0.0004696961 2019-01-27 05:32:04 Alagoas 0.0008064715 2019-01-27 05:32:04 Sergipe 0.0009212660 2019-01-27 05:32:04 Bahia 0.0003402313 2019-01-27 05:32:04 Minas Gerais 0.0002878725 2019-01-27 05:32:04 Espirito Santo 0.0006152315 2019-01-27 05:32:04 Rio de Janeiro 0.0004201821 2019-01-27 05:32:04 Sao Paulo 0.0002332859 2019-01-27 05:32:04 Parana 0.0003754640 2019-01-27 05:32:04 Santa Catarina 0.0004275229 2019-01-27 05:32:04 Rio Grande do Sul 0.0003890406 2019-01-27 05:32:04 Mato Grosso do Sul 0.0007656303 2019-01-27 05:32:04 Mato Grosso 0.0007608733 2019-01-27 05:32:04 Goias 0.0005728599 2019-01-27 05:32:04 Distrito Federal 0.0012292089 2019-01-27 05:32:04 2019-01-27 05:32:04 > svytotal(~v6033, censo_design) 2019-01-27 05:32:04 QQ: 'SELECT 1' 2019-01-27 05:32:04 II: Finished in 0s 2019-01-27 05:32:04 QQ: 'select v6033 from c10' 2019-01-27 05:32:04 II: Finished in 0s 2019-01-27 05:32:21 total SE 2019-01-27 05:32:21 v6033 8494688084 5609608 2019-01-27 05:32:21 2019-01-27 05:32:21 > svyby(~v6033, ~state_name, censo_design, svytotal) 2019-01-27 05:32:21 QQ: 'SELECT 1' 2019-01-27 05:32:21 II: Finished in 0s 2019-01-27 05:32:21 QQ: 'select v6033 from c10' 2019-01-27 05:32:21 II: Finished in 0s 2019-01-27 05:32:21 QQ: 'SELECT 1' 2019-01-27 05:32:21 II: Finished in 0s 2019-01-27 05:32:21 QQ: 'select v0001 from c10' 2019-01-27 05:32:21 II: Finished in 0.14s 2019-01-27 05:35:59 state_name v6033 se 2019-01-27 05:35:59 Rondonia Rondonia 67927439 419956.8 2019-01-27 05:35:59 Acre Acre 32383247 298944.8 2019-01-27 05:35:59 Amazonas Amazonas 156406314 1014699.0 2019-01-27 05:35:59 Roraima Roraima 20096387 259513.3 2019-01-27 05:35:59 Para Para 334081201 1127913.0 2019-01-27 05:35:59 Amapa Amapa 29702659 330004.5 2019-01-27 05:35:59 Tocantins Tocantins 60993702 387112.7 2019-01-27 05:35:59 Maranhao Maranhao 291865565 985990.6 2019-01-27 05:35:59 Piaui Piaui 137950175 571053.8 2019-01-27 05:35:59 Ceara Ceara 371667509 1284450.5 2019-01-27 05:35:59 Rio Grande do Norte Rio Grande do Norte 139571251 662696.9 2019-01-27 05:35:59 Paraiba Paraiba 171031139 656625.9 2019-01-27 05:35:59 Pernambuco Pernambuco 390167775 1168045.9 2019-01-27 05:35:59 Alagoas Alagoas 138520597 747684.8 2019-01-27 05:35:59 Sergipe Sergipe 90310670 573040.3 2019-01-27 05:35:59 Bahia Bahia 616752560 1609652.3 2019-01-27 05:35:59 Minas Gerais Minas Gerais 866719202 1582346.1 2019-01-27 05:35:59 Espirito Santo Espirito Santo 156171746 620178.8 2019-01-27 05:35:59 Rio de Janeiro Rio de Janeiro 721390292 1653565.2 2019-01-27 05:35:59 Sao Paulo Sao Paulo 1851082734 2919257.7 2019-01-27 05:35:59 Parana Parana 468793290 1134230.9 2019-01-27 05:35:59 Santa Catarina Santa Catarina 277580763 858334.0 2019-01-27 05:35:59 Rio Grande do Sul Rio Grande do Sul 483239360 1161857.8 2019-01-27 05:35:59 Mato Grosso do Sul Mato Grosso do Sul 110416076 577731.4 2019-01-27 05:35:59 Mato Grosso Mato Grosso 132644212 685210.9 2019-01-27 05:35:59 Goias Goias 265134506 928830.6 2019-01-27 05:35:59 Distrito Federal Distrito Federal 112087713 761934.0 2019-01-27 05:35:59 2019-01-27 05:35:59 > svytotal(~sexo, censo_design) 2019-01-27 05:35:59 QQ: 'SELECT 1' 2019-01-27 05:36:57 II: Finished in 58.89s 2019-01-27 05:36:58 QQ: 'select v0601 from c10' 2019-01-27 05:36:58 II: Finished in 0.14s 2019-01-27 05:37:26 total SE 2019-01-27 05:37:26 sexomasculino 93406990 27463 2019-01-27 05:37:26 sexofeminino 97348809 28283 2019-01-27 05:37:26 2019-01-27 05:37:26 > svyby(~sexo, ~state_name, censo_design, svytotal) 2019-01-27 05:37:26 QQ: 'SELECT 1' 2019-01-27 05:37:26 II: Finished in 0s 2019-01-27 05:37:26 QQ: 'select v0601 from c10' 2019-01-27 05:37:27 II: Finished in 0.14s 2019-01-27 05:37:28 QQ: 'SELECT 1' 2019-01-27 05:37:28 II: Finished in 0s 2019-01-27 05:37:28 QQ: 'select v0001 from c10' 2019-01-27 05:37:28 II: Finished in 0.18s 2019-01-27 05:41:13 state_name sexomasculino sexofeminino se1 2019-01-27 05:41:13 Rondonia Rondonia 795157 767252 2554.560 2019-01-27 05:41:13 Acre Acre 368324 365235 1897.240 2019-01-27 05:41:13 Amazonas Amazonas 1753179 1730806 5350.793 2019-01-27 05:41:13 Roraima Roraima 228859 221620 1516.803 2019-01-27 05:41:13 Para Para 3821837 3759214 7471.099 2019-01-27 05:41:13 Amapa Amapa 335135 334391 2167.409 2019-01-27 05:41:13 Tocantins Tocantins 702424 681021 2031.489 2019-01-27 05:41:13 Maranhao Maranhao 3261515 3313274 6216.475 2019-01-27 05:41:13 Piaui Piaui 1528422 1589938 3745.444 2019-01-27 05:41:13 Ceara Ceara 4120088 4332293 6150.622 2019-01-27 05:41:13 Rio Grande do Norte Rio Grande do Norte 1548887 1619140 4376.956 2019-01-27 05:41:13 Paraiba Paraiba 1824379 1942149 4154.179 2019-01-27 05:41:13 Pernambuco Pernambuco 4230681 4565767 6553.478 2019-01-27 05:41:13 Alagoas Alagoas 1511767 1608727 3681.693 2019-01-27 05:41:13 Sergipe Sergipe 1005041 1062976 3260.166 2019-01-27 05:41:13 Bahia Bahia 6878266 7138640 7219.615 2019-01-27 05:41:13 Minas Gerais Minas Gerais 9641877 9955453 9524.358 2019-01-27 05:41:13 Espirito Santo Espirito Santo 1731218 1783734 3882.857 2019-01-27 05:41:13 Rio de Janeiro Rio de Janeiro 7625679 8364250 10920.366 2019-01-27 05:41:13 Sao Paulo Sao Paulo 20077873 21184326 13014.578 2019-01-27 05:41:13 Parana Parana 5130994 5313532 6372.739 2019-01-27 05:41:13 Santa Catarina Santa Catarina 3100360 3148076 4390.688 2019-01-27 05:41:13 Rio Grande do Sul Rio Grande do Sul 5205057 5488872 6171.417 2019-01-27 05:41:13 Mato Grosso do Sul Mato Grosso do Sul 1219928 1229096 2964.964 2019-01-27 05:41:13 Mato Grosso Mato Grosso 1549536 1485586 3901.887 2019-01-27 05:41:13 Goias Goias 2981627 3022161 5729.441 2019-01-27 05:41:13 Distrito Federal Distrito Federal 1228880 1341280 4709.394 2019-01-27 05:41:13 se2 2019-01-27 05:41:13 Rondonia 2290.544 2019-01-27 05:41:13 Acre 1524.385 2019-01-27 05:41:13 Amazonas 4563.453 2019-01-27 05:41:13 Roraima 1688.436 2019-01-27 05:41:13 Para 5957.017 2019-01-27 05:41:13 Amapa 1957.696 2019-01-27 05:41:13 Tocantins 2292.632 2019-01-27 05:41:13 Maranhao 6480.564 2019-01-27 05:41:13 Piaui 3657.919 2019-01-27 05:41:13 Ceara 7618.144 2019-01-27 05:41:13 Rio Grande do Norte 3913.970 2019-01-27 05:41:13 Paraiba 4157.290 2019-01-27 05:41:13 Pernambuco 7393.445 2019-01-27 05:41:13 Alagoas 4336.396 2019-01-27 05:41:13 Sergipe 3437.799 2019-01-27 05:41:13 Bahia 8355.900 2019-01-27 05:41:13 Minas Gerais 9669.347 2019-01-27 05:41:13 Espirito Santo 3622.581 2019-01-27 05:41:13 Rio de Janeiro 9818.438 2019-01-27 05:41:13 Sao Paulo 13602.330 2019-01-27 05:41:13 Parana 5902.149 2019-01-27 05:41:13 Santa Catarina 4403.279 2019-01-27 05:41:13 Rio Grande do Sul 6684.385 2019-01-27 05:41:13 Mato Grosso do Sul 3511.597 2019-01-27 05:41:13 Mato Grosso 4471.896 2019-01-27 05:41:13 Goias 5736.100 2019-01-27 05:41:13 Distrito Federal 5120.614 2019-01-27 05:41:13 2019-01-27 05:41:13 > svyquantile(~v6033, censo_design, 0.5) 2019-01-27 05:41:13 QQ: 'SELECT 1' 2019-01-27 05:41:16 II: Finished in 2.88s 2019-01-27 05:41:16 QQ: 'select v6033 from c10' 2019-01-27 05:41:16 II: Finished in 0s 2019-01-27 05:41:50 QQ: 'SELECT 1' 2019-01-27 05:41:50 II: Finished in 0s 2019-01-27 05:42:35 Statistic: 2019-01-27 05:42:35 v6033 2019-01-27 05:42:35 q0.5 30 2019-01-27 05:42:35 SE: 2019-01-27 05:42:35 v6033 2019-01-27 05:42:35 q0.5 0.25 2019-01-27 05:42:35 2019-01-27 05:42:35 > svyby(~v6033, ~state_name, censo_design, svyquantile, 2019-01-27 05:42:35 + 0.5, ci = TRUE, keep.var = TRUE) 2019-01-27 05:42:35 QQ: 'SELECT 1' 2019-01-27 05:42:35 II: Finished in 0s 2019-01-27 05:42:35 QQ: 'select v6033 from c10' 2019-01-27 05:42:35 II: Finished in 0s 2019-01-27 05:42:35 QQ: 'SELECT 1' 2019-01-27 05:42:35 II: Finished in 0s 2019-01-27 05:42:35 QQ: 'select v0001 from c10' 2019-01-27 05:42:35 II: Finished in 0.19s 2019-01-27 05:46:50 state_name V1 se 2019-01-27 05:46:50 Rondonia Rondonia 27 0.25 2019-01-27 05:46:50 Acre Acre 24 0.25 2019-01-27 05:46:50 Amazonas Amazonas 24 0.25 2019-01-27 05:46:50 Roraima Roraima 24 0.25 2019-01-27 05:46:50 Para Para 25 0.25 2019-01-27 05:46:50 Amapa Amapa 23 0.25 2019-01-27 05:46:50 Tocantins Tocantins 26 0.25 2019-01-27 05:46:50 Maranhao Maranhao 25 0.25 2019-01-27 05:46:50 Piaui Piaui 28 0.25 2019-01-27 05:46:50 Ceara Ceara 28 0.25 2019-01-27 05:46:50 Rio Grande do Norte Rio Grande do Norte 29 0.25 2019-01-27 05:46:50 Paraiba Paraiba 29 0.25 2019-01-27 05:46:50 Pernambuco Pernambuco 29 0.25 2019-01-27 05:46:50 Alagoas Alagoas 26 0.25 2019-01-27 05:46:50 Sergipe Sergipe 27 0.25 2019-01-27 05:46:50 Bahia Bahia 28 0.25 2019-01-27 05:46:50 Minas Gerais Minas Gerais 31 0.25 2019-01-27 05:46:50 Espirito Santo Espirito Santo 30 0.25 2019-01-27 05:46:50 Rio de Janeiro Rio de Janeiro 33 0.25 2019-01-27 05:46:50 Sao Paulo Sao Paulo 32 0.25 2019-01-27 05:46:50 Parana Parana 31 0.25 2019-01-27 05:46:50 Santa Catarina Santa Catarina 31 0.25 2019-01-27 05:46:50 Rio Grande do Sul Rio Grande do Sul 33 0.25 2019-01-27 05:46:50 Mato Grosso do Sul Mato Grosso do Sul 29 0.25 2019-01-27 05:46:50 Mato Grosso Mato Grosso 28 0.25 2019-01-27 05:46:50 Goias Goias 30 0.25 2019-01-27 05:46:50 Distrito Federal Distrito Federal 29 0.25 2019-01-27 05:46:50 2019-01-27 05:46:50 > svyratio(numerator = ~nmorpob1, denominator = ~nmorpob1 + 2019-01-27 05:46:50 + one, censo_design, na.rm = TRUE) 2019-01-27 05:46:50 QQ: 'SELECT 1' 2019-01-27 05:51:39 II: Finished in 4.82s 2019-01-27 05:51:39 QQ: 'select v6531 from c10' 2019-01-27 05:52:15 II: Finished in 35.95s 2019-01-27 05:52:16 QQ: 'SELECT 1' 2019-01-27 05:52:16 II: Finished in 0s 2019-01-27 05:52:16 QQ: 'select one, v6531 from c10' 2019-01-27 05:52:16 II: Finished in 0.03s 2019-01-27 05:56:16 QQ: 'SELECT 1' 2019-01-27 05:56:16 II: Finished in 0s 2019-01-27 05:57:07 Ratio estimator: svyratio.svyrep.design(numerator = ~nmorpob1, denominator = ~nmorpob1 + 2019-01-27 05:57:07 one, censo_design, na.rm = TRUE) 2019-01-27 05:57:07 Ratios= 2019-01-27 05:57:07 nmorpob1 one 2019-01-27 05:57:07 nmorpob1 1 0.09317731 2019-01-27 05:57:07 SEs= 2019-01-27 05:57:07 [,1] [,2] 2019-01-27 05:57:07 [1,] 0 0.0001623267 2019-01-27 05:57:07 2019-01-27 05:57:07 > sub_censo_design <- subset(censo_design, v0640 == 2019-01-27 05:57:07 + 1) 2019-01-27 05:57:07 QQ: 'SELECT 1' 2019-01-27 05:57:07 II: Finished in 0s 2019-01-27 05:57:07 QQ: 'select v0640 from c10' 2019-01-27 05:57:08 II: Finished in 0.73s 2019-01-27 05:58:09 2019-01-27 05:58:09 > svymean(~v6033, sub_censo_design) 2019-01-27 05:58:09 QQ: 'SELECT 1' 2019-01-27 05:58:09 II: Finished in 0s 2019-01-27 05:58:09 QQ: 'select v6033 from c10' 2019-01-27 05:58:09 II: Finished in 0s 2019-01-27 05:58:21 mean SE 2019-01-27 05:58:21 v6033 45.922 0.0097 2019-01-27 05:58:21 2019-01-27 05:58:21 > this_result <- svymean(~v6033, censo_design) 2019-01-27 05:58:21 QQ: 'SELECT 1' 2019-01-27 05:58:47 II: Finished in 26.22s 2019-01-27 05:58:47 QQ: 'select v6033 from c10' 2019-01-27 05:58:47 II: Finished in 0s 2019-01-27 05:59:19 2019-01-27 05:59:19 > coef(this_result) 2019-01-27 05:59:19 v6033 2019-01-27 05:59:19 44.53174 2019-01-27 05:59:19 2019-01-27 05:59:19 > SE(this_result) 2019-01-27 05:59:19 [1] 0.02698713 2019-01-27 05:59:19 2019-01-27 05:59:19 > confint(this_result) 2019-01-27 05:59:19 2.5 % 97.5 % 2019-01-27 05:59:19 v6033 44.47885 44.58464 2019-01-27 05:59:19 2019-01-27 05:59:19 > cv(this_result) 2019-01-27 05:59:19 v6033 2019-01-27 05:59:19 0.0006060202 2019-01-27 05:59:19 2019-01-27 05:59:19 > grouped_result <- svyby(~v6033, ~state_name, censo_design, 2019-01-27 05:59:19 + svymean) 2019-01-27 05:59:19 QQ: 'SELECT 1' 2019-01-27 05:59:19 II: Finished in 0s 2019-01-27 05:59:19 QQ: 'select v6033 from c10' 2019-01-27 05:59:19 II: Finished in 0s 2019-01-27 05:59:19 QQ: 'SELECT 1' 2019-01-27 05:59:19 II: Finished in 0s 2019-01-27 05:59:19 QQ: 'select v0001 from c10' 2019-01-27 05:59:19 II: Finished in 0.19s 2019-01-27 06:03:05 2019-01-27 06:03:05 > coef(grouped_result) 2019-01-27 06:03:05 Rondonia Acre Amazonas Roraima 2019-01-27 06:03:05 43.47609 44.14539 44.89294 44.61115 2019-01-27 06:03:05 Para Amapa Tocantins Maranhao 2019-01-27 06:03:05 44.06793 44.36371 44.08827 44.39162 2019-01-27 06:03:05 Piaui Ceara Rio Grande do Norte Paraiba 2019-01-27 06:03:05 44.23805 43.97193 44.05621 45.40817 2019-01-27 06:03:05 Pernambuco Alagoas Sergipe Bahia 2019-01-27 06:03:05 44.35515 44.39060 43.67018 44.00062 2019-01-27 06:03:05 Minas Gerais Espirito Santo Rio de Janeiro Sao Paulo 2019-01-27 06:03:05 44.22639 44.43069 45.11529 44.86147 2019-01-27 06:03:05 Parana Santa Catarina Rio Grande do Sul Mato Grosso do Sul 2019-01-27 06:03:05 44.88411 44.42404 45.18820 45.08575 2019-01-27 06:03:05 Mato Grosso Goias Distrito Federal 2019-01-27 06:03:05 43.70309 44.16120 43.61118 2019-01-27 06:03:05 2019-01-27 06:03:05 > SE(grouped_result) 2019-01-27 06:03:05 [1] 0.26288751 0.36886548 0.27012795 0.52593285 0.13521800 0.39784164 2019-01-27 06:03:05 [7] 0.27967332 0.13861694 0.17762998 0.14687828 0.18014194 0.14591457 2019-01-27 06:03:05 [13] 0.12709112 0.22423277 0.24654787 0.10321527 0.07185371 0.15153763 2019-01-27 06:03:05 [19] 0.09207557 0.06474417 0.09895079 0.12380128 0.09633780 0.20559708 2019-01-27 06:03:05 [25] 0.21651840 0.13667909 0.28911335 2019-01-27 06:03:05 2019-01-27 06:03:05 > confint(grouped_result) 2019-01-27 06:03:05 2.5 % 97.5 % 2019-01-27 06:03:05 Rondonia 42.96084 43.99134 2019-01-27 06:03:05 Acre 43.42243 44.86835 2019-01-27 06:03:05 Amazonas 44.36349 45.42238 2019-01-27 06:03:05 Roraima 43.58034 45.64196 2019-01-27 06:03:05 Para 43.80290 44.33295 2019-01-27 06:03:05 Amapa 43.58396 45.14347 2019-01-27 06:03:05 Tocantins 43.54012 44.63642 2019-01-27 06:03:05 Maranhao 44.11994 44.66331 2019-01-27 06:03:05 Piaui 43.88990 44.58620 2019-01-27 06:03:05 Ceara 43.68405 44.25981 2019-01-27 06:03:05 Rio Grande do Norte 43.70313 44.40928 2019-01-27 06:03:05 Paraiba 45.12218 45.69416 2019-01-27 06:03:05 Pernambuco 44.10606 44.60424 2019-01-27 06:03:05 Alagoas 43.95111 44.83009 2019-01-27 06:03:05 Sergipe 43.18695 44.15340 2019-01-27 06:03:05 Bahia 43.79832 44.20292 2019-01-27 06:03:05 Minas Gerais 44.08556 44.36722 2019-01-27 06:03:05 Espirito Santo 44.13368 44.72770 2019-01-27 06:03:05 Rio de Janeiro 44.93483 45.29576 2019-01-27 06:03:05 Sao Paulo 44.73457 44.98836 2019-01-27 06:03:05 Parana 44.69017 45.07805 2019-01-27 06:03:05 Santa Catarina 44.18139 44.66668 2019-01-27 06:03:05 Rio Grande do Sul 44.99938 45.37701 2019-01-27 06:03:05 Mato Grosso do Sul 44.68278 45.48871 2019-01-27 06:03:05 Mato Grosso 43.27872 44.12746 2019-01-27 06:03:05 Goias 43.89332 44.42909 2019-01-27 06:03:05 Distrito Federal 43.04453 44.17783 2019-01-27 06:03:05 2019-01-27 06:03:05 > cv(grouped_result) 2019-01-27 06:03:05 Rondonia Acre Amazonas Roraima 2019-01-27 06:03:05 0.006046714 0.008355697 0.006017159 0.011789269 2019-01-27 06:03:05 Para Amapa Tocantins Maranhao 2019-01-27 06:03:05 0.003068399 0.008967727 0.006343485 0.003122592 2019-01-27 06:03:05 Piaui Ceara Rio Grande do Norte Paraiba 2019-01-27 06:03:05 0.004015321 0.003340274 0.004088912 0.003213399 2019-01-27 06:03:05 Pernambuco Alagoas Sergipe Bahia 2019-01-27 06:03:05 0.002865307 0.005051357 0.005645681 0.002345768 2019-01-27 06:03:05 Minas Gerais Espirito Santo Rio de Janeiro Sao Paulo 2019-01-27 06:03:05 0.001624679 0.003410652 0.002040895 0.001443202 2019-01-27 06:03:05 Parana Santa Catarina Rio Grande do Sul Mato Grosso do Sul 2019-01-27 06:03:05 0.002204584 0.002786808 0.002131924 0.004560135 2019-01-27 06:03:05 Mato Grosso Goias Distrito Federal 2019-01-27 06:03:05 0.004954304 0.003095004 0.006629340 2019-01-27 06:03:05 2019-01-27 06:03:05 > degf(censo_design) 2019-01-27 06:03:05 [1] 79 2019-01-27 06:03:05 2019-01-27 06:03:05 > svyvar(~v6033, censo_design) 2019-01-27 06:03:05 QQ: 'SELECT 1' 2019-01-27 06:03:31 II: Finished in 25.52s 2019-01-27 06:03:31 QQ: 'select v6033 from c10' 2019-01-27 06:03:31 II: Finished in 0s 2019-01-27 06:05:00 variance SE 2019-01-27 06:05:00 v6033 11161 22.895 2019-01-27 06:05:00 2019-01-27 06:05:00 > svymean(~v6033, censo_design, deff = TRUE) 2019-01-27 06:05:00 QQ: 'SELECT 1' 2019-01-27 06:05:17 II: Finished in 17.13s 2019-01-27 06:05:18 QQ: 'select v6033 from c10' 2019-01-27 06:05:18 II: Finished in 0s 2019-01-27 06:05:39 QQ: 'SELECT 1' 2019-01-27 06:05:39 II: Finished in 0s 2019-01-27 06:05:39 mean SE DEff 2019-01-27 06:05:39 v6033 44.531742 0.026987 1.5099 2019-01-27 06:05:39 2019-01-27 06:05:39 > svymean(~v6033, censo_design, deff = "replace") 2019-01-27 06:05:39 QQ: 'SELECT 1' 2019-01-27 06:05:39 II: Finished in 0s 2019-01-27 06:05:39 QQ: 'select v6033 from c10' 2019-01-27 06:05:39 II: Finished in 0s 2019-01-27 06:06:01 QQ: 'SELECT 1' 2019-01-27 06:06:01 II: Finished in 0s 2019-01-27 06:06:02 mean SE DEff 2019-01-27 06:06:02 v6033 44.531742 0.026987 1.3465 2019-01-27 06:06:02 2019-01-27 06:06:02 > svyciprop(~nmorpob6, censo_design, method = "likelihood", 2019-01-27 06:06:02 + na.rm = TRUE) 2019-01-27 06:06:21 QQ: 'SELECT 1' 2019-01-27 06:06:21 II: Finished in 0s 2019-01-27 06:06:21 QQ: 'select v6531 from c10' 2019-01-27 06:06:21 II: Finished in 0.06s 2019-01-27 06:36:12 QQ: 'SELECT 1' 2019-01-27 06:36:12 II: Finished in 0s 2019-01-27 06:36:12 QQ: 'select v6531 from c10' 2019-01-27 06:36:12 II: Finished in 0.08s 2019-01-27 06:40:45 2.5% 97.5% 2019-01-27 06:40:45 nmorpob6 0.365 NA NA 2019-01-27 06:40:45 2019-01-27 06:40:45 > svyttest(v6033 ~ nmorpob6, censo_design) 2019-01-27 06:41:06 QQ: 'SELECT 1' 2019-01-27 06:41:38 II: Finished in 32.54s 2019-01-27 06:41:38 QQ: 'select v6033, v6531 from c10' 2019-01-27 06:41:40 II: Finished in 1.37s 2019-01-27 07:04:58 2019-01-27 07:04:58 Design-based t-test 2019-01-27 07:04:58 2019-01-27 07:04:58 data: v6033 ~ nmorpob6 2019-01-27 07:04:58 t = 9.9732, df = 78, p-value = 1.421e-15 2019-01-27 07:04:58 alternative hypothesis: true difference in mean is not equal to 0 2019-01-27 07:04:58 95 percent confidence interval: 2019-01-27 07:04:58 0.4620185 0.6880306 2019-01-27 07:04:58 sample estimates: 2019-01-27 07:04:58 difference in mean 2019-01-27 07:04:58 0.5750246 2019-01-27 07:04:58 2019-01-27 07:04:58 2019-01-27 07:04:58 > svychisq(~nmorpob6 + sexo, censo_design) 2019-01-27 07:04:58 QQ: 'SELECT 1' 2019-01-27 07:04:58 II: Finished in 0s 2019-01-27 07:04:58 QQ: 'select v6531, v0601 from c10' 2019-01-27 07:05:01 II: Finished in 3.13s 2019-01-27 07:05:23 QQ: 'SELECT 1' 2019-01-27 07:05:23 II: Finished in 0s 2019-01-27 07:05:23 QQ: 'select v6531, v0601 from c10' 2019-01-27 07:05:24 II: Finished in 0.23s 2019-01-27 07:05:49 QQ: 'SELECT 1' 2019-01-27 07:05:49 II: Finished in 0s 2019-01-27 07:10:32 QQ: 'SELECT 1' 2019-01-27 07:10:32 II: Finished in 0s 2019-01-27 07:10:32 QQ: 'select v6531, v0601 from c10' 2019-01-27 07:10:32 II: Finished in 0.18s 2019-01-27 07:10:50 2019-01-27 07:10:50 Pearson's X^2: Rao & Scott adjustment 2019-01-27 07:10:50 2019-01-27 07:10:50 data: NextMethod("svychisq", design) 2019-01-27 07:10:50 F = 144.97, ndf = 1, ddf = 79, p-value < 2.2e-16 2019-01-27 07:10:50 2019-01-27 07:10:50 2019-01-27 07:10:50 > glm_result <- svyglm(v6033 ~ nmorpob6 + sexo, censo_design) 2019-01-27 07:11:09 QQ: 'SELECT 1' 2019-01-27 07:12:25 II: Finished in 1.27s 2019-01-27 07:12:25 QQ: 'select v6033, v6531, v0601 from c10' 2019-01-27 07:12:26 II: Finished in 0.25s 2019-01-27 07:36:55 2019-01-27 07:36:55 > summary(glm_result) 2019-01-27 07:37:00 2019-01-27 07:37:00 Call: 2019-01-27 07:37:00 NextMethod(formula = "svyglm", design) 2019-01-27 07:37:00 2019-01-27 07:37:00 Survey design: 2019-01-27 07:37:00 survey::svrepdesign(weight = as.formula(paste0("~", unique_designs[i, 2019-01-27 07:37:00 "type"], "_wgt")), repweights = bootw$repweights, type = "bootstrap", 2019-01-27 07:37:00 combined.weights = FALSE, scale = bootw$scale, rscales = bootw$rscales, 2019-01-27 07:37:00 data = paste0("c", substr(unique_designs[i, "year"], 3, 4), 2019-01-27 07:37:00 ifelse(unique_designs[i, "type"] == "pes", "", paste0("_", 2019-01-27 07:37:00 unique_designs[i, "type"]))), dbtype = "MonetDBLite", 2019-01-27 07:37:00 dbname = unique_designs[i, "dbfolder"]) 2019-01-27 07:37:00 2019-01-27 07:37:00 Coefficients: 2019-01-27 07:37:00 Estimate Std. Error t value Pr(>|t|) 2019-01-27 07:37:00 (Intercept) 44.06560 0.04797 918.699 < 2e-16 *** 2019-01-27 07:37:00 nmorpob6 0.57361 0.05764 9.952 1.78e-15 *** 2019-01-27 07:37:00 sexofeminino 0.51847 0.05392 9.615 7.86e-15 *** 2019-01-27 07:37:00 --- 2019-01-27 07:37:00 Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 2019-01-27 07:37:00 2019-01-27 07:37:00 (Dispersion parameter for gaussian family taken to be 230099349638) 2019-01-27 07:37:00 2019-01-27 07:37:00 Number of Fisher Scoring iterations: 2 2019-01-27 07:37:00 2019-01-27 07:37:00 2019-01-27 07:37:00 > library(convey) 2019-01-27 07:37:04 2019-01-27 07:37:04 > censo_design <- convey_prep(censo_design) 2019-01-27 07:37:04 2019-01-27 07:37:04 > sub_censo_design <- subset(censo_design, v6531 >= 2019-01-27 07:37:04 + 0) 2019-01-27 07:37:04 QQ: 'SELECT 1' 2019-01-27 07:37:04 II: Finished in 0s 2019-01-27 07:37:04 QQ: 'select v6531 from c10' 2019-01-27 07:37:04 II: Finished in 0.11s 2019-01-27 07:40:31 2019-01-27 07:40:31 > svygini(~v6531, sub_censo_design, na.rm = TRUE) 2019-01-27 07:40:31 QQ: 'SELECT 1' 2019-01-27 07:40:38 II: Finished in 7.07s 2019-01-27 07:40:39 QQ: 'select v6531 from c10' 2019-01-27 07:40:39 II: Finished in 0.11s 2019-01-27 07:40:39 QQ: 'SELECT 1' 2019-01-27 07:40:39 II: Finished in 0s 2019-01-27 07:40:39 QQ: 'select v6531 from c10' 2019-01-27 07:40:39 II: Finished in 0.06s 2019-01-27 07:50:17 gini SE 2019-01-27 07:50:17 v6531 0.61061 6e-04 2019-01-27 07:50:17 2019-01-27 07:50:17 > close(censo_design, shutdown = TRUE) 2019-01-27 07:50:30 > test return code=0