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R Under development (unstable) (2026-01-18 r89306) -- "Unsuffered Consequences"Copyright (C) 2026 The R Foundation for Statistical ComputingPlatform: x86_64-pc-linux-gnuR is free software and comes with ABSOLUTELY NO WARRANTY.You are welcome to redistribute it under certain conditions.Type 'license()' or 'licence()' for distribution details.R is a collaborative project with many contributors.Type 'contributors()' for more information and'citation()' on how to cite R or R packages in publications.Type 'demo()' for some demos, 'help()' for on-line help, or'help.start()' for an HTML browser interface to help.Type 'q()' to quit R.> library(foreign)> pc5 <- read.dta("pc5.dta")Warning message:In read.dta("pc5.dta") : cannot read factor labels from Stata 5 files> summary(pc5)age alb alkphos ascitesMin. :26.28 Min. :1.960 Min. : -9 Min. :-9.0001st Qu.:42.71 1st Qu.:3.330 1st Qu.: 423 1st Qu.: 0.000Median :50.47 Median :3.570 Median : 1009 Median : 0.000Mean :50.45 Mean :3.543 Mean : 1525 Mean :-2.0743rd Qu.:56.99 3rd Qu.:3.820 3rd Qu.: 1677 3rd Qu.: 0.000Max. :78.44 Max. :4.640 Max. :13862 Max. : 1.000bili chol edema edemarxMin. : 0.300 Min. : -9.0 Min. :0.00000 Min. :0.000001st Qu.: 0.700 1st Qu.: -9.0 1st Qu.:0.00000 1st Qu.:0.00000Median : 1.200 Median : 256.0 Median :0.00000 Median :0.00000Mean : 2.688 Mean : 245.8 Mean :0.09256 Mean :0.078153rd Qu.: 3.000 3rd Qu.: 346.0 3rd Qu.:0.00000 3rd Qu.:0.00000Max. :28.000 Max. :1775.0 Max. :1.00000 Max. :1.00000hepmeg time plate protime sexMin. :-9.00 Min. : 41 Min. : -9 Min. : 9.00 Min. :-9.0001st Qu.: 0.00 1st Qu.:1434 1st Qu.:181 1st Qu.:10.00 1st Qu.: 0.000Median : 0.00 Median :1487 Median :249 Median :10.60 Median : 1.000Mean :-1.75 Mean :1760 Mean :252 Mean :10.67 Mean :-1.4343rd Qu.: 1.00 3rd Qu.:2153 3rd Qu.:321 3rd Qu.:11.00 3rd Qu.: 1.000Max. : 1.00 Max. :4795 Max. :721 Max. :18.00 Max. : 1.000sgot spiders stage censMin. : -9.00 Min. :-9.000 Min. :-9.0000 Min. :0.00001st Qu.: 44.20 1st Qu.: 0.000 1st Qu.: 1.0000 1st Qu.:0.0000Median : 88.35 Median : 0.000 Median : 3.0000 Median :0.0000Mean : 88.22 Mean :-1.914 Mean : 0.1351 Mean :0.24433rd Qu.:130.20 3rd Qu.: 0.000 3rd Qu.: 3.0000 3rd Qu.:0.0000Max. :457.25 Max. : 1.000 Max. : 4.0000 Max. :1.0000rx trig copper idMin. :-9.0000 Min. : -9.00 Min. : -9.00 Min. : 1.01st Qu.: 1.0000 1st Qu.: -9.00 1st Qu.: 10.00 1st Qu.: 99.5Median : 1.0000 Median : 85.00 Median : 48.00 Median :195.0Mean :-0.9788 Mean : 81.44 Mean : 65.26 Mean :199.63rd Qu.: 2.0000 3rd Qu.:126.00 3rd Qu.: 88.00 3rd Qu.:302.5Max. : 2.0000 Max. :598.00 Max. :588.00 Max. :418.0first late t0Min. :0.0000 Min. :0.0000 Min. : 0.01st Qu.:0.0000 1st Qu.:0.0000 1st Qu.: 0.0Median :0.0000 Median :0.0000 Median : 0.0Mean :0.3657 Mean :0.3657 Mean : 543.83rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1487.0Max. :1.0000 Max. :1.0000 Max. :1487.0> str(pc5)'data.frame': 659 obs. of 24 variables:$ age : num 58.8 56.4 56.4 70.1 54.7 ...$ alb : num 2.6 4.14 4.14 3.48 2.54 ...$ alkphos: num 1718 7395 7395 516 6122 ...$ ascites: num 1 0 0 0 0 0 0 0 0 0 ...$ bili : num 14.5 1.1 1.1 1.4 1.8 ...$ chol : num 261 302 302 176 244 244 279 279 248 248 ...$ edema : num 1 0 0 1 1 1 0 0 0 0 ...$ edemarx: num 1 0 0 0.5 0.5 0.5 0 0 0 0 ...$ hepmeg : num 1 1 1 0 1 1 1 1 1 1 ...$ time : num 400 1487 4500 1012 1487 ...$ plate : num 190 221 221 151 183 183 136 136 -9 -9 ...$ protime: num 12.2 10.6 10.6 12 10.3 ...$ sex : num 1 1 1 0 1 1 1 1 1 1 ...$ sgot : num 137.9 113.5 113.5 96.1 60.6 ...$ spiders: num 1 1 1 0 1 1 1 1 0 0 ...$ stage : num 4 3 3 4 4 4 3 3 3 3 ...$ cens : num 1 0 0 1 0 1 0 0 0 1 ...$ rx : num 1 1 1 1 1 1 2 2 2 2 ...$ trig : num 172 88 88 55 92 92 72 72 63 63 ...$ copper : num 156 54 54 210 64 64 143 143 50 50 ...$ id : num 1 2 2 3 4 4 5 5 6 6 ...$ first : num 0 1 0 0 1 0 1 0 1 0 ...$ late : num 0 0 1 0 0 1 0 1 0 1 ...$ t0 : num 0 0 1487 0 0 ...- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "14 Feb 1997 14:22"- attr(*, "formats")= chr [1:24] "%9.0g" "%9.0g" "%9.0g" "%9.0g" ...- attr(*, "types")= int [1:24] 102 102 102 102 102 102 102 102 102 102 ...- attr(*, "val.labels")= chr [1:24] "" "" "" "" ...- attr(*, "var.labels")= chr [1:24] "" "" "" "" ...- attr(*, "version")= int 5> compressed <- read.dta("compressed.dta")> summary(compressed)age alb alkphos ascitesMin. :26.28 Min. :1.960 Min. : -9 Min. :-9.0001st Qu.:42.71 1st Qu.:3.330 1st Qu.: 423 1st Qu.: 0.000Median :50.47 Median :3.570 Median : 1009 Median : 0.000Mean :50.45 Mean :3.543 Mean : 1525 Mean :-2.0743rd Qu.:56.99 3rd Qu.:3.820 3rd Qu.: 1677 3rd Qu.: 0.000Max. :78.44 Max. :4.640 Max. :13862 Max. : 1.000bili chol edema edemarxMin. : 0.300 Min. : -9.0 Min. :0.00000 Min. :0.000001st Qu.: 0.700 1st Qu.: -9.0 1st Qu.:0.00000 1st Qu.:0.00000Median : 1.200 Median : 256.0 Median :0.00000 Median :0.00000Mean : 2.688 Mean : 245.8 Mean :0.09256 Mean :0.078153rd Qu.: 3.000 3rd Qu.: 346.0 3rd Qu.:0.00000 3rd Qu.:0.00000Max. :28.000 Max. :1775.0 Max. :1.00000 Max. :1.00000hepmeg time plate protime sexMin. :-9.00 Min. : 41 Min. : -9 Min. : 9.00 Min. :-9.0001st Qu.: 0.00 1st Qu.:1434 1st Qu.:181 1st Qu.:10.00 1st Qu.: 0.000Median : 0.00 Median :1487 Median :249 Median :10.60 Median : 1.000Mean :-1.75 Mean :1760 Mean :252 Mean :10.67 Mean :-1.4343rd Qu.: 1.00 3rd Qu.:2153 3rd Qu.:321 3rd Qu.:11.00 3rd Qu.: 1.000Max. : 1.00 Max. :4795 Max. :721 Max. :18.00 Max. : 1.000sgot spiders stage censMin. : -9.00 Min. :-9.000 Min. :-9.0000 Min. :0.00001st Qu.: 44.20 1st Qu.: 0.000 1st Qu.: 1.0000 1st Qu.:0.0000Median : 88.35 Median : 0.000 Median : 3.0000 Median :0.0000Mean : 88.22 Mean :-1.914 Mean : 0.1351 Mean :0.24433rd Qu.:130.20 3rd Qu.: 0.000 3rd Qu.: 3.0000 3rd Qu.:0.0000Max. :457.25 Max. : 1.000 Max. : 4.0000 Max. :1.0000rx trig copper idMin. :-9.0000 Min. : -9.00 Min. : -9.00 Min. : 1.01st Qu.: 1.0000 1st Qu.: -9.00 1st Qu.: 10.00 1st Qu.: 99.5Median : 1.0000 Median : 85.00 Median : 48.00 Median :195.0Mean :-0.9788 Mean : 81.44 Mean : 65.26 Mean :199.63rd Qu.: 2.0000 3rd Qu.:126.00 3rd Qu.: 88.00 3rd Qu.:302.5Max. : 2.0000 Max. :598.00 Max. :588.00 Max. :418.0first late t0Min. :0.0000 Min. :0.0000 Min. : 0.01st Qu.:0.0000 1st Qu.:0.0000 1st Qu.: 0.0Median :0.0000 Median :0.0000 Median : 0.0Mean :0.3657 Mean :0.3657 Mean : 543.83rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1487.0Max. :1.0000 Max. :1.0000 Max. :1487.0> all.equal(summary(pc5), summary(compressed))[1] TRUE> sun6 <- read.dta("sun6.dta")> summary(sun6)age alb alkphos ascitesMin. :26.28 Min. :1.960 Min. : -9 Min. :-9.0001st Qu.:42.71 1st Qu.:3.330 1st Qu.: 423 1st Qu.: 0.000Median :50.47 Median :3.570 Median : 1009 Median : 0.000Mean :50.45 Mean :3.543 Mean : 1525 Mean :-2.0743rd Qu.:56.99 3rd Qu.:3.820 3rd Qu.: 1677 3rd Qu.: 0.000Max. :78.44 Max. :4.640 Max. :13862 Max. : 1.000bili chol edema edemarxMin. : 0.300 Min. : -9.0 Min. :0.00000 Min. :0.000001st Qu.: 0.700 1st Qu.: -9.0 1st Qu.:0.00000 1st Qu.:0.00000Median : 1.200 Median : 256.0 Median :0.00000 Median :0.00000Mean : 2.688 Mean : 245.8 Mean :0.09256 Mean :0.078153rd Qu.: 3.000 3rd Qu.: 346.0 3rd Qu.:0.00000 3rd Qu.:0.00000Max. :28.000 Max. :1775.0 Max. :1.00000 Max. :1.00000hepmeg time plate protime sexMin. :-9.00 Min. : 41 Min. : -9 Min. : 9.00 Min. :-9.0001st Qu.: 0.00 1st Qu.:1434 1st Qu.:181 1st Qu.:10.00 1st Qu.: 0.000Median : 0.00 Median :1487 Median :249 Median :10.60 Median : 1.000Mean :-1.75 Mean :1760 Mean :252 Mean :10.67 Mean :-1.4343rd Qu.: 1.00 3rd Qu.:2153 3rd Qu.:321 3rd Qu.:11.00 3rd Qu.: 1.000Max. : 1.00 Max. :4795 Max. :721 Max. :18.00 Max. : 1.000sgot spiders stage censMin. : -9.00 Min. :-9.000 Min. :-9.0000 Min. :0.00001st Qu.: 44.20 1st Qu.: 0.000 1st Qu.: 1.0000 1st Qu.:0.0000Median : 88.35 Median : 0.000 Median : 3.0000 Median :0.0000Mean : 88.22 Mean :-1.914 Mean : 0.1351 Mean :0.24433rd Qu.:130.20 3rd Qu.: 0.000 3rd Qu.: 3.0000 3rd Qu.:0.0000Max. :457.25 Max. : 1.000 Max. : 4.0000 Max. :1.0000rx trig copper idMin. :-9.0000 Min. : -9.00 Min. : -9.00 Min. : 1.01st Qu.: 1.0000 1st Qu.: -9.00 1st Qu.: 10.00 1st Qu.: 99.5Median : 1.0000 Median : 85.00 Median : 48.00 Median :195.0Mean :-0.9788 Mean : 81.44 Mean : 65.26 Mean :199.63rd Qu.: 2.0000 3rd Qu.:126.00 3rd Qu.: 88.00 3rd Qu.:302.5Max. : 2.0000 Max. :598.00 Max. :588.00 Max. :418.0first late t0Min. :0.0000 Min. :0.0000 Min. : 0.01st Qu.:0.0000 1st Qu.:0.0000 1st Qu.: 0.0Median :0.0000 Median :0.0000 Median : 0.0Mean :0.3657 Mean :0.3657 Mean : 543.83rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:1487.0Max. :1.0000 Max. :1.0000 Max. :1487.0> str(sun6)'data.frame': 659 obs. of 24 variables:$ age : num 58.8 56.4 56.4 70.1 54.7 ...$ alb : num 2.6 4.14 4.14 3.48 2.54 ...$ alkphos: num 1718 7395 7395 516 6122 ...$ ascites: int 1 0 0 0 0 0 0 0 0 0 ...$ bili : num 14.5 1.1 1.1 1.4 1.8 ...$ chol : int 261 302 302 176 244 244 279 279 248 248 ...$ edema : int 1 0 0 1 1 1 0 0 0 0 ...$ edemarx: num 1 0 0 0.5 0.5 0.5 0 0 0 0 ...$ hepmeg : int 1 1 1 0 1 1 1 1 1 1 ...$ time : int 400 1487 4500 1012 1487 1925 1487 1504 1487 2503 ...$ plate : int 190 221 221 151 183 183 136 136 -9 -9 ...$ protime: num 12.2 10.6 10.6 12 10.3 ...$ sex : int 1 1 1 0 1 1 1 1 1 1 ...$ sgot : num 137.9 113.5 113.5 96.1 60.6 ...$ spiders: int 1 1 1 0 1 1 1 1 0 0 ...$ stage : int 4 3 3 4 4 4 3 3 3 3 ...$ cens : int 1 0 0 1 0 1 0 0 0 1 ...$ rx : int 1 1 1 1 1 1 2 2 2 2 ...$ trig : int 172 88 88 55 92 92 72 72 63 63 ...$ copper : int 156 54 54 210 64 64 143 143 50 50 ...$ id : int 1 2 2 3 4 4 5 5 6 6 ...$ first : int 0 1 0 0 1 0 1 0 1 0 ...$ late : int 0 0 1 0 0 1 0 1 0 1 ...$ t0 : int 0 0 1487 0 0 1487 0 1487 0 1487 ...- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "14 Sep 2000 10:40"- attr(*, "formats")= chr [1:24] "%9.0g" "%9.0g" "%9.0g" "%9.0g" ...- attr(*, "types")= int [1:24] 102 102 102 98 102 105 98 102 98 105 ...- attr(*, "val.labels")= chr [1:24] "" "" "" "" ...- attr(*, "var.labels")= chr [1:24] "" "" "" "" ...- attr(*, "version")= int 6> all.equal(summary(sun6),summary(pc5))[1] TRUE> df <- read.dta("datefactor.dta")> sdf <- summary(df)> if (getRversion() < "4.6.0") # "backport" NA's -> NAs to match reference output+ sdf <- sub("NA's", "NAs ", sdf, fixed = TRUE)> sdfhlth159 id adateEXCELLENT: 0 Min. : 1.00 Min. :1960-01-02VERY GOOD: 6 1st Qu.: 8.25 1st Qu.:1960-01-09GOOD : 8 Median :15.50 Median :1960-01-16FAIR : 4 Mean :15.50 Mean :1960-01-16POOR : 1 3rd Qu.:22.75 3rd Qu.:1960-01-23NAs :11 Max. :30.00 Max. :1960-01-31> data(esoph)> write.dta(esoph,esophile <- tempfile())> esoph2 <- read.dta(esophile)> all.equal(ordered(esoph2$alcgp),esoph$alcgp)[1] TRUE> write.dta(esoph,esophile,convert.factors="string")> esoph2 <- read.dta(esophile)> all.equal(as.character(esoph$alcgp),esoph2$alcgp)[1] TRUE> write.dta(esoph,esophile,convert.factors="code")> esoph2 <- read.dta(esophile)> all.equal(as.numeric(esoph$alcgp),as.numeric(esoph2$alcgp))[1] TRUE>> se <- read.dta("stata7se.dta")> print(se)race number1 white 22 asian 53 hispanic 54 white 45 black 56 white 67 black 7> v8 <- read.dta("stata8mac.dta")> print(v8)race number1 white 22 asian 53 hispanic 54 white 45 black 56 white 67 black 7>> stata8 <- read.dta("auto8.dta",missing.type=TRUE,convert.underscore=FALSE)> str(stata8)'data.frame': 74 obs. of 13 variables:$ make : chr "AMC Concord" "AMC Pacer" "AMC Spirit" "Buick Century" ...$ price : int 4099 4749 3799 4816 7827 5788 4453 5189 10372 4082 ...$ mpg : int 22 17 22 20 15 18 26 20 16 19 ...$ rep78 : int 3 3 NA 3 4 3 NA 3 3 3 ...$ headroom : num 2.5 3 3 4.5 4 4 3 2 3.5 3.5 ...$ trunk : int 11 11 12 16 20 21 10 16 17 13 ...$ weight : int 2930 3350 2640 3250 4080 3670 2230 3280 3880 3400 ...$ length : int 186 173 168 196 222 218 170 200 207 200 ...$ turn : int 40 40 35 40 43 43 34 42 43 42 ...$ displacement: int 121 258 121 196 350 231 304 196 231 231 ...$ gear_ratio : num 3.58 2.53 3.08 2.93 2.41 ...$ foreign : Factor w/ 2 levels "Domestic","Foreign": 1 1 1 1 1 1 1 1 1 1 ...$ testmiss : num NA NA NA NA NA NA NA NA NA NA ...- attr(*, "datalabel")= chr "1978 Automobile Data"- attr(*, "time.stamp")= chr "20 May 2003 14:39"- attr(*, "formats")= chr [1:13] "%-18s" "%8.0gc" "%8.0g" "%8.0g" ...- attr(*, "types")= int [1:13] 18 252 252 252 254 252 252 252 252 252 ...- attr(*, "val.labels")= chr [1:13] "" "" "" "" ...- attr(*, "var.labels")= chr [1:13] "Make and Model" "Price" "Mileage (mpg)" "Repair Record 1978" ...- attr(*, "version")= int 8- attr(*, "label.table")=List of 1..$ origin: Named int [1:2] 0 1.. ..- attr(*, "names")= chr [1:2] "Domestic" "Foreign"- attr(*, "missing")=List of 13..$ make : NULL..$ price : num [1:74] NA NA NA NA NA NA NA NA NA NA .....$ mpg : num [1:74] NA NA NA NA NA NA NA NA NA NA .....$ rep78 : num [1:74] NA NA 0 NA NA NA 0 NA NA NA .....$ headroom : num [1:74] NA NA NA NA NA NA NA NA NA NA .....$ trunk : num [1:74] NA NA NA NA NA NA NA NA NA NA .....$ weight : num [1:74] NA NA NA NA NA NA NA NA NA NA .....$ length : num [1:74] NA NA NA NA NA NA NA NA NA NA .....$ turn : num [1:74] NA NA NA NA NA NA NA NA NA NA .....$ displacement: num [1:74] NA NA NA NA NA NA NA NA NA NA .....$ gear_ratio : num [1:74] NA NA NA NA NA NA NA NA NA NA .....$ foreign : num [1:74] NA NA NA NA NA NA NA NA NA NA .....$ testmiss : num [1:74] 18 18 18 18 18 18 18 18 18 18 ...>> bq <- read.dta("MLLabelsWithNotesChar.dta")> str(bq)'data.frame': 0 obs. of 1 variable:$ female: Factor w/ 2 levels "No","Yes":- attr(*, "datalabel")= chr "datalabelBQ"- attr(*, "time.stamp")= chr "27 Apr 2013 16:16"- attr(*, "formats")= chr "%8.0g"- attr(*, "types")= int 251- attr(*, "val.labels")= chr "female_lbl_def"- attr(*, "var.labels")= chr "Is it female"- attr(*, "expansion.fields")=List of 11..$ : chr [1:3] "female" "question" "Are you Female?"..$ : chr [1:3] "_dta" "_lang_c" "default"..$ : chr [1:3] "_dta" "_lang_v_spanish" "etiqdataBQ"..$ : chr [1:3] "female" "_lang_l_spanish" "female_lbl_es"..$ : chr [1:3] "female" "_lang_v_spanish" "Femenino"..$ : chr [1:3] "_dta" "note1" "datasetNoteTxt"..$ : chr [1:3] "_dta" "note0" "1"..$ : chr [1:3] "female" "note2" "FemaleNote2Txt"..$ : chr [1:3] "female" "note0" "2"..$ : chr [1:3] "female" "note1" "FemaleNoteTxt"..$ : chr [1:3] "_dta" "_lang_list" "default spanish"- attr(*, "version")= int 12- attr(*, "label.table")=List of 2..$ female_lbl_es : Named int [1:2] 0 1.. ..- attr(*, "names")= chr [1:2] "No" "Si"..$ female_lbl_def: Named int [1:2] 0 1.. ..- attr(*, "names")= chr [1:2] "No" "Yes"> write.dta(bq, "bq.dta", version = 12)> str(read.dta('bq.dta'))'data.frame': 0 obs. of 1 variable:$ female: Factor w/ 2 levels "No","Yes":- attr(*, "datalabel")= chr "datalabelBQ"- attr(*, "time.stamp")= chr ""- attr(*, "formats")= chr "%9.0g"- attr(*, "types")= int 253- attr(*, "val.labels")= chr "female_lbl_def"- attr(*, "var.labels")= chr "Is it female"- attr(*, "expansion.fields")=List of 11..$ : chr [1:3] "female" "question" "Are you Female?"..$ : chr [1:3] "_dta" "_lang_c" "default"..$ : chr [1:3] "_dta" "_lang_v_spanish" "etiqdataBQ"..$ : chr [1:3] "female" "_lang_l_spanish" "female_lbl_es"..$ : chr [1:3] "female" "_lang_v_spanish" "Femenino"..$ : chr [1:3] "_dta" "note1" "datasetNoteTxt"..$ : chr [1:3] "_dta" "note0" "1"..$ : chr [1:3] "female" "note2" "FemaleNote2Txt"..$ : chr [1:3] "female" "note0" "2"..$ : chr [1:3] "female" "note1" "FemaleNoteTxt"..$ : chr [1:3] "_dta" "_lang_list" "default spanish"- attr(*, "version")= int 12- attr(*, "label.table")=List of 2..$ female_lbl_def: Named int [1:2] 1 2.. ..- attr(*, "names")= chr [1:2] "No" "Yes"..$ female_lbl_es : Named int [1:2] 0 1.. ..- attr(*, "names")= chr [1:2] "No" "Si"> unlink("bq.dta")>> ## PR#15290> bq <- read.dta("OneVarTwoValLabels.dta")> str(bq)'data.frame': 0 obs. of 1 variable:$ female: Factor w/ 2 levels "Male","Female":- attr(*, "datalabel")= chr ""- attr(*, "time.stamp")= chr "25 Apr 2013 21:40"- attr(*, "formats")= chr "%9.0g"- attr(*, "types")= int 251- attr(*, "val.labels")= chr "fem_lbl_val_en"- attr(*, "var.labels")= chr ""- attr(*, "expansion.fields")=List of 3..$ : chr [1:3] "_dta" "_lang_c" "default"..$ : chr [1:3] "female" "_lang_l_spanish" "fem_lbl_val_es"..$ : chr [1:3] "_dta" "_lang_list" "default spanish"- attr(*, "version")= int 12- attr(*, "label.table")=List of 2..$ fem_lbl_val_es: Named int [1:2] 0 1.. ..- attr(*, "names")= chr [1:2] "Masculino" "Femenino"..$ fem_lbl_val_en: Named int [1:2] 0 1.. ..- attr(*, "names")= chr [1:2] "Male" "Female">> ## Dates and date-times in Stata12> Sys.setenv(TZ = "UTC") # avoid timezone differences: cannot unset so must be last> read.dta("xxx12.dta")x xc xbigc xdate1 2014-01-23 20:07:16 2014-01-23 20:07:16 2014-01-23 20:07:16 2014-01-232 2014-01-23 20:07:17 2014-01-23 20:07:17 2014-01-23 20:07:17 2014-01-233 2014-01-23 20:07:18 2014-01-23 20:07:18 2014-01-23 20:07:18 2014-01-234 2014-01-23 20:07:19 2014-01-23 20:07:19 2014-01-23 20:07:19 2014-01-235 2014-01-23 20:07:20 2014-01-23 20:07:20 2014-01-23 20:07:20 2014-01-236 2014-01-23 20:07:21 2014-01-23 20:07:21 2014-01-23 20:07:21 2014-01-237 2014-01-23 20:07:22 2014-01-23 20:07:22 2014-01-23 20:07:22 2014-01-238 2014-01-23 20:07:23 2014-01-23 20:07:23 2014-01-23 20:07:23 2014-01-239 2014-01-23 20:07:24 2014-01-23 20:07:24 2014-01-23 20:07:24 2014-01-2310 2014-01-23 20:07:25 2014-01-23 20:07:25 2014-01-23 20:07:25 2014-01-23>> q()> proc.time()user system elapsed0.167 0.042 0.201