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### This file is part of the 'foreign' package for R.
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# A copy of the GNU General Public License is available at
# http://www.r-project.org/Licenses/
read.dta <- function(file, convert.dates = TRUE,
convert.factors = TRUE, missing.type = FALSE,
convert.underscore = FALSE, warn.missing.labels = TRUE)
{
if(length(grep("^(http|ftp|https)://", file))) {
tmp <- tempfile()
download.file(file, tmp, quiet = TRUE, mode = "wb")
file <- tmp
on.exit(unlink(file))
}
rval <- .External(do_readStata, file)
if(convert.underscore)
names(rval) <- gsub("_", ".", names(rval))
types <- attr(rval, "types")
stata.na <- data.frame(type = 251L:255L,
min = c(101, 32741, 2147483621, 2^127, 2^1023),
inc = c(1,1,1,2^115,2^1011)
)
if(!missing.type) {
if (abs(attr(rval, "version")) >= 8L) {
for(v in which(types > 250L)) {
this.type <- types[v] - 250L
rval[[v]][rval[[v]] >= stata.na$min[this.type]] <- NA
}
}
} else {
if (abs(attr(rval, "version")) >= 8L) {
missings <- vector("list", length(rval))
names(missings) <- names(rval)
for(v in which(types > 250L)) {
this.type <- types[v] - 250L
nas <- is.na(rval[[v]]) | rval[[v]] >= stata.na$min[this.type]
natype <- (rval[[v]][nas] - stata.na$min[this.type])/stata.na$inc[this.type]
natype[is.na(natype)] <- 0L
missings[[v]] <- rep(NA, NROW(rval))
missings[[v]][nas] <- natype
rval[[v]][nas] <- NA
}
attr(rval,"missing") <- missings
} else
warning("'missing.type' only applicable to version >= 8 files")
}
convert_dt_c <- function(x)
as.POSIXct((x+0.1)/1000, origin = "1960-01-01") # avoid rounding down
convert_dt_C <- function(x) {
ls <- .leap.seconds + seq_along(.leap.seconds)
z <- (x+0.1)/1000 # avoid rounding down
z <- z - rowSums(outer(z, ls, ">="))
as.POSIXct(z, origin = "1960-01-01")
}
if (convert.dates) {
ff <- attr(rval, "formats")
## dates <- grep("%-*d", ff)
## Stata 12 introduced 'business dates'
## 'Formats beginning with %t or %-t are Stata's date and time formats.'
## but it seems some are earlier.
## The dta_115 description suggests this is too inclusive:
## 'Stata has an old *%d* format notation and some datasets
## still have them. Format *%d*... is equivalent to modern
## format *%td*... and *%-d*... is equivalent to *%-td*...'
dates <- if (attr(rval, "version") >= 8L) grep('^%(-|)(d|td)', ff)
else grep("%-*d", ff)
## avoid as.Date in case strptime is messed up
base <- structure(-3653L, class = "Date") # Stata dates are integer vars
for(v in dates) rval[[v]] <- structure(base + rval[[v]], class = "Date")
for(v in grep("%tc", ff)) rval[[v]] <- convert_dt_c(rval[[v]])
for(v in grep("%tC", ff)) rval[[v]] <- convert_dt_C(rval[[v]])
}
if (convert.factors %in% c(TRUE, NA)) {
if (attr(rval, "version") == 5L)
warning("cannot read factor labels from Stata 5 files")
else {
ll <- attr(rval, "val.labels")
tt <- attr(rval, "label.table")
factors <- which(ll != "")
for(v in factors) {
labels <- tt[[ll[v]]]
if (warn.missing.labels && is.null(labels)) {
warning(gettextf("value labels (%s) for %s are missing",
sQuote(ll[v]), sQuote(names(rval)[v])),
domain = NA)
next
}
if(!is.na(convert.factors)) {
## some levels don't have labels, so skip
if (!all(rval[[v]] %in% c(NA, NaN, tt[[ll[v]]])))
next
}
rval[[v]] <- factor(rval[[v]], levels=tt[[ll[v]]],
labels=names(tt[[ll[v]]]))
}
}
}
att <- attributes(rval)
##rval <- as.data.frame(rval, stringsAsFactors=FALSE)
class(rval) <- "data.frame"
newatt <- attributes(rval)
newatt <- c(newatt, att[!(names(att) %in% names(newatt))])
attributes(rval) <- newatt
rval
}
write.dta <-
function(dataframe, file, version = 7L,
convert.dates = TRUE, tz = "GMT",
convert.factors = c("labels","string","numeric","codes"))
{
if(!is.data.frame(dataframe))
stop("The object \"dataframe\" must have class data.frame")
if (version < 6L) stop("Version must be 6-12")
if (version == 9L) version <- 8L
if (version == 11L) version <- 10L
if (version == 12L) version <- 10L
if (version > 12L) {
warning("Version must be 6-12: using 7")
version <- 7L
}
## assume this is in chars: probably only works for ASCII
## But Stata formats are ASCII only
namelength <- if (version == 6L) 8L else 31L
oldn <- names(dataframe)
nn <- abbreviate(oldn, namelength)
if (any(nchar(nn) > namelength))
stop("cannot uniquely abbreviate variable names")
if (any(nchar(oldn) > namelength))
warning("abbreviating variable names")
names(dataframe) <- nn
attr(dataframe,"orig.names") <- oldn
if (convert.dates) {
dates <- which(sapply(dataframe,
function(x) inherits(x, "Date")))
for(v in dates)
dataframe[[v]] <- as.vector(julian(dataframe[[v]],
as.Date("1960-1-1", tz="GMT")))
dates <- which(sapply(dataframe,
function(x) inherits(x, "POSIXt")))
for(v in dates)
dataframe[[v]] <- as.vector(round(julian(dataframe[[v]],
ISOdate(1960,1,1, tz=tz))))
## It would be possible to write these as %tc format,
## milliseconds since 01jan1960 00:00:00.000
## dataframe[[v]] <- 1000*as.vector(as.POSIXct(dataframe[[v]], tz=tz) + 315619200)
}
convert.factors <- match.arg(convert.factors)
factors <- which(sapply(dataframe,is.factor))
if(convert.factors == "string") {
for(v in factors)
dataframe[[v]] <- I(as.character(dataframe[[v]]))
} else if (convert.factors == "numeric") {
for(v in factors)
dataframe[[v]] <- as.numeric(as.character(dataframe[[v]]))
} else if (convert.factors == "codes") {
for (v in factors)
dataframe[[v]] <- as.numeric(dataframe[[v]])
}
shortlevels <- function(f) {
ll <- levels(f)
if (is.null(ll)) return(NULL)
## avoid warning if non-ASCII strings are used (unwisely)
if (all(nchar(ll, "bytes") <= 80L)) ll else abbreviate(ll, 80L)
}
leveltable <- lapply(dataframe, shortlevels)
if (any(sapply(dataframe, function(x) {
d <- dim(x)
!is.null(d) && d[1L] < length(x)
})))
stop("cannot handle multicolumn columns")
invisible(.External(do_writeStata, file, dataframe, version, leveltable))
}
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