1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
|
spss.get <- function(file, lowernames=FALSE,
datevars=NULL,
use.value.labels=TRUE,
to.data.frame=TRUE,
max.value.labels=Inf,
force.single=TRUE, allow=NULL, charfactor=FALSE,
reencode=NA) {
w <- read.spss(file, use.value.labels=use.value.labels,
to.data.frame=to.data.frame,
max.value.labels=max.value.labels,
reencode=reencode)
a <- attributes(w)
vl <- a$variable.labels
nam <- a$names
nam <- makeNames(a$names, unique=TRUE, allow=allow)
if(lowernames) nam <- casefold(nam)
names(w) <- nam
lnam <- names(vl)
if(length(vl))
for(i in 1:length(vl)) {
n <- lnam[i]
lab <- vl[i]
if(lab != '' && lab != n) label(w[[i]]) <- lab
}
attr(w, 'variable.labels') <- NULL
if(force.single || length(datevars) || charfactor)
for(v in nam) {
x <- w[[v]]
changed <- FALSE
if(v %in% datevars) {
x <- importConvertDateTime(x, 'date', 'spss')
changed <- TRUE
} else if(all(is.na(x))) {
storage.mode(x) <- 'integer'
changed <- TRUE
} else if(!(is.factor(x) || is.character(x))) {
if(all(is.na(x))) {
storage.mode(x) <- 'integer'
changed <- TRUE
} else if(max(abs(x),na.rm=TRUE) <= (2^31-1) &&
all(floor(x) == x, na.rm=TRUE)) {
storage.mode(x) <- 'integer'
changed <- TRUE
}
} else if(charfactor && is.character(x)) {
if(length(unique(x)) < .5*length(x))
{
x <- sub(' +$', '', x) # remove trailing blanks
x <- factor(x, exclude='')
changed <- TRUE
}
}
if(changed) w[[v]] <- x
}
w
}
csv.get <- function(file, lowernames=FALSE, datevars=NULL, datetimevars=NULL,
dateformat='%F', fixdates=c('none','year'),
comment.char = "", autodate=TRUE, allow=NULL,
charfactor=FALSE,
sep=',', skip=0, vnames=NULL, labels=NULL, text=NULL, ...){
fixdates <- match.arg(fixdates)
if(length(text) && ! missing(file)) stop('may not specify both file and text')
scn <- function(skip)
if(length(text)) scan(text=text, what=character(0), skip=skip,
nlines=1, sep=sep, quiet=TRUE)
else
scan(file, what=character(0), skip=skip, nlines=1, sep=sep, quiet=TRUE)
rcsv <- function(...)
if(length(text)) read.csv(text=text, check.names=FALSE,
comment.char=comment.char, sep=sep, skip=skip, ...)
else
read.csv(file, check.names=FALSE, comment.char=comment.char,
sep=sep, skip=skip,, ...)
if(length(vnames)) vnames <- scn(skip=vnames - 1)
if(length(labels)) labels <- scn(skip=labels - 1)
w <- if(length(vnames))
rcsv(header=FALSE, col.names=vnames)
else
rcsv()
n <- nam <- names(w)
m <- makeNames(n, unique=TRUE, allow=allow)
if(length(labels)) n <- labels
if(lowernames)
m <- casefold(m)
changed <- any(m != nam)
if(changed)
names(w) <- m
cleanup.import(w,
labels=if(length(labels))labels else if(changed)n else NULL,
datevars=datevars, datetimevars=datetimevars,
dateformat=dateformat, autodate=autodate,
fixdates=fixdates, charfactor=charfactor)
}
stata.get <- function(file, lowernames=FALSE,
convert.dates=TRUE, convert.factors=TRUE,
missing.type=FALSE, convert.underscore=TRUE,
warn.missing.labels=TRUE, force.single=TRUE,
allow=NULL, charfactor=FALSE, ...) {
## depends on the read.dta function from foreign
## Function to convert the elements of w into more compact
## data storage types.
convertObjs <- function(x, charfactor, force.single) {
## Date is not nessarely a integer but it ignores any
## fraction it might have
if((inherits(x, 'Date') || is.factor(x))
&& storage.mode(x) != 'integer') {
storage.mode(x) <- 'integer'
} else if(charfactor && is.character(x)) {
## If x is a character and arg charfactor is TRUE then
## convert x to a factor if the number of unique values of x is less
## than half the total number of values in x
if(length(unique(x)) < length(x) / 2)
{
x <- sub(' +$', '', x) # remove trailing blanks
x <- factor(x, exclude='')
}
} else if(is.numeric(x)) {
if(all(is.na(x))) {
## if all values are NA then convert to integer because
## it is 4 bytes instead of 8
storage.mode(x) <- 'integer'
}
else if(force.single && max(abs(x), na.rm=TRUE) <= (2^31-1) &&
all(floor(x) == x, na.rm=TRUE)) {
## convert x to integer if arg force.single is TRUE and the maximum
## absolute value of x is less then maximum value that an integer
## can store.
storage.mode(x) <- 'integer'
}
}
return(x)
}
## A function to create additional attributes to add to the elements of
## w
create.attribs <- function(var.label, val.label, format, label.table) {
attribs <- list()
if(format != '') {
attribs$format <- format
}
## Translate var labels into Hmisc var lables
if(var.label != '') {
attribs$label <- var.label
}
## The label.table values are found by looking a the checking to see
## if there is a non-empty value in val.labels. That value corrasponds
## a named element in label.table.
## Check to see if val.label is not empty and it is one of the
## names in label.table and that its value is not NULL
if(val.label != '' && val.label %in% names(label.table) &&
!is.null(label.table[[val.label]])) {
attribs$value.label.table <- label.table[[val.label]]
}
return(attribs)
}
## Read the stata file into w
w <- read.dta(file, convert.dates=convert.dates,
convert.factors=convert.factors,
missing.type=missing.type,
convert.underscore=convert.underscore,
warn.missing.labels=warn.missing.labels, ...)
## extract attributes from w
a <- attributes(w)
num.vars <- length(w)
## Do translate attributes names into R names
nam <- makeNames(a$names, unique=TRUE, allow=allow)
if(lowernames) nam <- casefold(nam, upper=FALSE)
a$names <- nam
## If var.labels is empty then create a empty char vector.
if(!length(a$var.labels)) {
a$var.labels <- character(num.vars)
}
## If val.labels is empty then create an empty char vector.
if(length(a$val.labels)) {
val.labels <- a$val.labels
} else {
val.labels <- character(num.vars)
}
## create list of attributes for the elements in w. An mapply is faster
## then a for loop in large data sets.
attribs <- mapply(FUN=create.attribs, var.label=a$var.labels,
val.label=val.labels, format=a$formats,
MoreArgs=list(label.table=a$label.table),
SIMPLIFY=FALSE)
## clear var.labels attribute
attr(w, 'var.labels') <- NULL
## Convert the elements of w as needed
w <- lapply(w, FUN=convertObjs, force.single=force.single,
charfactor=charfactor)
## strip off the naming info for w
w <- unname(w)
## add the new attributes to the current attributes of
## the elements of w
for(i in seq(along.with=w)) {
## Set the label for the element
if('label' %in% names(attribs[[i]])) {
label(w[[i]]) <- attribs[[i]]$label
## clear the label value from attribs[[i]]
attribs[[i]]$label <- NULL
}
## combine the new attribs with the current attributes
consolidate(attributes(w[[i]])) <- attribs[[i]]
}
## add the names, rownames, class variables, and some extra stata
## info back to w
stata.info <- a[c('datalabel','version','time.stamp','val.labels','label.table')]
attributes(w) <- c(a[c('names','row.names','class')],
stata.info=list(stata.info))
return(w)
}
|
