Commit 88286f9aab7e66ea698b225c08fc133457d9c87e - gdata

Import Debian changes 2.12.0-1 gdata (2.12.0-1) unstable; urgency=low * New upstream release * debian/control: Set Build-Depends: to current R version Dirk Eddelbuettel 5 years ago

23 changed file(s) with 870 addition(s) and 599 deletion(s). Raw diff Collapse all Expand all

-1

.Rinstignore less more

0	0	doc/.*\.tex$
1	1	doc/.*\.sty$
2	2	doc/.*\.dtx$
3		doc/.*\.Rnw$⏎
	3	\.svn⏎

+70

-0

ChangeLog less more

	0	2012-09-12 17:29 warnes
	1
	2	* [r1604] .Rinstignore: Don't ignore .Rnw files, but do ignore .svn
	3	files.
	4
	5	2012-09-11 20:41 warnes
	6
	7	* [r1603] man/interleave.Rd: Clarify workding of DROP argument to
	8	interleave().
	9
	10	2012-09-11 20:37 warnes
	11
	12	* [r1602] man/interleave.Rd: Replace call to aggregate.table() with
	13	equivalent tapply() call since aggregate.table() is being
	14	depreciated.
	15
	16	2012-08-22 16:47 warnes
	17
	18	* [r1601] DESCRIPTION, inst/NEWS: Update DESCRIPTION and NEWS for
	19	gdate 2.11.1.
	20
	21	2012-08-22 16:42 warnes
	22
	23	* [r1600] man/read.xls.Rd: Add example for read.xls() that shows
	24	how to use the fileEncoding
	25	argument to read in latin-1 encoded data.
	26
	27	2012-08-22 16:41 warnes
	28
	29	* [r1599] tests/latin-1.xls, tests/test.read.xls.R,
	30	tests/test.read.xls.Rout.save: Add XLSX test for latin-1
	31	characters, and look for them in their new
	32	location in inst/xls/.
	33
	34	2012-08-22 16:35 warnes
	35
	36	* [r1598] inst/xls/latin-1.xls, inst/xls/latin-1.xlsx: add XLSX
	37	version of latin-1.xls
	38
	39	2012-08-22 15:48 warnes
	40
	41	* [r1597] tests/latin-1.xls, tests/test.read.xls.R,
	42	tests/test.read.xls.Rout.save: Add test file and code to ensure
	43	that read.xls() can properly handle
	44	files with alternative encodings. latin-1.xls contains each of
	45	the
	46	non-ascii latin-1 special characters in both the column headings
	47	and
	48	the body of the file.
	49
	50	2012-08-22 15:45 warnes
	51
	52	* [r1596] R/read.xls.R: Change code to have R read the csv/tab data
	53	from the file rather than
	54	from the connetion we made, so that file encodings can be
	55	properly handled.
	56
	57	2012-08-22 14:29 warnes
	58
	59	* [r1595] R/read.xls.R: Always close the connection.
	60
	61	2012-08-13 22:13 warnes
	62
	63	* [r1594] inst/perl/xls2csv.pl: Remove trailing space from output
	64	line.
	65
	66	2012-06-18 20:32 warnes
	67
	68	* [r1567] inst/NEWS: Update NEWS for 2.11.0 release.
	69
0	70	2012-06-18 20:27 warnes
1	71
2	72	* [r1566] DESCRIPTION: Bump version number and add

-4

DESCRIPTION less more

3	3	Depends: R (>= 2.13.0)
4	4	SystemRequirements: perl
5	5	Imports: gtools
6		Version: 2.11.0
7		Date: 2012-06-08
	6	Version: 2.12.0
	7	Date: 2012-10-12
8	8	Author: Gregory R. Warnes, with contributions from Ben Bolker, Gregor
9	9	Gorjanc, Gabor Grothendieck, Ales Korosec, Thomas Lumley, Don
10	10	MacQueen, Arni Magnusson, Jim Rogers, and others
11	11	Maintainer: Gregory Warnes <greg@warnes.net>
12	12	License: GPL-2
13		Packaged: 2012-06-18 20:32:37 UTC; warnegr1
	13	Packaged: 2012-09-12 17:41:01 UTC; warnegr1
14	14	Repository: CRAN
15		Date/Publication: 2012-06-20 05:38:45
	15	Date/Publication: 2012-09-12 18:32:34

+19

-17

MD5 less more

0		6d5f26662e2d560c1cb8157b4f2a698a *ChangeLog
1		97baeaefbec6b08b278ffd6a18f846d2 *DESCRIPTION
	0	483f69e6cdc20db9b61860670972684d *ChangeLog
	1	673939a0718c96893c11d3d64315c364 *DESCRIPTION
2	2	905fe9c5be6e143737163bc6317e6640 *INSTALL
3	3	632a2df95d6003a608b5579ca2f1a9dd *NAMESPACE
4		35031870a379dc6ee2e1b5d23c1489a6 *NEWS
	4	8397287f5ada0a978e40002ccdb2ba56 *NEWS
5	5	92e3ca5e31d594044b8325a441142c37 *R/Args.R
6	6	94976a0bed5195b50511e200d1711280 *R/ConvertMedUnits.R
7		734e0ca76e140f510bc30c597f2e1dc1 *R/aggregate.table.R
	7	0f26158c70aca9269f5304b440e5ab35 *R/aggregate.table.R
8	8	78e0c21cf9e4693553a4174d9d3b3c80 *R/bindData.R
9	9	df4bed53c71599dde15cbf23b4ca645a *R/case.R
10	10	ea9399bf2240d9c3a536da45bcf34cd2 *R/cbindX.R

28	28	2141528b10d1732e0683ba27fc97f581 *R/nobs.R
29	29	eca2d4b7165eb8ae97e0944284120cc9 *R/object.size.R
30	30	c3c6e74c9238d0b99b74c09cf76b154d *R/onAttach.R
31		f43e1a53025924fe95e25ad4cbd3933b *R/read.xls.R
	31	53d3ccd68f0b4b5d3e2c27d7bfaedc17 *R/read.xls.R
32	32	aaace07c7a900ddec695220ad10e0d14 *R/rename.vars.R
33	33	8dbe70d52ae3d60a07aa928fc3c62413 *R/reorder.R
34	34	cef4f8eb74136397feee111cf921676f *R/resample.R

45	45	151173ad3f3a2e7f065e494b474ae3d7 *R/xls2sep.R
46	46	aa1b782482928d032b1b0961d333c0f1 *R/xlsFormats.R
47	47	0df2e08650ae305a620ceb84ca798a63 *data/MedUnits.rda
48		6d5f26662e2d560c1cb8157b4f2a698a *inst/ChangeLog
49		35031870a379dc6ee2e1b5d23c1489a6 *inst/NEWS
	48	483f69e6cdc20db9b61860670972684d *inst/ChangeLog
	49	8397287f5ada0a978e40002ccdb2ba56 *inst/NEWS
50	50	ac512b1ebd4d71ac96b2a4d5288d53cb *inst/bin/xls2csv
51	51	ce0b4437c51faccb3595d986e8acae80 *inst/bin/xls2csv.bat
52	52	99af68b9933865da35d30b3f0d4606be *inst/doc/Rnews.dtx

54	54	e444b0ed03b42abe356a8ad70f055189 *inst/doc/gregmisc.pdf
55	55	f1dc90111b7898b5944c1f67abec00a2 *inst/doc/gregmisc.tex
56	56	afcc7e1ba12e2aab12a4349fc8470d08 *inst/doc/mapLevels.Rnw
57		3a15b00a1ce7a79b4eccd4575da32e66 *inst/doc/mapLevels.pdf
	57	4c6ef5f6392d7b16379427aebd117941 *inst/doc/mapLevels.pdf
58	58	a968a07310286934daaea108e3f915f4 *inst/doc/unknown.Rnw
59		8dc2f21043c89eaadf5376140b8c280e *inst/doc/unknown.pdf
	59	61a58e50ee3d6de9aa65406508f1ccaa *inst/doc/unknown.pdf
60	60	3622c5d29d09f1a179211f22acf6cdef *inst/perl/Archive/README-Archive-Zip
61	61	013677fabc8a49480cca5c10d67dd850 *inst/perl/Archive/Zip.pm
62	62	da56a4326657fda95d0de93c65ed4006 *inst/perl/Archive/Zip/Archive.pm

108	108	95fb12c6a78ec327de63e9a04f34775f *inst/perl/sheetCount.pl
109	109	95fb12c6a78ec327de63e9a04f34775f *inst/perl/sheetNames.pl
110	110	f55aa6f304604c5f1eb96351f0dd9b82 *inst/perl/supportedFormats.pl
111		cf0aef866f7646891b7bcbe661fb56bd *inst/perl/xls2csv.pl
112		cf0aef866f7646891b7bcbe661fb56bd *inst/perl/xls2tab.pl
113		cf0aef866f7646891b7bcbe661fb56bd *inst/perl/xls2tsv.pl
	111	84e6c5093222000137198cc67f8f1da8 *inst/perl/xls2csv.pl
	112	84e6c5093222000137198cc67f8f1da8 *inst/perl/xls2tab.pl
	113	84e6c5093222000137198cc67f8f1da8 *inst/perl/xls2tsv.pl
114	114	a616e808bd826e929f56223020649675 *inst/unitTests/Makefile
115	115	7b65e0f6b0ea277d2390df9b3f439fa0 *inst/unitTests/report.html
116	116	f5603c25cdff9c9cbc647efee4f2b2fd *inst/unitTests/report.txt

130	130	07387258cd5a208a2aae70441c2112e0 *inst/xls/ExampleExcelFile.xls
131	131	59f44d54c2c09ee757af7b6724dc9d63 *inst/xls/ExampleExcelFile.xlsx
132	132	7c16d3cfd37123f3c321c12a92b9269a *inst/xls/iris.xls
	133	8a0467a49bfb791295925cb6a372b1ff *inst/xls/latin-1.xls
	134	36e751188a4e3d37ce3be57d2152922a *inst/xls/latin-1.xlsx
133	135	24a1020fb457c398c620457ad114e245 *man/Args.Rd
134	136	64979ed4d4cf6136b74b38290bc04e76 *man/ConvertMedUnits.Rd
135	137	abfda9fcf25a1a9306348b22d73e3049 *man/MedUnits.Rd
136		6fd748ee6c6ffd6cb660f0a0ba4eac62 *man/aggregate.table.Rd
	138	8d8f92632f70e98c2063fd8ce368e5e7 *man/aggregate.table.Rd
137	139	140de526fc0a3c819dcd687e7bb3ed77 *man/bindData.Rd
138	140	a4c69a81cca648bfdc2f6913229b4e0e *man/case.Rd
139	141	640626fce10a1b97ad82fd594f18b058 *man/cbindX.Rd

147	149	38580f70b4b3af84ebfa4b952dd7021b *man/getDateTimePart.Rd
148	150	eb90a75f6e6d0171486d3a96626cf04b *man/humanReadable.Rd
149	151	6beab4e8b711110199599f8427d1d042 *man/installXLSXsupport.Rd
150		4d51ee507199034e28f4c73183387fa9 *man/interleave.Rd
	152	26bb8febce31195f8efcf071270913bc *man/interleave.Rd
151	153	0d70b8cd533a830a68103355b1054ec5 *man/is.what.Rd
152	154	8c50e81caf14aebb11d908fbcc9fe2de *man/keep.Rd
153	155	4bfbaf0835fff3cbc3ba8f17f9823bfb *man/ll.Rd

157	159	4789e9c9a034bc5665d93c80579729ef *man/nPairs.Rd
158	160	4e3ba1601ecb171596b609516d2e8911 *man/nobs.Rd
159	161	67467a836f6e35a897d6bee4d0a7808d *man/object.size.Rd
160		215a46ab86591b5d0605960bb74d8bf0 *man/read.xls.Rd
	162	e60eab08c9047f0ccfb78fa0d8c0b94b *man/read.xls.Rd
161	163	b73a198509b4fdcb4a24a85909309532 *man/rename.vars.Rd
162	164	dce038a56263e98621c3715f0aefecd3 *man/reorder.Rd
163	165	fc28b1b680997fd8ff2ab73478db4872 *man/resample.Rd

172	174	ad219282ec6913083b82073691923f9b *man/wideByFactor.Rd
173	175	56d52a59a9c4f5132d5ae69673823ae8 *man/write.fwf.Rd
174	176	8a9c1fe9d0316d0b98e6d353c2b7a6cf *man/xlsFormats.Rd
175		2d7645d15b62dc6a3615fbce5b41b2c7 *tests/test.read.xls.R
176		dd0df8f42b531719bf942ea1e633c155 *tests/test.read.xls.Rout.save
	177	019c9def35c544fde79f6fdfbcc4a066 *tests/test.read.xls.R
	178	1d037734847eb0062a9dcfe04fdba49b *tests/test.read.xls.Rout.save
177	179	dee3232474b92bcdf1ad75ca31080792 *tests/test.write.fwf.eol.R
178	180	b32b0eb85790d71ea6025ae5eca71fb1 *tests/tests.write.fwf.R
179	181	ee812493ba050211ca9960810a98dddd *tests/tests.write.fwf.Rout.save

+31

-0

NEWS less more

	0	Changes in 2.12.0 (2012-10-12)
	1	------------------------------
	2
	3	Other Changes:
	4
	5	- 'stats::aggregate' was made into a generic on 27-Jan-2010, so that
	6	attempting to call 'aggregate' on a 'table' object will now
	7	incorrectly call 'aggregate.table'. Since 'aggregate.table' can be
	8	replaced by a call to tapply using two index vectors, e.g.
	9	aggregate.table(x, by1=a, by2=b, mean)
	10	can be replaced by
	11	tapply(x, INDEX=list(a, b), FUN=mean),
	12	the 'aggregate.table' function will now display a warning that it
	13	is depreciated and recommending the equivalent call to tapply. It
	14	will be removed entirely in a future version of gdata.
	15
	16	Changes in 2.11.1 (2012-09-22)
	17	------------------------------
	18
	19	Enhancements:
	20
	21	- read.xls() now supports fileEncoding argument to allow non-ascii
	22	encoded data to be handled. See the manual page for an example.
	23
	24	Bug Fixes:
	25
	26	- The perl script utilized by read.xls() was incorrectly appending a
	27	space character at the end of each line, causing problems with
	28	character and NA entries in the final column.
	29
	30
0	31	Changes in 2.11.0 (2012-06-18)
1	32	------------------------------
2	33

+33

-11

R/aggregate.table.R less more

0		# $Id: aggregate.table.R 625 2005-06-09 14:20:30Z nj7w $
	0	# $Id: aggregate.table.R 1605 2012-09-12 17:39:42Z warnes $
1	1
2	2	aggregate.table <- function(x, by1, by2, FUN=mean, ... )
3	3	{
4		if(!is.factor(by1)) by1 <- as.factor(by1)
5		if(!is.factor(by2)) by2 <- as.factor(by2)
	4	warning("'aggregate.table' is depreciated.",
	5	"Please use 'tapply(X=",
	6	deparse(substitute(x)),
	7	", INDEX=list(",
	8	deparse(substitute(by1)),
	9	", ",
	10	deparse(substitute(by2)),
	11	"), FUN=",
	12	deparse(substitute(FUN)),
	13	if(length(list(...))>0)
	14	{
	15	l <- list(...)
	16	paste(", ",
	17	paste(names(l),"=",
	18	deparse(substitute(...)),
	19	sep="",
	20	collapse=", ")
	21	)
	22	},
	23	")' instead.")
	24	tapply(X=x, INDEX=list(by1, by2), FUN=FUN, ...)
	25	}
6	26
7		ag <- aggregate(x, by=list(by1,by2), FUN=FUN, ... )
8		tab <- matrix( nrow=nlevels(by1), ncol=nlevels(by2) )
9		dimnames(tab) <- list(levels(by1),levels(by2))
10
11		for(i in 1:nrow(ag))
12		tab[ as.character(ag[i,1]), as.character(ag[i,2]) ] <- ag[i,3]
13		tab
14		}
	27	## aggregate.table <- function(x, by1, by2, FUN=mean, ... )
	28	## {
	29	##
	30	## tab <- matrix( nrow=nlevels(by1), ncol=nlevels(by2) )
	31	## dimnames(tab) <- list(levels(by1),levels(by2))
	32	##
	33	## for(i in 1:nrow(ag))
	34	## tab[ as.character(ag[i,1]), as.character(ag[i,2]) ] <- ag[i,3]
	35	## tab
	36	## }

+13

-14

R/read.xls.R less more

0		## s$Id: read.xls.R 1541 2012-06-06 01:21:44Z warnes $
	0	## s$Id: read.xls.R 1596 2012-08-22 15:45:22Z warnes $
1	1
2	2	read.xls <- function(xls, sheet = 1, verbose=FALSE, pattern,
3	3	na.strings = c("NA","#DIV/0!"), ...,

27	27	findPerl(perl, verbose = verbose)
28	28
29	29	con <- xls2sep(xls, sheet, verbose=verbose, ..., method=method, perl = perl)
	30	## While xls2sep returns a connection, we are better off directly
	31	## opening the file, so that R can properly handle the encoding. So,
	32	## just grab the full file path to use later, and close the connection.
	33	tfn <- summary(con)$description
	34	close(con)
30	35
31		## load the csv file
32		open(con)
33		tfn <- summary(con)$description
34	36	if (missing(pattern))
35	37	{
36	38	if(verbose)
37	39	cat("Reading", method, "file ", dQuote(tfn), "...\n")
38	40
39	41	if(method=="csv")
40		retval <- read.csv(con, na.strings=na.strings, ...)
	42	retval <- read.csv(tfn, na.strings=na.strings, ...)
41	43	else if (method %in% c("tsv","tab") )
42		retval <- read.delim(con, na.strings=na.strings, ...)
	44	retval <- read.delim(tfn, na.strings=na.strings, ...)
43	45	else
44	46	stop("Unknown method", method)
45	47

48	50	}
49	51	else {
50	52	if(verbose)
51		cat("Searching for lines containing pattern ", pattern, "... ")
52		idx <- grep(pattern, readLines(con))
	53	cat("Searching for lines tfntaining pattern ", pattern, "... ")
	54	idx <- grep(pattern, readLines(tfn))
53	55	if (length(idx) == 0) {
54	56	warning("pattern not found")
55	57	return(NULL)

57	59	if(verbose)
58	60	cat("Done.\n")
59	61
60		seek(con, 0)
61
62	62	if(verbose)
63	63	cat("Reading", method, "file ", dQuote(tfn), "...\n")
64	64
65	65	if(method=="csv")
66		retval <- read.csv(con, skip = idx[1]-1, na.strings=na.strings, ...)
	66	retval <- read.csv(tfn, skip = idx[1]-1, na.strings=na.strings, ...)
67	67	else if (method %in% c("tsv","tab") )
68		retval <- read.delim(con, skip = idx[1]-1, na.strings=na.strings, ...)
	68	retval <- read.delim(tfn, skip = idx[1]-1, na.strings=na.strings, ...)
69	69	else
70	70	stop("Unknown method", method)
71
72		close(con)
73	71
74	72	if(verbose)
75	73	cat("Done.\n")
76	74	}
	75
77	76	retval
78	77	}
79	78

-0

debian/changelog less more

	0	gdata (2.12.0-1) unstable; urgency=low
	1
	2	* New upstream release
	3
	4	* debian/control: Set Build-Depends: to current R version
	5
	6	-- Dirk Eddelbuettel <edd@debian.org> Wed, 12 Sep 2012 16:04:16 -0500
	7
0	8	gdata (2.11.0-1) unstable; urgency=low
1	9
2	10	* New upstream release

-1

debian/control less more

1	1	Section: gnu-r
2	2	Priority: optional
3	3	Maintainer: Dirk Eddelbuettel <edd@debian.org>
4		Build-Depends: cdbs, debhelper (>= 7.0.0), r-base-dev (>= 2.15.0), r-cran-gtools
	4	Build-Depends: cdbs, debhelper (>= 7.0.0), r-base-dev (>= 2.15.1), r-cran-gtools
5	5	Standards-Version: 3.9.3
6	6
7	7	Package: r-cran-gdata

+70

-0

inst/ChangeLog less more

	0	2012-09-12 17:29 warnes
	1
	2	* [r1604] .Rinstignore: Don't ignore .Rnw files, but do ignore .svn
	3	files.
	4
	5	2012-09-11 20:41 warnes
	6
	7	* [r1603] man/interleave.Rd: Clarify workding of DROP argument to
	8	interleave().
	9
	10	2012-09-11 20:37 warnes
	11
	12	* [r1602] man/interleave.Rd: Replace call to aggregate.table() with
	13	equivalent tapply() call since aggregate.table() is being
	14	depreciated.
	15
	16	2012-08-22 16:47 warnes
	17
	18	* [r1601] DESCRIPTION, inst/NEWS: Update DESCRIPTION and NEWS for
	19	gdate 2.11.1.
	20
	21	2012-08-22 16:42 warnes
	22
	23	* [r1600] man/read.xls.Rd: Add example for read.xls() that shows
	24	how to use the fileEncoding
	25	argument to read in latin-1 encoded data.
	26
	27	2012-08-22 16:41 warnes
	28
	29	* [r1599] tests/latin-1.xls, tests/test.read.xls.R,
	30	tests/test.read.xls.Rout.save: Add XLSX test for latin-1
	31	characters, and look for them in their new
	32	location in inst/xls/.
	33
	34	2012-08-22 16:35 warnes
	35
	36	* [r1598] inst/xls/latin-1.xls, inst/xls/latin-1.xlsx: add XLSX
	37	version of latin-1.xls
	38
	39	2012-08-22 15:48 warnes
	40
	41	* [r1597] tests/latin-1.xls, tests/test.read.xls.R,
	42	tests/test.read.xls.Rout.save: Add test file and code to ensure
	43	that read.xls() can properly handle
	44	files with alternative encodings. latin-1.xls contains each of
	45	the
	46	non-ascii latin-1 special characters in both the column headings
	47	and
	48	the body of the file.
	49
	50	2012-08-22 15:45 warnes
	51
	52	* [r1596] R/read.xls.R: Change code to have R read the csv/tab data
	53	from the file rather than
	54	from the connetion we made, so that file encodings can be
	55	properly handled.
	56
	57	2012-08-22 14:29 warnes
	58
	59	* [r1595] R/read.xls.R: Always close the connection.
	60
	61	2012-08-13 22:13 warnes
	62
	63	* [r1594] inst/perl/xls2csv.pl: Remove trailing space from output
	64	line.
	65
	66	2012-06-18 20:32 warnes
	67
	68	* [r1567] inst/NEWS: Update NEWS for 2.11.0 release.
	69
0	70	2012-06-18 20:27 warnes
1	71
2	72	* [r1566] DESCRIPTION: Bump version number and add

+31

-0

inst/NEWS less more

	0	Changes in 2.12.0 (2012-10-12)
	1	------------------------------
	2
	3	Other Changes:
	4
	5	- 'stats::aggregate' was made into a generic on 27-Jan-2010, so that
	6	attempting to call 'aggregate' on a 'table' object will now
	7	incorrectly call 'aggregate.table'. Since 'aggregate.table' can be
	8	replaced by a call to tapply using two index vectors, e.g.
	9	aggregate.table(x, by1=a, by2=b, mean)
	10	can be replaced by
	11	tapply(x, INDEX=list(a, b), FUN=mean),
	12	the 'aggregate.table' function will now display a warning that it
	13	is depreciated and recommending the equivalent call to tapply. It
	14	will be removed entirely in a future version of gdata.
	15
	16	Changes in 2.11.1 (2012-09-22)
	17	------------------------------
	18
	19	Enhancements:
	20
	21	- read.xls() now supports fileEncoding argument to allow non-ascii
	22	encoded data to be handled. See the manual page for an example.
	23
	24	Bug Fixes:
	25
	26	- The perl script utilized by read.xls() was incorrectly appending a
	27	space character at the end of each line, causing problems with
	28	character and NA entries in the final column.
	29
	30
0	31	Changes in 2.11.0 (2012-06-18)
1	32	------------------------------
2	33

inst/doc/mapLevels.pdf less more

Binary diff not shown

inst/doc/unknown.pdf less more

Binary diff not shown

-1

inst/perl/xls2csv.pl less more

266	266	}
267	267	else
268	268	{
269		print OutFile "$outputLine \n"
	269	print OutFile "$outputLine\n"
270	270	}
271	271	}
272	272

-1

inst/perl/xls2tab.pl less more

266	266	}
267	267	else
268	268	{
269		print OutFile "$outputLine \n"
	269	print OutFile "$outputLine\n"
270	270	}
271	271	}
272	272

-1

inst/perl/xls2tsv.pl less more

266	266	}
267	267	else
268	268	{
269		print OutFile "$outputLine \n"
	269	print OutFile "$outputLine\n"
270	270	}
271	271	}
272	272

inst/xls/latin-1.xls less more

Binary diff not shown

inst/xls/latin-1.xlsx less more

Binary diff not shown

+16

-3

man/aggregate.table.Rd less more

0		% $Id: aggregate.table.Rd 1435 2010-05-02 06:11:26Z warnes $
	0	% $Id: aggregate.table.Rd 1605 2012-09-12 17:39:42Z warnes $
1	1	%
2	2	% $Log$
3	3	% Revision 1.7 2005/09/12 15:42:45 nj7w

52	52
53	53	\seealso{ \code{\link{aggregate}}, \code{\link{tapply}},
54	54	\code{\link{interleave}} }
55
	55	\note{This function is DEPRECIATED. Please use \code{tapply}
	56	instead. See example for illustration.}
56	57	\examples{
57	58	# Useful example:
58	59	#
59	60	# Create a 2-way table of means, standard errors, and # obs
60
	61	set.seed(314159)
61	62	g1 <- sample(letters[1:5], 1000, replace=TRUE)
62	63	g2 <- sample(LETTERS[1:3], 1000, replace=TRUE )
63	64	dat <- rnorm(1000)
64	65
65	66	stderr <- function(x) sqrt( var(x,na.rm=TRUE) / nobs(x) )
66	67
	68	## Depreciated:
67	69	means <- aggregate.table( dat, g1, g2, mean )
	70	## Instead use:
	71	means <- tapply( dat, list(g1, g2), mean )
	72
	73	## Depreciated
68	74	stderrs <- aggregate.table( dat, g1, g2, stderr )
	75	## Instead use:
	76	stderrs <- tapply( dat, list(g1, g2), stderr )
	77
	78	## Depreciated
69	79	ns <- aggregate.table( dat, g1, g2, nobs )
	80	## Instead use:
	81	ns <- tapply( dat, list(g1, g2), nobs )
	82
70	83	blanks <- matrix( " ", nrow=5, ncol=3)
71	84
72	85	tab <- interleave( "Mean"=round(means,2),

-6

man/interleave.Rd less more

0		% $Id: interleave.Rd 1435 2010-05-02 06:11:26Z warnes $
	0	% $Id: interleave.Rd 1603 2012-09-11 20:41:43Z warnes $
1	1	%
2	2	% $Log$
3	3	% Revision 1.8 2005/12/12 22:02:48 nj7w

51	51	argument name will be appended to the row names to show the source of
52	52	each row. }
53	53	\item{sep}{Separator between the original row name and the object name.}
54		\item{drop}{logical - If the number of columns in output matrix is 1, whether
55		matrix should be returned or a vector }
	54	\item{drop}{boolean flag - When TRUE, matrices containing one column
	55	will be converted to vectors.}
56	56	}
57	57	\details{
58	58	This function creates a new matrix or data frame from its arguments.

87	87
88	88	stderr <- function(x) sqrt( var(x,na.rm=TRUE) / nobs(x) )
89	89
90		means <- aggregate.table( dat, g1, g2, mean )
91		stderrs <- aggregate.table( dat, g1, g2, stderr )
92		ns <- aggregate.table( dat, g1, g2, nobs )
	90	means <- tapply(dat, list(g1, g2), mean )
	91	stderrs <- tapply(dat, list(g1, g2), stderr )
	92	ns <- tapply(dat, list(g1, g2), nobs )
93	93	blanks <- matrix( " ", nrow=5, ncol=3)
94	94
95	95	tab <- interleave( "Mean"=round(means,2),

+26

-19

man/read.xls.Rd less more

86	86
87	87
88	88	\dontrun{
89		# Example specifying exact Perl path for default MS-Windows install of
90		# ActiveState perl
	89	## Example specifying exact Perl path for default MS-Windows install of
	90	## ActiveState perl
91	91	iris <- read.xls(xlsfile, perl="C:/perl/bin/perl.exe")
92	92	}
93	93
94	94	\dontrun{
95		# Example specifying exact Perl path for Unix systems
	95	## Example specifying exact Perl path for Unix systems
96	96	iris <- read.xls(xlsfile, perl="/usr/bin/perl")
97	97
98		# finding perl
99		# (read.xls automatically calls findPerl so this is rarely needed)
	98	## finding perl
	99	## (read.xls automatically calls findPerl so this is rarely needed)
100	100	perl <- gdata:::findPerl("perl")
101	101	iris <- read.xls(xlsfile, perl=perl)
102	102	}
103	103
104	104	\dontrun{
105		# read xls file from net
	105	## read xls file from net
106	106	nba.url <- "http://mgtclass.mgt.unm.edu/Bose/Excel/Tutorial.05/Cases/NBA.xls"
107	107	nba <- read.xls(nba.url)
108	108	}
109	109
110	110	\dontrun{
111		# read xls file ignoring all lines prior to first containing State
	111	## read xls file ignoring all lines prior to first containing State
112	112	crime.url <- "http://www.jrsainfo.org/jabg/state_data2/Tribal_Data00.xls"
113	113	crime <- read.xls(crime.url, pattern = "State")
114	114
115		# use of xls2csv - open con, print two lines, close con
	115	## use of xls2csv - open con, print two lines, close con
116	116	con <- xls2csv(crime.url)
117	117	print(readLines(con, 2))
118	118	file.remove(summary(con)$description)
119	119	}
120	120
121		# Examples demonstrating selection of specific 'sheets'
122		# from the example XLS file 'ExampleExcelFile.xls'
	121	## Examples demonstrating selection of specific 'sheets'
	122	## from the example XLS file 'ExampleExcelFile.xls'
123	123	exampleFile <- file.path(.path.package('gdata'),'xls',
124	124	'ExampleExcelFile.xls')
125	125	exampleFile2007 <- file.path(.path.package('gdata'),'xls',
126	126	'ExampleExcelFile.xlsx')
127	127
128		# see the number and names of sheets:
	128	## see the number and names of sheets:
129	129	sheetCount(exampleFile)
130		if( 'XLSX' \%in\% xlsFormats() ) # if XLSX is supported..
	130	if( 'XLSX' \%in\% xlsFormats() ) ## if XLSX is supported..
131	131	sheetCount(exampleFile2007)
132	132
133	133
134		# show names of shets in the file
	134	## show names of shets in the file
135	135	sheetNames(exampleFile)
136		if( 'XLSX' \%in\% xlsFormats() ) # if XLSX is supported..
	136	if( 'XLSX' \%in\% xlsFormats() ) ## if XLSX is supported..
137	137	sheetNames(exampleFile2007)
138	138
139		data <- read.xls(exampleFile) # default is first worksheet
140		data <- read.xls(exampleFile, sheet=2) # second worksheet by number
141		data <- read.xls(exampleFile, sheet="Sheet Second",v=TRUE) # and by name
	139	data <- read.xls(exampleFile) ## default is first worksheet
	140	data <- read.xls(exampleFile, sheet=2) ## second worksheet by number
	141	data <- read.xls(exampleFile, sheet="Sheet Second",v=TRUE) ## and by name
142	142
143		# load the third worksheet, skipping the first two non-data lines...
144		if( 'XLSX' \%in\% xlsFormats() ) # if XLSX is supported..
	143	## load the third worksheet, skipping the first two non-data lines...
	144	if( 'XLSX' \%in\% xlsFormats() ) ## if XLSX is supported..
145	145	data <- read.xls(exampleFile2007, sheet="Sheet with initial text", skip=2)
	146
	147	## load a file containing data and column names using latin-1
	148	## characters
	149	latinFile <- file.path(.path.package('gdata'),'xls','latin-1.xls')
	150	latin1 <- read.xls(latinFile, fileEncoding="latin1")
	151	colnames(latin1)
	152
146	153
147	154	}
148	155	\author{

+11

-2

tests/test.read.xls.R less more

83	83	}
84	84
85	85
	86	## Check handing of fileEncoding for latin-1 characters
	87
	88	latin1File <- file.path(.path.package('gdata'),'xls', 'latin-1.xls')
	89	latin1FileX <- file.path(.path.package('gdata'),'xls', 'latin-1.xlsx')
	90
	91	example.latin1 <- read.xls(latin1File, fileEncoding='latin1')
	92
	93	if( 'XLSX' %in% xlsFormats() )
	94	{
	95	example.latin1.x <- read.xls(latin1FileX, fileEncoding='latin1')
	96	}
86	97
87	98
88
89

+527

-518

tests/test.read.xls.Rout.save less more

41	41	>
42	42	> iris.1 <- read.xls(xlsfile) # defaults to csv format
43	43	> iris.1
44		Sepal.Length Sepal.Width Petal.Length Petal.Width Species
45		1 5.1 3.5 1.4 0.2 setosa
46		2 4.9 3.0 1.4 0.2 setosa
47		3 4.7 3.2 1.3 0.2 setosa
48		4 4.6 3.1 1.5 0.2 setosa
49		5 5.0 3.6 1.4 0.2 setosa
50		6 5.4 3.9 1.7 0.4 setosa
51		7 4.6 3.4 1.4 0.3 setosa
52		8 5.0 3.4 1.5 0.2 setosa
53		9 4.4 2.9 1.4 0.2 setosa
54		10 4.9 3.1 1.5 0.1 setosa
55		11 5.4 3.7 1.5 0.2 setosa
56		12 4.8 3.4 1.6 0.2 setosa
57		13 4.8 3.0 1.4 0.1 setosa
58		14 4.3 3.0 1.1 0.1 setosa
59		15 5.8 4.0 1.2 0.2 setosa
60		16 5.7 4.4 1.5 0.4 setosa
61		17 5.4 3.9 1.3 0.4 setosa
62		18 5.1 3.5 1.4 0.3 setosa
63		19 5.7 3.8 1.7 0.3 setosa
64		20 5.1 3.8 1.5 0.3 setosa
65		21 5.4 3.4 1.7 0.2 setosa
66		22 5.1 3.7 1.5 0.4 setosa
67		23 4.6 3.6 1.0 0.2 setosa
68		24 5.1 3.3 1.7 0.5 setosa
69		25 4.8 3.4 1.9 0.2 setosa
70		26 5.0 3.0 1.6 0.2 setosa
71		27 5.0 3.4 1.6 0.4 setosa
72		28 5.2 3.5 1.5 0.2 setosa
73		29 5.2 3.4 1.4 0.2 setosa
74		30 4.7 3.2 1.6 0.2 setosa
75		31 4.8 3.1 1.6 0.2 setosa
76		32 5.4 3.4 1.5 0.4 setosa
77		33 5.2 4.1 1.5 0.1 setosa
78		34 5.5 4.2 1.4 0.2 setosa
79		35 4.9 3.1 1.5 0.2 setosa
80		36 5.0 3.2 1.2 0.2 setosa
81		37 5.5 3.5 1.3 0.2 setosa
82		38 4.9 3.6 1.4 0.1 setosa
83		39 4.4 3.0 1.3 0.2 setosa
84		40 5.1 3.4 1.5 0.2 setosa
85		41 5.0 3.5 1.3 0.3 setosa
86		42 4.5 2.3 1.3 0.3 setosa
87		43 4.4 3.2 1.3 0.2 setosa
88		44 5.0 3.5 1.6 0.6 setosa
89		45 5.1 3.8 1.9 0.4 setosa
90		46 4.8 3.0 1.4 0.3 setosa
91		47 5.1 3.8 1.6 0.2 setosa
92		48 4.6 3.2 1.4 0.2 setosa
93		49 5.3 3.7 1.5 0.2 setosa
94		50 5.0 3.3 1.4 0.2 setosa
95		51 7.0 3.2 4.7 1.4 versicolor
96		52 6.4 3.2 4.5 1.5 versicolor
97		53 6.9 3.1 4.9 1.5 versicolor
98		54 5.5 2.3 4.0 1.3 versicolor
99		55 6.5 2.8 4.6 1.5 versicolor
100		56 5.7 2.8 4.5 1.3 versicolor
101		57 6.3 3.3 4.7 1.6 versicolor
102		58 4.9 2.4 3.3 1.0 versicolor
103		59 6.6 2.9 4.6 1.3 versicolor
104		60 5.2 2.7 3.9 1.4 versicolor
105		61 5.0 2.0 3.5 1.0 versicolor
106		62 5.9 3.0 4.2 1.5 versicolor
107		63 6.0 2.2 4.0 1.0 versicolor
108		64 6.1 2.9 4.7 1.4 versicolor
109		65 5.6 2.9 3.6 1.3 versicolor
110		66 6.7 3.1 4.4 1.4 versicolor
111		67 5.6 3.0 4.5 1.5 versicolor
112		68 5.8 2.7 4.1 1.0 versicolor
113		69 6.2 2.2 4.5 1.5 versicolor
114		70 5.6 2.5 3.9 1.1 versicolor
115		71 5.9 3.2 4.8 1.8 versicolor
116		72 6.1 2.8 4.0 1.3 versicolor
117		73 6.3 2.5 4.9 1.5 versicolor
118		74 6.1 2.8 4.7 1.2 versicolor
119		75 6.4 2.9 4.3 1.3 versicolor
120		76 6.6 3.0 4.4 1.4 versicolor
121		77 6.8 2.8 4.8 1.4 versicolor
122		78 6.7 3.0 5.0 1.7 versicolor
123		79 6.0 2.9 4.5 1.5 versicolor
124		80 5.7 2.6 3.5 1.0 versicolor
125		81 5.5 2.4 3.8 1.1 versicolor
126		82 5.5 2.4 3.7 1.0 versicolor
127		83 5.8 2.7 3.9 1.2 versicolor
128		84 6.0 2.7 5.1 1.6 versicolor
129		85 5.4 3.0 4.5 1.5 versicolor
130		86 6.0 3.4 4.5 1.6 versicolor
131		87 6.7 3.1 4.7 1.5 versicolor
132		88 6.3 2.3 4.4 1.3 versicolor
133		89 5.6 3.0 4.1 1.3 versicolor
134		90 5.5 2.5 4.0 1.3 versicolor
135		91 5.5 2.6 4.4 1.2 versicolor
136		92 6.1 3.0 4.6 1.4 versicolor
137		93 5.8 2.6 4.0 1.2 versicolor
138		94 5.0 2.3 3.3 1.0 versicolor
139		95 5.6 2.7 4.2 1.3 versicolor
140		96 5.7 3.0 4.2 1.2 versicolor
141		97 5.7 2.9 4.2 1.3 versicolor
142		98 6.2 2.9 4.3 1.3 versicolor
143		99 5.1 2.5 3.0 1.1 versicolor
144		100 5.7 2.8 4.1 1.3 versicolor
145		101 6.3 3.3 6.0 2.5 virginica
146		102 5.8 2.7 5.1 1.9 virginica
147		103 7.1 3.0 5.9 2.1 virginica
148		104 6.3 2.9 5.6 1.8 virginica
149		105 6.5 3.0 5.8 2.2 virginica
150		106 7.6 3.0 6.6 2.1 virginica
151		107 4.9 2.5 4.5 1.7 virginica
152		108 7.3 2.9 6.3 1.8 virginica
153		109 6.7 2.5 5.8 1.8 virginica
154		110 7.2 3.6 6.1 2.5 virginica
155		111 6.5 3.2 5.1 2.0 virginica
156		112 6.4 2.7 5.3 1.9 virginica
157		113 6.8 3.0 5.5 2.1 virginica
158		114 5.7 2.5 5.0 2.0 virginica
159		115 5.8 2.8 5.1 2.4 virginica
160		116 6.4 3.2 5.3 2.3 virginica
161		117 6.5 3.0 5.5 1.8 virginica
162		118 7.7 3.8 6.7 2.2 virginica
163		119 7.7 2.6 6.9 2.3 virginica
164		120 6.0 2.2 5.0 1.5 virginica
165		121 6.9 3.2 5.7 2.3 virginica
166		122 5.6 2.8 4.9 2.0 virginica
167		123 7.7 2.8 6.7 2.0 virginica
168		124 6.3 2.7 4.9 1.8 virginica
169		125 6.7 3.3 5.7 2.1 virginica
170		126 7.2 3.2 6.0 1.8 virginica
171		127 6.2 2.8 4.8 1.8 virginica
172		128 6.1 3.0 4.9 1.8 virginica
173		129 6.4 2.8 5.6 2.1 virginica
174		130 7.2 3.0 5.8 1.6 virginica
175		131 7.4 2.8 6.1 1.9 virginica
176		132 7.9 3.8 6.4 2.0 virginica
177		133 6.4 2.8 5.6 2.2 virginica
178		134 6.3 2.8 5.1 1.5 virginica
179		135 6.1 2.6 5.6 1.4 virginica
180		136 7.7 3.0 6.1 2.3 virginica
181		137 6.3 3.4 5.6 2.4 virginica
182		138 6.4 3.1 5.5 1.8 virginica
183		139 6.0 3.0 4.8 1.8 virginica
184		140 6.9 3.1 5.4 2.1 virginica
185		141 6.7 3.1 5.6 2.4 virginica
186		142 6.9 3.1 5.1 2.3 virginica
187		143 5.8 2.7 5.1 1.9 virginica
188		144 6.8 3.2 5.9 2.3 virginica
189		145 6.7 3.3 5.7 2.5 virginica
190		146 6.7 3.0 5.2 2.3 virginica
191		147 6.3 2.5 5.0 1.9 virginica
192		148 6.5 3.0 5.2 2.0 virginica
193		149 6.2 3.4 5.4 2.3 virginica
194		150 5.9 3.0 5.1 1.8 virginica
	44	Sepal.Length Sepal.Width Petal.Length Petal.Width Species
	45	1 5.1 3.5 1.4 0.2 setosa
	46	2 4.9 3.0 1.4 0.2 setosa
	47	3 4.7 3.2 1.3 0.2 setosa
	48	4 4.6 3.1 1.5 0.2 setosa
	49	5 5.0 3.6 1.4 0.2 setosa
	50	6 5.4 3.9 1.7 0.4 setosa
	51	7 4.6 3.4 1.4 0.3 setosa
	52	8 5.0 3.4 1.5 0.2 setosa
	53	9 4.4 2.9 1.4 0.2 setosa
	54	10 4.9 3.1 1.5 0.1 setosa
	55	11 5.4 3.7 1.5 0.2 setosa
	56	12 4.8 3.4 1.6 0.2 setosa
	57	13 4.8 3.0 1.4 0.1 setosa
	58	14 4.3 3.0 1.1 0.1 setosa
	59	15 5.8 4.0 1.2 0.2 setosa
	60	16 5.7 4.4 1.5 0.4 setosa
	61	17 5.4 3.9 1.3 0.4 setosa
	62	18 5.1 3.5 1.4 0.3 setosa
	63	19 5.7 3.8 1.7 0.3 setosa
	64	20 5.1 3.8 1.5 0.3 setosa
	65	21 5.4 3.4 1.7 0.2 setosa
	66	22 5.1 3.7 1.5 0.4 setosa
	67	23 4.6 3.6 1.0 0.2 setosa
	68	24 5.1 3.3 1.7 0.5 setosa
	69	25 4.8 3.4 1.9 0.2 setosa
	70	26 5.0 3.0 1.6 0.2 setosa
	71	27 5.0 3.4 1.6 0.4 setosa
	72	28 5.2 3.5 1.5 0.2 setosa
	73	29 5.2 3.4 1.4 0.2 setosa
	74	30 4.7 3.2 1.6 0.2 setosa
	75	31 4.8 3.1 1.6 0.2 setosa
	76	32 5.4 3.4 1.5 0.4 setosa
	77	33 5.2 4.1 1.5 0.1 setosa
	78	34 5.5 4.2 1.4 0.2 setosa
	79	35 4.9 3.1 1.5 0.2 setosa
	80	36 5.0 3.2 1.2 0.2 setosa
	81	37 5.5 3.5 1.3 0.2 setosa
	82	38 4.9 3.6 1.4 0.1 setosa
	83	39 4.4 3.0 1.3 0.2 setosa
	84	40 5.1 3.4 1.5 0.2 setosa
	85	41 5.0 3.5 1.3 0.3 setosa
	86	42 4.5 2.3 1.3 0.3 setosa
	87	43 4.4 3.2 1.3 0.2 setosa
	88	44 5.0 3.5 1.6 0.6 setosa
	89	45 5.1 3.8 1.9 0.4 setosa
	90	46 4.8 3.0 1.4 0.3 setosa
	91	47 5.1 3.8 1.6 0.2 setosa
	92	48 4.6 3.2 1.4 0.2 setosa
	93	49 5.3 3.7 1.5 0.2 setosa
	94	50 5.0 3.3 1.4 0.2 setosa
	95	51 7.0 3.2 4.7 1.4 versicolor
	96	52 6.4 3.2 4.5 1.5 versicolor
	97	53 6.9 3.1 4.9 1.5 versicolor
	98	54 5.5 2.3 4.0 1.3 versicolor
	99	55 6.5 2.8 4.6 1.5 versicolor
	100	56 5.7 2.8 4.5 1.3 versicolor
	101	57 6.3 3.3 4.7 1.6 versicolor
	102	58 4.9 2.4 3.3 1.0 versicolor
	103	59 6.6 2.9 4.6 1.3 versicolor
	104	60 5.2 2.7 3.9 1.4 versicolor
	105	61 5.0 2.0 3.5 1.0 versicolor
	106	62 5.9 3.0 4.2 1.5 versicolor
	107	63 6.0 2.2 4.0 1.0 versicolor
	108	64 6.1 2.9 4.7 1.4 versicolor
	109	65 5.6 2.9 3.6 1.3 versicolor
	110	66 6.7 3.1 4.4 1.4 versicolor
	111	67 5.6 3.0 4.5 1.5 versicolor
	112	68 5.8 2.7 4.1 1.0 versicolor
	113	69 6.2 2.2 4.5 1.5 versicolor
	114	70 5.6 2.5 3.9 1.1 versicolor
	115	71 5.9 3.2 4.8 1.8 versicolor
	116	72 6.1 2.8 4.0 1.3 versicolor
	117	73 6.3 2.5 4.9 1.5 versicolor
	118	74 6.1 2.8 4.7 1.2 versicolor
	119	75 6.4 2.9 4.3 1.3 versicolor
	120	76 6.6 3.0 4.4 1.4 versicolor
	121	77 6.8 2.8 4.8 1.4 versicolor
	122	78 6.7 3.0 5.0 1.7 versicolor
	123	79 6.0 2.9 4.5 1.5 versicolor
	124	80 5.7 2.6 3.5 1.0 versicolor
	125	81 5.5 2.4 3.8 1.1 versicolor
	126	82 5.5 2.4 3.7 1.0 versicolor
	127	83 5.8 2.7 3.9 1.2 versicolor
	128	84 6.0 2.7 5.1 1.6 versicolor
	129	85 5.4 3.0 4.5 1.5 versicolor
	130	86 6.0 3.4 4.5 1.6 versicolor
	131	87 6.7 3.1 4.7 1.5 versicolor
	132	88 6.3 2.3 4.4 1.3 versicolor
	133	89 5.6 3.0 4.1 1.3 versicolor
	134	90 5.5 2.5 4.0 1.3 versicolor
	135	91 5.5 2.6 4.4 1.2 versicolor
	136	92 6.1 3.0 4.6 1.4 versicolor
	137	93 5.8 2.6 4.0 1.2 versicolor
	138	94 5.0 2.3 3.3 1.0 versicolor
	139	95 5.6 2.7 4.2 1.3 versicolor
	140	96 5.7 3.0 4.2 1.2 versicolor
	141	97 5.7 2.9 4.2 1.3 versicolor
	142	98 6.2 2.9 4.3 1.3 versicolor
	143	99 5.1 2.5 3.0 1.1 versicolor
	144	100 5.7 2.8 4.1 1.3 versicolor
	145	101 6.3 3.3 6.0 2.5 virginica
	146	102 5.8 2.7 5.1 1.9 virginica
	147	103 7.1 3.0 5.9 2.1 virginica
	148	104 6.3 2.9 5.6 1.8 virginica
	149	105 6.5 3.0 5.8 2.2 virginica
	150	106 7.6 3.0 6.6 2.1 virginica
	151	107 4.9 2.5 4.5 1.7 virginica
	152	108 7.3 2.9 6.3 1.8 virginica
	153	109 6.7 2.5 5.8 1.8 virginica
	154	110 7.2 3.6 6.1 2.5 virginica
	155	111 6.5 3.2 5.1 2.0 virginica
	156	112 6.4 2.7 5.3 1.9 virginica
	157	113 6.8 3.0 5.5 2.1 virginica
	158	114 5.7 2.5 5.0 2.0 virginica
	159	115 5.8 2.8 5.1 2.4 virginica
	160	116 6.4 3.2 5.3 2.3 virginica
	161	117 6.5 3.0 5.5 1.8 virginica
	162	118 7.7 3.8 6.7 2.2 virginica
	163	119 7.7 2.6 6.9 2.3 virginica
	164	120 6.0 2.2 5.0 1.5 virginica
	165	121 6.9 3.2 5.7 2.3 virginica
	166	122 5.6 2.8 4.9 2.0 virginica
	167	123 7.7 2.8 6.7 2.0 virginica
	168	124 6.3 2.7 4.9 1.8 virginica
	169	125 6.7 3.3 5.7 2.1 virginica
	170	126 7.2 3.2 6.0 1.8 virginica
	171	127 6.2 2.8 4.8 1.8 virginica
	172	128 6.1 3.0 4.9 1.8 virginica
	173	129 6.4 2.8 5.6 2.1 virginica
	174	130 7.2 3.0 5.8 1.6 virginica
	175	131 7.4 2.8 6.1 1.9 virginica
	176	132 7.9 3.8 6.4 2.0 virginica
	177	133 6.4 2.8 5.6 2.2 virginica
	178	134 6.3 2.8 5.1 1.5 virginica
	179	135 6.1 2.6 5.6 1.4 virginica
	180	136 7.7 3.0 6.1 2.3 virginica
	181	137 6.3 3.4 5.6 2.4 virginica
	182	138 6.4 3.1 5.5 1.8 virginica
	183	139 6.0 3.0 4.8 1.8 virginica
	184	140 6.9 3.1 5.4 2.1 virginica
	185	141 6.7 3.1 5.6 2.4 virginica
	186	142 6.9 3.1 5.1 2.3 virginica
	187	143 5.8 2.7 5.1 1.9 virginica
	188	144 6.8 3.2 5.9 2.3 virginica
	189	145 6.7 3.3 5.7 2.5 virginica
	190	146 6.7 3.0 5.2 2.3 virginica
	191	147 6.3 2.5 5.0 1.9 virginica
	192	148 6.5 3.0 5.2 2.0 virginica
	193	149 6.2 3.4 5.4 2.3 virginica
	194	150 5.9 3.0 5.1 1.8 virginica
195	195	>
196	196	> iris.2 <- read.xls(xlsfile,method="csv") # specify csv format
197	197	> iris.2
198		Sepal.Length Sepal.Width Petal.Length Petal.Width Species
199		1 5.1 3.5 1.4 0.2 setosa
200		2 4.9 3.0 1.4 0.2 setosa
201		3 4.7 3.2 1.3 0.2 setosa
202		4 4.6 3.1 1.5 0.2 setosa
203		5 5.0 3.6 1.4 0.2 setosa
204		6 5.4 3.9 1.7 0.4 setosa
205		7 4.6 3.4 1.4 0.3 setosa
206		8 5.0 3.4 1.5 0.2 setosa
207		9 4.4 2.9 1.4 0.2 setosa
208		10 4.9 3.1 1.5 0.1 setosa
209		11 5.4 3.7 1.5 0.2 setosa
210		12 4.8 3.4 1.6 0.2 setosa
211		13 4.8 3.0 1.4 0.1 setosa
212		14 4.3 3.0 1.1 0.1 setosa
213		15 5.8 4.0 1.2 0.2 setosa
214		16 5.7 4.4 1.5 0.4 setosa
215		17 5.4 3.9 1.3 0.4 setosa
216		18 5.1 3.5 1.4 0.3 setosa
217		19 5.7 3.8 1.7 0.3 setosa
218		20 5.1 3.8 1.5 0.3 setosa
219		21 5.4 3.4 1.7 0.2 setosa
220		22 5.1 3.7 1.5 0.4 setosa
221		23 4.6 3.6 1.0 0.2 setosa
222		24 5.1 3.3 1.7 0.5 setosa
223		25 4.8 3.4 1.9 0.2 setosa
224		26 5.0 3.0 1.6 0.2 setosa
225		27 5.0 3.4 1.6 0.4 setosa
226		28 5.2 3.5 1.5 0.2 setosa
227		29 5.2 3.4 1.4 0.2 setosa
228		30 4.7 3.2 1.6 0.2 setosa
229		31 4.8 3.1 1.6 0.2 setosa
230		32 5.4 3.4 1.5 0.4 setosa
231		33 5.2 4.1 1.5 0.1 setosa
232		34 5.5 4.2 1.4 0.2 setosa
233		35 4.9 3.1 1.5 0.2 setosa
234		36 5.0 3.2 1.2 0.2 setosa
235		37 5.5 3.5 1.3 0.2 setosa
236		38 4.9 3.6 1.4 0.1 setosa
237		39 4.4 3.0 1.3 0.2 setosa
238		40 5.1 3.4 1.5 0.2 setosa
239		41 5.0 3.5 1.3 0.3 setosa
240		42 4.5 2.3 1.3 0.3 setosa
241		43 4.4 3.2 1.3 0.2 setosa
242		44 5.0 3.5 1.6 0.6 setosa
243		45 5.1 3.8 1.9 0.4 setosa
244		46 4.8 3.0 1.4 0.3 setosa
245		47 5.1 3.8 1.6 0.2 setosa
246		48 4.6 3.2 1.4 0.2 setosa
247		49 5.3 3.7 1.5 0.2 setosa
248		50 5.0 3.3 1.4 0.2 setosa
249		51 7.0 3.2 4.7 1.4 versicolor
250		52 6.4 3.2 4.5 1.5 versicolor
251		53 6.9 3.1 4.9 1.5 versicolor
252		54 5.5 2.3 4.0 1.3 versicolor
253		55 6.5 2.8 4.6 1.5 versicolor
254		56 5.7 2.8 4.5 1.3 versicolor
255		57 6.3 3.3 4.7 1.6 versicolor
256		58 4.9 2.4 3.3 1.0 versicolor
257		59 6.6 2.9 4.6 1.3 versicolor
258		60 5.2 2.7 3.9 1.4 versicolor
259		61 5.0 2.0 3.5 1.0 versicolor
260		62 5.9 3.0 4.2 1.5 versicolor
261		63 6.0 2.2 4.0 1.0 versicolor
262		64 6.1 2.9 4.7 1.4 versicolor
263		65 5.6 2.9 3.6 1.3 versicolor
264		66 6.7 3.1 4.4 1.4 versicolor
265		67 5.6 3.0 4.5 1.5 versicolor
266		68 5.8 2.7 4.1 1.0 versicolor
267		69 6.2 2.2 4.5 1.5 versicolor
268		70 5.6 2.5 3.9 1.1 versicolor
269		71 5.9 3.2 4.8 1.8 versicolor
270		72 6.1 2.8 4.0 1.3 versicolor
271		73 6.3 2.5 4.9 1.5 versicolor
272		74 6.1 2.8 4.7 1.2 versicolor
273		75 6.4 2.9 4.3 1.3 versicolor
274		76 6.6 3.0 4.4 1.4 versicolor
275		77 6.8 2.8 4.8 1.4 versicolor
276		78 6.7 3.0 5.0 1.7 versicolor
277		79 6.0 2.9 4.5 1.5 versicolor
278		80 5.7 2.6 3.5 1.0 versicolor
279		81 5.5 2.4 3.8 1.1 versicolor
280		82 5.5 2.4 3.7 1.0 versicolor
281		83 5.8 2.7 3.9 1.2 versicolor
282		84 6.0 2.7 5.1 1.6 versicolor
283		85 5.4 3.0 4.5 1.5 versicolor
284		86 6.0 3.4 4.5 1.6 versicolor
285		87 6.7 3.1 4.7 1.5 versicolor
286		88 6.3 2.3 4.4 1.3 versicolor
287		89 5.6 3.0 4.1 1.3 versicolor
288		90 5.5 2.5 4.0 1.3 versicolor
289		91 5.5 2.6 4.4 1.2 versicolor
290		92 6.1 3.0 4.6 1.4 versicolor
291		93 5.8 2.6 4.0 1.2 versicolor
292		94 5.0 2.3 3.3 1.0 versicolor
293		95 5.6 2.7 4.2 1.3 versicolor
294		96 5.7 3.0 4.2 1.2 versicolor
295		97 5.7 2.9 4.2 1.3 versicolor
296		98 6.2 2.9 4.3 1.3 versicolor
297		99 5.1 2.5 3.0 1.1 versicolor
298		100 5.7 2.8 4.1 1.3 versicolor
299		101 6.3 3.3 6.0 2.5 virginica
300		102 5.8 2.7 5.1 1.9 virginica
301		103 7.1 3.0 5.9 2.1 virginica
302		104 6.3 2.9 5.6 1.8 virginica
303		105 6.5 3.0 5.8 2.2 virginica
304		106 7.6 3.0 6.6 2.1 virginica
305		107 4.9 2.5 4.5 1.7 virginica
306		108 7.3 2.9 6.3 1.8 virginica
307		109 6.7 2.5 5.8 1.8 virginica
308		110 7.2 3.6 6.1 2.5 virginica
309		111 6.5 3.2 5.1 2.0 virginica
310		112 6.4 2.7 5.3 1.9 virginica
311		113 6.8 3.0 5.5 2.1 virginica
312		114 5.7 2.5 5.0 2.0 virginica
313		115 5.8 2.8 5.1 2.4 virginica
314		116 6.4 3.2 5.3 2.3 virginica
315		117 6.5 3.0 5.5 1.8 virginica
316		118 7.7 3.8 6.7 2.2 virginica
317		119 7.7 2.6 6.9 2.3 virginica
318		120 6.0 2.2 5.0 1.5 virginica
319		121 6.9 3.2 5.7 2.3 virginica
320		122 5.6 2.8 4.9 2.0 virginica
321		123 7.7 2.8 6.7 2.0 virginica
322		124 6.3 2.7 4.9 1.8 virginica
323		125 6.7 3.3 5.7 2.1 virginica
324		126 7.2 3.2 6.0 1.8 virginica
325		127 6.2 2.8 4.8 1.8 virginica
326		128 6.1 3.0 4.9 1.8 virginica
327		129 6.4 2.8 5.6 2.1 virginica
328		130 7.2 3.0 5.8 1.6 virginica
329		131 7.4 2.8 6.1 1.9 virginica
330		132 7.9 3.8 6.4 2.0 virginica
331		133 6.4 2.8 5.6 2.2 virginica
332		134 6.3 2.8 5.1 1.5 virginica
333		135 6.1 2.6 5.6 1.4 virginica
334		136 7.7 3.0 6.1 2.3 virginica
335		137 6.3 3.4 5.6 2.4 virginica
336		138 6.4 3.1 5.5 1.8 virginica
337		139 6.0 3.0 4.8 1.8 virginica
338		140 6.9 3.1 5.4 2.1 virginica
339		141 6.7 3.1 5.6 2.4 virginica
340		142 6.9 3.1 5.1 2.3 virginica
341		143 5.8 2.7 5.1 1.9 virginica
342		144 6.8 3.2 5.9 2.3 virginica
343		145 6.7 3.3 5.7 2.5 virginica
344		146 6.7 3.0 5.2 2.3 virginica
345		147 6.3 2.5 5.0 1.9 virginica
346		148 6.5 3.0 5.2 2.0 virginica
347		149 6.2 3.4 5.4 2.3 virginica
348		150 5.9 3.0 5.1 1.8 virginica
	198	Sepal.Length Sepal.Width Petal.Length Petal.Width Species
	199	1 5.1 3.5 1.4 0.2 setosa
	200	2 4.9 3.0 1.4 0.2 setosa
	201	3 4.7 3.2 1.3 0.2 setosa
	202	4 4.6 3.1 1.5 0.2 setosa
	203	5 5.0 3.6 1.4 0.2 setosa
	204	6 5.4 3.9 1.7 0.4 setosa
	205	7 4.6 3.4 1.4 0.3 setosa
	206	8 5.0 3.4 1.5 0.2 setosa
	207	9 4.4 2.9 1.4 0.2 setosa
	208	10 4.9 3.1 1.5 0.1 setosa
	209	11 5.4 3.7 1.5 0.2 setosa
	210	12 4.8 3.4 1.6 0.2 setosa
	211	13 4.8 3.0 1.4 0.1 setosa
	212	14 4.3 3.0 1.1 0.1 setosa
	213	15 5.8 4.0 1.2 0.2 setosa
	214	16 5.7 4.4 1.5 0.4 setosa
	215	17 5.4 3.9 1.3 0.4 setosa
	216	18 5.1 3.5 1.4 0.3 setosa
	217	19 5.7 3.8 1.7 0.3 setosa
	218	20 5.1 3.8 1.5 0.3 setosa
	219	21 5.4 3.4 1.7 0.2 setosa
	220	22 5.1 3.7 1.5 0.4 setosa
	221	23 4.6 3.6 1.0 0.2 setosa
	222	24 5.1 3.3 1.7 0.5 setosa
	223	25 4.8 3.4 1.9 0.2 setosa
	224	26 5.0 3.0 1.6 0.2 setosa
	225	27 5.0 3.4 1.6 0.4 setosa
	226	28 5.2 3.5 1.5 0.2 setosa
	227	29 5.2 3.4 1.4 0.2 setosa
	228	30 4.7 3.2 1.6 0.2 setosa
	229	31 4.8 3.1 1.6 0.2 setosa
	230	32 5.4 3.4 1.5 0.4 setosa
	231	33 5.2 4.1 1.5 0.1 setosa
	232	34 5.5 4.2 1.4 0.2 setosa
	233	35 4.9 3.1 1.5 0.2 setosa
	234	36 5.0 3.2 1.2 0.2 setosa
	235	37 5.5 3.5 1.3 0.2 setosa
	236	38 4.9 3.6 1.4 0.1 setosa
	237	39 4.4 3.0 1.3 0.2 setosa
	238	40 5.1 3.4 1.5 0.2 setosa
	239	41 5.0 3.5 1.3 0.3 setosa
	240	42 4.5 2.3 1.3 0.3 setosa
	241	43 4.4 3.2 1.3 0.2 setosa
	242	44 5.0 3.5 1.6 0.6 setosa
	243	45 5.1 3.8 1.9 0.4 setosa
	244	46 4.8 3.0 1.4 0.3 setosa
	245	47 5.1 3.8 1.6 0.2 setosa
	246	48 4.6 3.2 1.4 0.2 setosa
	247	49 5.3 3.7 1.5 0.2 setosa
	248	50 5.0 3.3 1.4 0.2 setosa
	249	51 7.0 3.2 4.7 1.4 versicolor
	250	52 6.4 3.2 4.5 1.5 versicolor
	251	53 6.9 3.1 4.9 1.5 versicolor
	252	54 5.5 2.3 4.0 1.3 versicolor
	253	55 6.5 2.8 4.6 1.5 versicolor
	254	56 5.7 2.8 4.5 1.3 versicolor
	255	57 6.3 3.3 4.7 1.6 versicolor
	256	58 4.9 2.4 3.3 1.0 versicolor
	257	59 6.6 2.9 4.6 1.3 versicolor
	258	60 5.2 2.7 3.9 1.4 versicolor
	259	61 5.0 2.0 3.5 1.0 versicolor
	260	62 5.9 3.0 4.2 1.5 versicolor
	261	63 6.0 2.2 4.0 1.0 versicolor
	262	64 6.1 2.9 4.7 1.4 versicolor
	263	65 5.6 2.9 3.6 1.3 versicolor
	264	66 6.7 3.1 4.4 1.4 versicolor
	265	67 5.6 3.0 4.5 1.5 versicolor
	266	68 5.8 2.7 4.1 1.0 versicolor
	267	69 6.2 2.2 4.5 1.5 versicolor
	268	70 5.6 2.5 3.9 1.1 versicolor
	269	71 5.9 3.2 4.8 1.8 versicolor
	270	72 6.1 2.8 4.0 1.3 versicolor
	271	73 6.3 2.5 4.9 1.5 versicolor
	272	74 6.1 2.8 4.7 1.2 versicolor
	273	75 6.4 2.9 4.3 1.3 versicolor
	274	76 6.6 3.0 4.4 1.4 versicolor
	275	77 6.8 2.8 4.8 1.4 versicolor
	276	78 6.7 3.0 5.0 1.7 versicolor
	277	79 6.0 2.9 4.5 1.5 versicolor
	278	80 5.7 2.6 3.5 1.0 versicolor
	279	81 5.5 2.4 3.8 1.1 versicolor
	280	82 5.5 2.4 3.7 1.0 versicolor
	281	83 5.8 2.7 3.9 1.2 versicolor
	282	84 6.0 2.7 5.1 1.6 versicolor
	283	85 5.4 3.0 4.5 1.5 versicolor
	284	86 6.0 3.4 4.5 1.6 versicolor
	285	87 6.7 3.1 4.7 1.5 versicolor
	286	88 6.3 2.3 4.4 1.3 versicolor
	287	89 5.6 3.0 4.1 1.3 versicolor
	288	90 5.5 2.5 4.0 1.3 versicolor
	289	91 5.5 2.6 4.4 1.2 versicolor
	290	92 6.1 3.0 4.6 1.4 versicolor
	291	93 5.8 2.6 4.0 1.2 versicolor
	292	94 5.0 2.3 3.3 1.0 versicolor
	293	95 5.6 2.7 4.2 1.3 versicolor
	294	96 5.7 3.0 4.2 1.2 versicolor
	295	97 5.7 2.9 4.2 1.3 versicolor
	296	98 6.2 2.9 4.3 1.3 versicolor
	297	99 5.1 2.5 3.0 1.1 versicolor
	298	100 5.7 2.8 4.1 1.3 versicolor
	299	101 6.3 3.3 6.0 2.5 virginica
	300	102 5.8 2.7 5.1 1.9 virginica
	301	103 7.1 3.0 5.9 2.1 virginica
	302	104 6.3 2.9 5.6 1.8 virginica
	303	105 6.5 3.0 5.8 2.2 virginica
	304	106 7.6 3.0 6.6 2.1 virginica
	305	107 4.9 2.5 4.5 1.7 virginica
	306	108 7.3 2.9 6.3 1.8 virginica
	307	109 6.7 2.5 5.8 1.8 virginica
	308	110 7.2 3.6 6.1 2.5 virginica
	309	111 6.5 3.2 5.1 2.0 virginica
	310	112 6.4 2.7 5.3 1.9 virginica
	311	113 6.8 3.0 5.5 2.1 virginica
	312	114 5.7 2.5 5.0 2.0 virginica
	313	115 5.8 2.8 5.1 2.4 virginica
	314	116 6.4 3.2 5.3 2.3 virginica
	315	117 6.5 3.0 5.5 1.8 virginica
	316	118 7.7 3.8 6.7 2.2 virginica
	317	119 7.7 2.6 6.9 2.3 virginica
	318	120 6.0 2.2 5.0 1.5 virginica
	319	121 6.9 3.2 5.7 2.3 virginica
	320	122 5.6 2.8 4.9 2.0 virginica
	321	123 7.7 2.8 6.7 2.0 virginica
	322	124 6.3 2.7 4.9 1.8 virginica
	323	125 6.7 3.3 5.7 2.1 virginica
	324	126 7.2 3.2 6.0 1.8 virginica
	325	127 6.2 2.8 4.8 1.8 virginica
	326	128 6.1 3.0 4.9 1.8 virginica
	327	129 6.4 2.8 5.6 2.1 virginica
	328	130 7.2 3.0 5.8 1.6 virginica
	329	131 7.4 2.8 6.1 1.9 virginica
	330	132 7.9 3.8 6.4 2.0 virginica
	331	133 6.4 2.8 5.6 2.2 virginica
	332	134 6.3 2.8 5.1 1.5 virginica
	333	135 6.1 2.6 5.6 1.4 virginica
	334	136 7.7 3.0 6.1 2.3 virginica
	335	137 6.3 3.4 5.6 2.4 virginica
	336	138 6.4 3.1 5.5 1.8 virginica
	337	139 6.0 3.0 4.8 1.8 virginica
	338	140 6.9 3.1 5.4 2.1 virginica
	339	141 6.7 3.1 5.6 2.4 virginica
	340	142 6.9 3.1 5.1 2.3 virginica
	341	143 5.8 2.7 5.1 1.9 virginica
	342	144 6.8 3.2 5.9 2.3 virginica
	343	145 6.7 3.3 5.7 2.5 virginica
	344	146 6.7 3.0 5.2 2.3 virginica
	345	147 6.3 2.5 5.0 1.9 virginica
	346	148 6.5 3.0 5.2 2.0 virginica
	347	149 6.2 3.4 5.4 2.3 virginica
	348	150 5.9 3.0 5.1 1.8 virginica
349	349	>
350	350	> iris.3 <- read.xls(xlsfile,method="tab") # specify tab format
351	351	> iris.3
352		Sepal.Length Sepal.Width Petal.Length Petal.Width Species
353		1 5.1 3.5 1.4 0.2 setosa
354		2 4.9 3.0 1.4 0.2 setosa
355		3 4.7 3.2 1.3 0.2 setosa
356		4 4.6 3.1 1.5 0.2 setosa
357		5 5.0 3.6 1.4 0.2 setosa
358		6 5.4 3.9 1.7 0.4 setosa
359		7 4.6 3.4 1.4 0.3 setosa
360		8 5.0 3.4 1.5 0.2 setosa
361		9 4.4 2.9 1.4 0.2 setosa
362		10 4.9 3.1 1.5 0.1 setosa
363		11 5.4 3.7 1.5 0.2 setosa
364		12 4.8 3.4 1.6 0.2 setosa
365		13 4.8 3.0 1.4 0.1 setosa
366		14 4.3 3.0 1.1 0.1 setosa
367		15 5.8 4.0 1.2 0.2 setosa
368		16 5.7 4.4 1.5 0.4 setosa
369		17 5.4 3.9 1.3 0.4 setosa
370		18 5.1 3.5 1.4 0.3 setosa
371		19 5.7 3.8 1.7 0.3 setosa
372		20 5.1 3.8 1.5 0.3 setosa
373		21 5.4 3.4 1.7 0.2 setosa
374		22 5.1 3.7 1.5 0.4 setosa
375		23 4.6 3.6 1.0 0.2 setosa
376		24 5.1 3.3 1.7 0.5 setosa
377		25 4.8 3.4 1.9 0.2 setosa
378		26 5.0 3.0 1.6 0.2 setosa
379		27 5.0 3.4 1.6 0.4 setosa
380		28 5.2 3.5 1.5 0.2 setosa
381		29 5.2 3.4 1.4 0.2 setosa
382		30 4.7 3.2 1.6 0.2 setosa
383		31 4.8 3.1 1.6 0.2 setosa
384		32 5.4 3.4 1.5 0.4 setosa
385		33 5.2 4.1 1.5 0.1 setosa
386		34 5.5 4.2 1.4 0.2 setosa
387		35 4.9 3.1 1.5 0.2 setosa
388		36 5.0 3.2 1.2 0.2 setosa
389		37 5.5 3.5 1.3 0.2 setosa
390		38 4.9 3.6 1.4 0.1 setosa
391		39 4.4 3.0 1.3 0.2 setosa
392		40 5.1 3.4 1.5 0.2 setosa
393		41 5.0 3.5 1.3 0.3 setosa
394		42 4.5 2.3 1.3 0.3 setosa
395		43 4.4 3.2 1.3 0.2 setosa
396		44 5.0 3.5 1.6 0.6 setosa
397		45 5.1 3.8 1.9 0.4 setosa
398		46 4.8 3.0 1.4 0.3 setosa
399		47 5.1 3.8 1.6 0.2 setosa
400		48 4.6 3.2 1.4 0.2 setosa
401		49 5.3 3.7 1.5 0.2 setosa
402		50 5.0 3.3 1.4 0.2 setosa
403		51 7.0 3.2 4.7 1.4 versicolor
404		52 6.4 3.2 4.5 1.5 versicolor
405		53 6.9 3.1 4.9 1.5 versicolor
406		54 5.5 2.3 4.0 1.3 versicolor
407		55 6.5 2.8 4.6 1.5 versicolor
408		56 5.7 2.8 4.5 1.3 versicolor
409		57 6.3 3.3 4.7 1.6 versicolor
410		58 4.9 2.4 3.3 1.0 versicolor
411		59 6.6 2.9 4.6 1.3 versicolor
412		60 5.2 2.7 3.9 1.4 versicolor
413		61 5.0 2.0 3.5 1.0 versicolor
414		62 5.9 3.0 4.2 1.5 versicolor
415		63 6.0 2.2 4.0 1.0 versicolor
416		64 6.1 2.9 4.7 1.4 versicolor
417		65 5.6 2.9 3.6 1.3 versicolor
418		66 6.7 3.1 4.4 1.4 versicolor
419		67 5.6 3.0 4.5 1.5 versicolor
420		68 5.8 2.7 4.1 1.0 versicolor
421		69 6.2 2.2 4.5 1.5 versicolor
422		70 5.6 2.5 3.9 1.1 versicolor
423		71 5.9 3.2 4.8 1.8 versicolor
424		72 6.1 2.8 4.0 1.3 versicolor
425		73 6.3 2.5 4.9 1.5 versicolor
426		74 6.1 2.8 4.7 1.2 versicolor
427		75 6.4 2.9 4.3 1.3 versicolor
428		76 6.6 3.0 4.4 1.4 versicolor
429		77 6.8 2.8 4.8 1.4 versicolor
430		78 6.7 3.0 5.0 1.7 versicolor
431		79 6.0 2.9 4.5 1.5 versicolor
432		80 5.7 2.6 3.5 1.0 versicolor
433		81 5.5 2.4 3.8 1.1 versicolor
434		82 5.5 2.4 3.7 1.0 versicolor
435		83 5.8 2.7 3.9 1.2 versicolor
436		84 6.0 2.7 5.1 1.6 versicolor
437		85 5.4 3.0 4.5 1.5 versicolor
438		86 6.0 3.4 4.5 1.6 versicolor
439		87 6.7 3.1 4.7 1.5 versicolor
440		88 6.3 2.3 4.4 1.3 versicolor
441		89 5.6 3.0 4.1 1.3 versicolor
442		90 5.5 2.5 4.0 1.3 versicolor
443		91 5.5 2.6 4.4 1.2 versicolor
444		92 6.1 3.0 4.6 1.4 versicolor
445		93 5.8 2.6 4.0 1.2 versicolor
446		94 5.0 2.3 3.3 1.0 versicolor
447		95 5.6 2.7 4.2 1.3 versicolor
448		96 5.7 3.0 4.2 1.2 versicolor
449		97 5.7 2.9 4.2 1.3 versicolor
450		98 6.2 2.9 4.3 1.3 versicolor
451		99 5.1 2.5 3.0 1.1 versicolor
452		100 5.7 2.8 4.1 1.3 versicolor
453		101 6.3 3.3 6.0 2.5 virginica
454		102 5.8 2.7 5.1 1.9 virginica
455		103 7.1 3.0 5.9 2.1 virginica
456		104 6.3 2.9 5.6 1.8 virginica
457		105 6.5 3.0 5.8 2.2 virginica
458		106 7.6 3.0 6.6 2.1 virginica
459		107 4.9 2.5 4.5 1.7 virginica
460		108 7.3 2.9 6.3 1.8 virginica
461		109 6.7 2.5 5.8 1.8 virginica
462		110 7.2 3.6 6.1 2.5 virginica
463		111 6.5 3.2 5.1 2.0 virginica
464		112 6.4 2.7 5.3 1.9 virginica
465		113 6.8 3.0 5.5 2.1 virginica
466		114 5.7 2.5 5.0 2.0 virginica
467		115 5.8 2.8 5.1 2.4 virginica
468		116 6.4 3.2 5.3 2.3 virginica
469		117 6.5 3.0 5.5 1.8 virginica
470		118 7.7 3.8 6.7 2.2 virginica
471		119 7.7 2.6 6.9 2.3 virginica
472		120 6.0 2.2 5.0 1.5 virginica
473		121 6.9 3.2 5.7 2.3 virginica
474		122 5.6 2.8 4.9 2.0 virginica
475		123 7.7 2.8 6.7 2.0 virginica
476		124 6.3 2.7 4.9 1.8 virginica
477		125 6.7 3.3 5.7 2.1 virginica
478		126 7.2 3.2 6.0 1.8 virginica
479		127 6.2 2.8 4.8 1.8 virginica
480		128 6.1 3.0 4.9 1.8 virginica
481		129 6.4 2.8 5.6 2.1 virginica
482		130 7.2 3.0 5.8 1.6 virginica
483		131 7.4 2.8 6.1 1.9 virginica
484		132 7.9 3.8 6.4 2.0 virginica
485		133 6.4 2.8 5.6 2.2 virginica
486		134 6.3 2.8 5.1 1.5 virginica
487		135 6.1 2.6 5.6 1.4 virginica
488		136 7.7 3.0 6.1 2.3 virginica
489		137 6.3 3.4 5.6 2.4 virginica
490		138 6.4 3.1 5.5 1.8 virginica
491		139 6.0 3.0 4.8 1.8 virginica
492		140 6.9 3.1 5.4 2.1 virginica
493		141 6.7 3.1 5.6 2.4 virginica
494		142 6.9 3.1 5.1 2.3 virginica
495		143 5.8 2.7 5.1 1.9 virginica
496		144 6.8 3.2 5.9 2.3 virginica
497		145 6.7 3.3 5.7 2.5 virginica
498		146 6.7 3.0 5.2 2.3 virginica
499		147 6.3 2.5 5.0 1.9 virginica
500		148 6.5 3.0 5.2 2.0 virginica
501		149 6.2 3.4 5.4 2.3 virginica
502		150 5.9 3.0 5.1 1.8 virginica
	352	Sepal.Length Sepal.Width Petal.Length Petal.Width Species
	353	1 5.1 3.5 1.4 0.2 setosa
	354	2 4.9 3.0 1.4 0.2 setosa
	355	3 4.7 3.2 1.3 0.2 setosa
	356	4 4.6 3.1 1.5 0.2 setosa
	357	5 5.0 3.6 1.4 0.2 setosa
	358	6 5.4 3.9 1.7 0.4 setosa
	359	7 4.6 3.4 1.4 0.3 setosa
	360	8 5.0 3.4 1.5 0.2 setosa
	361	9 4.4 2.9 1.4 0.2 setosa
	362	10 4.9 3.1 1.5 0.1 setosa
	363	11 5.4 3.7 1.5 0.2 setosa
	364	12 4.8 3.4 1.6 0.2 setosa
	365	13 4.8 3.0 1.4 0.1 setosa
	366	14 4.3 3.0 1.1 0.1 setosa
	367	15 5.8 4.0 1.2 0.2 setosa
	368	16 5.7 4.4 1.5 0.4 setosa
	369	17 5.4 3.9 1.3 0.4 setosa
	370	18 5.1 3.5 1.4 0.3 setosa
	371	19 5.7 3.8 1.7 0.3 setosa
	372	20 5.1 3.8 1.5 0.3 setosa
	373	21 5.4 3.4 1.7 0.2 setosa
	374	22 5.1 3.7 1.5 0.4 setosa
	375	23 4.6 3.6 1.0 0.2 setosa
	376	24 5.1 3.3 1.7 0.5 setosa
	377	25 4.8 3.4 1.9 0.2 setosa
	378	26 5.0 3.0 1.6 0.2 setosa
	379	27 5.0 3.4 1.6 0.4 setosa
	380	28 5.2 3.5 1.5 0.2 setosa
	381	29 5.2 3.4 1.4 0.2 setosa
	382	30 4.7 3.2 1.6 0.2 setosa
	383	31 4.8 3.1 1.6 0.2 setosa
	384	32 5.4 3.4 1.5 0.4 setosa
	385	33 5.2 4.1 1.5 0.1 setosa
	386	34 5.5 4.2 1.4 0.2 setosa
	387	35 4.9 3.1 1.5 0.2 setosa
	388	36 5.0 3.2 1.2 0.2 setosa
	389	37 5.5 3.5 1.3 0.2 setosa
	390	38 4.9 3.6 1.4 0.1 setosa
	391	39 4.4 3.0 1.3 0.2 setosa
	392	40 5.1 3.4 1.5 0.2 setosa
	393	41 5.0 3.5 1.3 0.3 setosa
	394	42 4.5 2.3 1.3 0.3 setosa
	395	43 4.4 3.2 1.3 0.2 setosa
	396	44 5.0 3.5 1.6 0.6 setosa
	397	45 5.1 3.8 1.9 0.4 setosa
	398	46 4.8 3.0 1.4 0.3 setosa
	399	47 5.1 3.8 1.6 0.2 setosa
	400	48 4.6 3.2 1.4 0.2 setosa
	401	49 5.3 3.7 1.5 0.2 setosa
	402	50 5.0 3.3 1.4 0.2 setosa
	403	51 7.0 3.2 4.7 1.4 versicolor
	404	52 6.4 3.2 4.5 1.5 versicolor
	405	53 6.9 3.1 4.9 1.5 versicolor
	406	54 5.5 2.3 4.0 1.3 versicolor
	407	55 6.5 2.8 4.6 1.5 versicolor
	408	56 5.7 2.8 4.5 1.3 versicolor
	409	57 6.3 3.3 4.7 1.6 versicolor
	410	58 4.9 2.4 3.3 1.0 versicolor
	411	59 6.6 2.9 4.6 1.3 versicolor
	412	60 5.2 2.7 3.9 1.4 versicolor
	413	61 5.0 2.0 3.5 1.0 versicolor
	414	62 5.9 3.0 4.2 1.5 versicolor
	415	63 6.0 2.2 4.0 1.0 versicolor
	416	64 6.1 2.9 4.7 1.4 versicolor
	417	65 5.6 2.9 3.6 1.3 versicolor
	418	66 6.7 3.1 4.4 1.4 versicolor
	419	67 5.6 3.0 4.5 1.5 versicolor
	420	68 5.8 2.7 4.1 1.0 versicolor
	421	69 6.2 2.2 4.5 1.5 versicolor
	422	70 5.6 2.5 3.9 1.1 versicolor
	423	71 5.9 3.2 4.8 1.8 versicolor
	424	72 6.1 2.8 4.0 1.3 versicolor
	425	73 6.3 2.5 4.9 1.5 versicolor
	426	74 6.1 2.8 4.7 1.2 versicolor
	427	75 6.4 2.9 4.3 1.3 versicolor
	428	76 6.6 3.0 4.4 1.4 versicolor
	429	77 6.8 2.8 4.8 1.4 versicolor
	430	78 6.7 3.0 5.0 1.7 versicolor
	431	79 6.0 2.9 4.5 1.5 versicolor
	432	80 5.7 2.6 3.5 1.0 versicolor
	433	81 5.5 2.4 3.8 1.1 versicolor
	434	82 5.5 2.4 3.7 1.0 versicolor
	435	83 5.8 2.7 3.9 1.2 versicolor
	436	84 6.0 2.7 5.1 1.6 versicolor
	437	85 5.4 3.0 4.5 1.5 versicolor
	438	86 6.0 3.4 4.5 1.6 versicolor
	439	87 6.7 3.1 4.7 1.5 versicolor
	440	88 6.3 2.3 4.4 1.3 versicolor
	441	89 5.6 3.0 4.1 1.3 versicolor
	442	90 5.5 2.5 4.0 1.3 versicolor
	443	91 5.5 2.6 4.4 1.2 versicolor
	444	92 6.1 3.0 4.6 1.4 versicolor
	445	93 5.8 2.6 4.0 1.2 versicolor
	446	94 5.0 2.3 3.3 1.0 versicolor
	447	95 5.6 2.7 4.2 1.3 versicolor
	448	96 5.7 3.0 4.2 1.2 versicolor
	449	97 5.7 2.9 4.2 1.3 versicolor
	450	98 6.2 2.9 4.3 1.3 versicolor
	451	99 5.1 2.5 3.0 1.1 versicolor
	452	100 5.7 2.8 4.1 1.3 versicolor
	453	101 6.3 3.3 6.0 2.5 virginica
	454	102 5.8 2.7 5.1 1.9 virginica
	455	103 7.1 3.0 5.9 2.1 virginica
	456	104 6.3 2.9 5.6 1.8 virginica
	457	105 6.5 3.0 5.8 2.2 virginica
	458	106 7.6 3.0 6.6 2.1 virginica
	459	107 4.9 2.5 4.5 1.7 virginica
	460	108 7.3 2.9 6.3 1.8 virginica
	461	109 6.7 2.5 5.8 1.8 virginica
	462	110 7.2 3.6 6.1 2.5 virginica
	463	111 6.5 3.2 5.1 2.0 virginica
	464	112 6.4 2.7 5.3 1.9 virginica
	465	113 6.8 3.0 5.5 2.1 virginica
	466	114 5.7 2.5 5.0 2.0 virginica
	467	115 5.8 2.8 5.1 2.4 virginica
	468	116 6.4 3.2 5.3 2.3 virginica
	469	117 6.5 3.0 5.5 1.8 virginica
	470	118 7.7 3.8 6.7 2.2 virginica
	471	119 7.7 2.6 6.9 2.3 virginica
	472	120 6.0 2.2 5.0 1.5 virginica
	473	121 6.9 3.2 5.7 2.3 virginica
	474	122 5.6 2.8 4.9 2.0 virginica
	475	123 7.7 2.8 6.7 2.0 virginica
	476	124 6.3 2.7 4.9 1.8 virginica
	477	125 6.7 3.3 5.7 2.1 virginica
	478	126 7.2 3.2 6.0 1.8 virginica
	479	127 6.2 2.8 4.8 1.8 virginica
	480	128 6.1 3.0 4.9 1.8 virginica
	481	129 6.4 2.8 5.6 2.1 virginica
	482	130 7.2 3.0 5.8 1.6 virginica
	483	131 7.4 2.8 6.1 1.9 virginica
	484	132 7.9 3.8 6.4 2.0 virginica
	485	133 6.4 2.8 5.6 2.2 virginica
	486	134 6.3 2.8 5.1 1.5 virginica
	487	135 6.1 2.6 5.6 1.4 virginica
	488	136 7.7 3.0 6.1 2.3 virginica
	489	137 6.3 3.4 5.6 2.4 virginica
	490	138 6.4 3.1 5.5 1.8 virginica
	491	139 6.0 3.0 4.8 1.8 virginica
	492	140 6.9 3.1 5.4 2.1 virginica
	493	141 6.7 3.1 5.6 2.4 virginica
	494	142 6.9 3.1 5.1 2.3 virginica
	495	143 5.8 2.7 5.1 1.9 virginica
	496	144 6.8 3.2 5.9 2.3 virginica
	497	145 6.7 3.3 5.7 2.5 virginica
	498	146 6.7 3.0 5.2 2.3 virginica
	499	147 6.3 2.5 5.0 1.9 virginica
	500	148 6.5 3.0 5.2 2.0 virginica
	501	149 6.2 3.4 5.4 2.3 virginica
	502	150 5.9 3.0 5.1 1.8 virginica
503	503	>
504	504	> stopifnot(all.equal(iris.1, iris.2))
505	505	> stopifnot(all.equal(iris.1, iris.3))

541	541	> example.2 <- read.xls(exampleFile, sheet=2) # second worksheet by number
542	542	> example.2
543	543	X D E. F G Factor
544		1 FirstRow 1 NA NA NA Red
545		2 SecondRow 2 1 NA NA Green
546		3 ThirdRow 3 2 1 NA Red
547		4 FourthRow 4 3 2 1 Black
	544	1 FirstRow 1 NA NA NA Red
	545	2 SecondRow 2 1 NA NA Green
	546	3 ThirdRow 3 2 1 NA Red
	547	4 FourthRow 4 3 2 1 Black
548	548	>
549	549	> example.3 <- read.xls(exampleFile, sheet=3, header=FALSE) # third worksheet by number
550	550	> example.3
551	551	V1 V2 V3 V4 V5 V6
552		1 1 2001-01-01 1:01 0.2058182 NA A
553		2 2 2002-02-02 2:02 0.2910708 NA B
554		3 3 2003-03-03 3:03 0.3564875 -0.84147098 C
	552	1 1 2001-01-01 1:01 0.2058182 NA A
	553	2 2 2002-02-02 2:02 0.2910708 NA B
	554	3 3 2003-03-03 3:03 0.3564875 -0.84147098 C
555	555	4 4 2004-04-04 4:04 0.4116363 0.70807342
556		5 5 2005-05-05 5:05 0.4602234 0.50136797 A
557		6 6 2006-06-06 6:06 NA 0.25136984 B
558		7 7 2007-07-07 7:07 0.5445436 0.06318679 B
559		8 8 2008-08-08 8:08 0.5821416 NA C
560		9 9 2009-09-09 9:09 0.6174545 0.00000000 A
561		10 10 2010-10-10 10:10 0.6508541 0.00000000 A
	556	5 5 2005-05-05 5:05 0.4602234 0.50136797 A
	557	6 6 2006-06-06 6:06 NA 0.25136984 B
	558	7 7 2007-07-07 7:07 0.5445436 0.06318679 B
	559	8 8 2008-08-08 8:08 0.5821416 NA C
	560	9 9 2009-09-09 9:09 0.6174545 0.00000000 A
	561	10 10 2010-10-10 10:10 0.6508541 0.00000000 A
562	562	>
563	563	> example.4 <- read.xls(exampleFile, sheet=3, header=FALSE) # third worksheet by number
564	564	> example.4
565	565	V1 V2 V3 V4 V5 V6
566		1 1 2001-01-01 1:01 0.2058182 NA A
567		2 2 2002-02-02 2:02 0.2910708 NA B
568		3 3 2003-03-03 3:03 0.3564875 -0.84147098 C
	566	1 1 2001-01-01 1:01 0.2058182 NA A
	567	2 2 2002-02-02 2:02 0.2910708 NA B
	568	3 3 2003-03-03 3:03 0.3564875 -0.84147098 C
569	569	4 4 2004-04-04 4:04 0.4116363 0.70807342
570		5 5 2005-05-05 5:05 0.4602234 0.50136797 A
571		6 6 2006-06-06 6:06 NA 0.25136984 B
572		7 7 2007-07-07 7:07 0.5445436 0.06318679 B
573		8 8 2008-08-08 8:08 0.5821416 NA C
574		9 9 2009-09-09 9:09 0.6174545 0.00000000 A
575		10 10 2010-10-10 10:10 0.6508541 0.00000000 A
	570	5 5 2005-05-05 5:05 0.4602234 0.50136797 A
	571	6 6 2006-06-06 6:06 NA 0.25136984 B
	572	7 7 2007-07-07 7:07 0.5445436 0.06318679 B
	573	8 8 2008-08-08 8:08 0.5821416 NA C
	574	9 9 2009-09-09 9:09 0.6174545 0.00000000 A
	575	10 10 2010-10-10 10:10 0.6508541 0.00000000 A
576	576	>
577	577	> if( 'XLSX' %in% xlsFormats() )
578	578	+ {

604	604	6 6 36 216
605	605	7 7 49 343
606	606	X D E. F G Factor
607		1 FirstRow 1 NA NA NA Red
608		2 SecondRow 2 1 NA NA Green
609		3 ThirdRow 3 2 1 NA Red
610		4 FourthRow 4 3 2 1 Black
	607	1 FirstRow 1 NA NA NA Red
	608	2 SecondRow 2 1 NA NA Green
	609	3 ThirdRow 3 2 1 NA Red
	610	4 FourthRow 4 3 2 1 Black
611	611	V1 V2 V3 V4 V5 V6
612		1 1 2001-01-01 1:01 0.2058182 NA A
613		2 2 2002-02-02 2:02 0.2910708 NA B
614		3 3 2003-03-03 3:03 0.3564875 -0.84147098 C
	612	1 1 2001-01-01 1:01 0.2058182 NA A
	613	2 2 2002-02-02 2:02 0.2910708 NA B
	614	3 3 2003-03-03 3:03 0.3564875 -0.84147098 C
615	615	4 4 2004-04-04 4:04 0.4116363 0.70807342
616		5 5 2005-05-05 5:05 0.4602234 0.50136797 A
617		6 6 2006-06-06 6:06 NA 0.25136984 B
618		7 7 2007-07-07 7:07 0.5445436 0.06318679 B
619		8 8 2008-08-08 8:08 0.5821416 NA C
620		9 9 2009-09-09 9:09 0.6174545 0.00000000 A
621		10 10 2010-10-10 10:10 0.6508541 0.00000000 A
	616	5 5 2005-05-05 5:05 0.4602234 0.50136797 A
	617	6 6 2006-06-06 6:06 NA 0.25136984 B
	618	7 7 2007-07-07 7:07 0.5445436 0.06318679 B
	619	8 8 2008-08-08 8:08 0.5821416 NA C
	620	9 9 2009-09-09 9:09 0.6174545 0.00000000 A
	621	10 10 2010-10-10 10:10 0.6508541 0.00000000 A
622	622	V1 V2 V3 V4 V5 V6
623		1 1 2001-01-01 1:01 0.2058182 NA A
624		2 2 2002-02-02 2:02 0.2910708 NA B
625		3 3 2003-03-03 3:03 0.3564875 -0.84147098 C
	623	1 1 2001-01-01 1:01 0.2058182 NA A
	624	2 2 2002-02-02 2:02 0.2910708 NA B
	625	3 3 2003-03-03 3:03 0.3564875 -0.84147098 C
626	626	4 4 2004-04-04 4:04 0.4116363 0.70807342
627		5 5 2005-05-05 5:05 0.4602234 0.50136797 A
628		6 6 2006-06-06 6:06 NA 0.25136984 B
629		7 7 2007-07-07 7:07 0.5445436 0.06318679 B
630		8 8 2008-08-08 8:08 0.5821416 NA C
631		9 9 2009-09-09 9:09 0.6174545 0.00000000 A
632		10 10 2010-10-10 10:10 0.6508541 0.00000000 A
	627	5 5 2005-05-05 5:05 0.4602234 0.50136797 A
	628	6 6 2006-06-06 6:06 NA 0.25136984 B
	629	7 7 2007-07-07 7:07 0.5445436 0.06318679 B
	630	8 8 2008-08-08 8:08 0.5821416 NA C
	631	9 9 2009-09-09 9:09 0.6174545 0.00000000 A
	632	10 10 2010-10-10 10:10 0.6508541 0.00000000 A
633	633	X D E. F G Factor
634		1 FirstRow 1 NA NA NA Red
635		2 SecondRow 2 1 NA NA Green
636		3 ThirdRow 3 2 1 NA Red
637		4 FourthRow 4 3 2 1 Black
	634	1 FirstRow 1 NA NA NA Red
	635	2 SecondRow 2 1 NA NA Green
	636	3 ThirdRow 3 2 1 NA Red
	637	4 FourthRow 4 3 2 1 Black
638	638	X X.1 D E. F G Factor
639		1 NA FirstRow 1 NA NA NA Red
640		2 NA SecondRow 2 1 NA NA Green
641		3 NA ThirdRow 3 2 1 NA Red
642		4 NA FourthRow 4 3 2 1 Black
	639	1 NA FirstRow 1 NA NA NA Red
	640	2 NA SecondRow 2 1 NA NA Green
	641	3 NA ThirdRow 3 2 1 NA Red
	642	4 NA FourthRow 4 3 2 1 Black
643	643	>
644	644	>
645	645	> ## Check handling of skip.blank.lines=FALSE

647	647	> example.skip <- read.xls(exampleFile, sheet=2, blank.lines.skip=FALSE)
648	648	> example.skip
649	649	X D E. F G Factor
650		1 FirstRow 1 NA NA NA Red
651		2 SecondRow 2 1 NA NA Green
	650	1 FirstRow 1 NA NA NA Red
	651	2 SecondRow 2 1 NA NA Green
652	652	3 NA NA NA NA
653		4 ThirdRow 3 2 1 NA Red
654		5 FourthRow 4 3 2 1 Black
	653	4 ThirdRow 3 2 1 NA Red
	654	5 FourthRow 4 3 2 1 Black
655	655	>
656	656	> if( 'XLSX' %in% xlsFormats() )
657	657	+ {

659	659	+ example.x.skip
660	660	+ }
661	661	X D E. F G Factor
662		1 FirstRow 1 NA NA NA Red
663		2 SecondRow 2 1 NA NA Green
	662	1 FirstRow 1 NA NA NA Red
	663	2 SecondRow 2 1 NA NA Green
664	664	3 NA NA NA NA
665		4 ThirdRow 3 2 1 NA Red
666		5 FourthRow 4 3 2 1 Black
667		>
668		>
669		>
670		>
	665	4 ThirdRow 3 2 1 NA Red
	666	5 FourthRow 4 3 2 1 Black
	667	>
	668	>
	669	> ## Check handing of fileEncoding for latin-1 characters
	670	>
	671	> latin1File <- file.path(.path.package('gdata'),'xls', 'latin-1.xls')
	672	> latin1FileX <- file.path(.path.package('gdata'),'xls', 'latin-1.xlsx')
	673	>
	674	> example.latin1 <- read.xls(latin1File, fileEncoding='latin1')
	675	>
	676	> if( 'XLSX' %in% xlsFormats() )
	677	+ {
	678	+ example.latin1.x <- read.xls(latin1FileX, fileEncoding='latin1')
	679	+ }
671	680	>
672	681	>
673	682	>
674	683	> proc.time()
675	684	user system elapsed
676		3.259 0.383 3.748
	685	3.564 0.436 4.186