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/dports/devel/R-cran-data.table/data.table/
H A DNAMESPACE10 export(as.data.table,is.data.table,test.data.table)
66 S3method(as.data.table, data.table)
67 S3method(as.data.table, data.frame)
79 S3method(as.data.table, table)
86 # fix in R in Sep 2019 (#3948) makes c|rbind S3 dispatch work; see FAQ 2.24.
89 S3method(rbind, data.table)
94 # # > cbind.data.table rbind.data.table
97 # export(rbind.data.table)
98 # # A revdep using rbind.data.frame() directly before (which data.table changed in base) should ch…
102 export(.rbind.data.table) # continue to export for now because it has been exported in the past so …
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/dports/devel/R-cran-data.table/data.table/man/
H A Drbindlist.Rd3 \alias{rbind.data.table}
4 \alias{rbind}
5 \title{ Makes one data.table from a list of many }
7 Same as \code{do.call("rbind", l)} on \code{data.frame}s, but much faster.
20 …data.table}, \code{data.frame} or \code{list}, including \code{NULL} (skipped) or an empty object …
31 \seealso{ \code{\link{data.table}}, \code{\link{split.data.table}} }
34 DT1 = data.table(A=1:3,B=letters[1:3])
35 DT2 = data.table(A=4:5,B=letters[4:5])
40 DT1 = data.table(A=1:3,B=letters[1:3])
41 DT2 = data.table(B=letters[4:5],A=4:5)
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/dports/textproc/R-cran-rio/rio/man/
H A Dimport_list.Rd5 \title{Import list of data frames}
7 import_list(file, setclass, which, rbind = FALSE,
13 …data.frame}. Allowed values include \dQuote{tbl_df}, \dQuote{tbl}, or \dQuote{tibble} (if using dp…
17 \item{rbind}{A logical indicating whether to pass the import list of data frames through \code{\lin…
19 \item{rbind_label}{If \code{rbind = TRUE}, a character string specifying the name of a column to ad…
21 \item{rbind_fill}{If \code{rbind = TRUE}, a logical indicating whether to set the \code{fill = TRUE…
26 …rbind=FALSE} (the default), a list of a data frames. Otherwise, that list is passed to \code{\link…
29 Use \code{\link{import}} to import a list of data frames from a vector of file names or from a mult…
43 # import and rbind all worksheets
44 mtcars2 <- import_list("mtcars.xlsx", rbind = TRUE)
/dports/finance/R-cran-AER/AER/tests/
H A DCh-Microeconometrics.R22 data("SwissLabor")
61 av <- data.frame(rbind(swiss = av, foreign = av),
84 table(true = SwissLabor$participation,
91 tab <- table(true = SwissLabor$participation,
165 table(I(MurderRates$executions > 0), MurderRates$southern)
212 round(sqrt(rbind(diag(vcov(rd_pois)),
231 plot(table(RecreationDemand$trips), ylab = "")
237 rbind(obs = table(RecreationDemand$trips)[1:10], exp = round(
283 data("Affairs")
334 table(Actual = SwissLabor$participation, Predicted =
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/dports/finance/R-cran-AER/AER/demo/
H A DCh-Microeconometrics.R22 data("SwissLabor")
61 av <- data.frame(rbind(swiss = av, foreign = av),
84 table(true = SwissLabor$participation,
91 tab <- table(true = SwissLabor$participation,
165 table(I(MurderRates$executions > 0), MurderRates$southern)
212 round(sqrt(rbind(diag(vcov(rd_pois)),
231 plot(table(RecreationDemand$trips), ylab = "")
237 rbind(obs = table(RecreationDemand$trips)[1:10], exp = round(
283 data("Affairs")
334 table(Actual = SwissLabor$participation, Predicted =
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/dports/textproc/py-agate/agate-1.6.3/docs/cookbook/
H A Dr.rst14 selected <- data[c("last_name", "first_name", "age")]
15 excluded <- data[!c("last_name", "first_name", "age")]
21 selected = table.select(['last_name', 'first_name', 'age'])
22 excluded = table.exclude(['last_name', 'first_name', 'age'])
33 newdata <- subset(data, age >= 20 | age < 10)
39 new_table = table.where(lambda row: row['age'] >= 20 or row['age'] < 10)
75 rbind chapter
78 Agate's :meth:`.Table.merge` is the equivalent of R's :code:`rbind`.
84 merged <- rbind(first_year, second_year)
/dports/math/R-cran-sp/sp/man/
H A DSpatialLinesDataFrame-class.Rd4 \alias{coerce,SpatialLinesDataFrame,data.frame-method}
6 \alias{rbind.SpatialLinesDataFrame}
13 \description{ this class holds data consisting of (sets of lines), where each
14 set of lines relates to an attribute row in a data.frame }
20 \item{\code{data}:}{Object of class \link{data.frame} containing the attribute table }
40 \item{rbind}{\code{signature(object = "SpatialLinesDataFrame")}:
41 rbind-like method}
45 \code{rbind} for \code{SpatialLinesDataFrame} is only possible for
46 objects with unique IDs. If you want to \code{rbind} objects
H A DSpatialPolygonsDataFrame-class.Rd5 \alias{as.data.frame.SpatialPolygonsDataFrame}
6 \alias{coerce,SpatialPolygonsDataFrame,data.frame-method}
9 \alias{rbind.SpatialPolygonsDataFrame}
20 \item{\code{data}:}{Object of class \code{"data.frame"}; attribute table }
35 \item{rbind}{\code{signature(object = "SpatialPolygonsDataFrame")}:
36 rbind-like method, see notes below}
40 …e data frame row names against the Polygons ID slots. They must then agree with each other, and be…
42 If you want to \code{rbind} objects with
68 data=data.frame(x=x, y=y, z=z, row.names=row.names(polys)))
/dports/science/R-cran-e1071/e1071/inst/doc/
H A Dsvmdoc.R8 data(Glass, package="mlbench")
29 rpart.model <- rpart(Type ~ ., data = trainset)
37 table(pred = svm.pred, true = testset[,10])
40 table(pred = rpart.pred, true = testset[,10])
62 tab <- classAgreement(table(svm.pred, testset[,10]))
69 tab <- classAgreement(table(rpart.pred, testset[,10]))
74 x <- rbind(summary(sv.acc), summary(sv.kap), summary(rp.acc), summary(rp.kap))
88 data(Ozone, package="mlbench")
102 rpart.model <- rpart(V4 ~ ., data = trainset)
126 rpart.model <- rpart(V4 ~ ., data = trainset)
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/dports/devel/R-cran-sfsmisc/sfsmisc/tests/
H A DdDA.R4 data(iris)
13 table(diagDA(m.iris, cl.true, m.iris), cl.true)
14 table(diagDA(m.iris, cl.true, m.iris, pool=FALSE), cl.true)
17 data(iris3)
18 train <- rbind(iris3[1:25,,1], iris3[1:25,,2], iris3[1:25,,3])
19 test <- rbind(iris3[26:50,,1], iris3[26:50,,2], iris3[26:50,,3])
23 table(pcl, cl)## 0 + 1 + 2 misclassified
H A DdDA.Rout.save21 > data(iris)
25 > m.iris <- data.matrix(iris[, 1:4])
30 > table(diagDA(m.iris, cl.true, m.iris), cl.true)
36 > table(diagDA(m.iris, cl.true, m.iris, pool=FALSE), cl.true)
44 > data(iris3)
45 > train <- rbind(iris3[1:25,,1], iris3[1:25,,2], iris3[1:25,,3])
46 > test <- rbind(iris3[26:50,,1], iris3[26:50,,2], iris3[26:50,,3])
50 > table(pcl, cl)## 0 + 1 + 2 misclassified
/dports/math/R-cran-Amelia/Amelia/inst/doc/
H A Dusing-amelia.R8 data(freetrade)
15 data = freetrade))
50 table(a.out$imputations[[3]]$polity)
55 table(a.out1$imputations[[3]]$polity)
58 table(a.out1$imputations[[3]]$signed)
63 table(a.out2$imputations[[3]]$signed)
152 z5$zelig(tariff ~ polity + pop + gdp.pc + year + country, data = freetrade) globalVar
159 z5$zelig(tariff ~ polity + pop + gdp.pc + year + country, data = freetrade) globalVar
172 z5_imp$zelig(tariff ~ polity + pop + gdp.pc + year + country, data = a.out) globalVar
180 b.out <- rbind(b.out, ols.out$coef)
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/dports/math/R-cran-prodlim/prodlim/R/
H A Dredist.R60 contr <- rbind(fractions[[i]],format(mass[[i]],digits=4,nsmall=4))
62 contr <- rbind(t(contr),c("sum",format(sum(mass[[i]]),digits=4,nsmall=4)))
70 …table <- summary(f <- prodlim(Hist(time,status)~1,data=data.frame(time,status)),times=c(0,time),pe… functionVar
72 tab <- table$table[,c("time","n.risk","n.event","n.lost","surv")]
74 out <- list(fit=f,table=tab) nameattr
/dports/math/R-cran-lava/lava/R/
H A Ddiagtest.R39 if (!is.table(table) & (is.matrix(table) || is.data.frame(table))) {
52 if (!is.table(table) && (is.matrix(table) || is.data.frame(table))) {
53 table <- base::table(table[,c(1,2),drop=FALSE])
56 if (!is.table(table) || nrow(table)!=2 || ncol(table)!=2) stop("2x2 table expected")
80 coefmat <- rbind(Prevalence=p1,
91 res <- list(table=table, prop.table=table/sum(table), nameattr
99 table <- round(M$P*nrow(M$data))
102 table <- base::table(table)
147 rbind(expit(x[seq(nrow(x)-1),,drop=FALSE]),
154 rbind(sin(x[seq(nrow(x)-1),,drop=FALSE])^2,
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/dports/math/R-cran-Zelig/Zelig/R/
H A Dinterface.R4 rbind(
57 new_obj$data <- cbind(1, obj$model)
58 names(new_obj$data)[1] <- "by"
60 new_obj$data <- tbl_df(new_obj$data)
67 new_obj$zelig.out <- new_obj$data %>%
183 comb <- rbind(comb, comb_temp)
187 comb <- rbind(comb, comb_temp)
191 comb <- rbind(comb, comb_temp)
195 comb <- rbind(comb, comb_temp)
264 comb <- rbind(comb, comb_temp)
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/dports/math/R-cran-memisc/memisc/vignettes/
H A Dftable-matrix.Rmd27 tab.Survived <- xtabs(Freq~Survived,data=Titanic)
44 We can even add a simple table of counts:
112 rbind(
121 rbind(
141 rbind(
150 It is also possible to combine `rbind` and `cbind`:
152 tab.Age <- xtabs(Freq~Age,data=Titanic)
153 tab.Sex <- xtabs(Freq~Sex,data=Titanic)
154 tab.Class <- xtabs(Freq~Class,data=Titanic)
158 rbind(
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/dports/math/R-cran-memisc/memisc/inst/doc/
H A Dftable-matrix.Rmd27 tab.Survived <- xtabs(Freq~Survived,data=Titanic)
44 We can even add a simple table of counts:
112 rbind(
121 rbind(
141 rbind(
150 It is also possible to combine `rbind` and `cbind`:
152 tab.Age <- xtabs(Freq~Age,data=Titanic)
153 tab.Sex <- xtabs(Freq~Sex,data=Titanic)
154 tab.Class <- xtabs(Freq~Class,data=Titanic)
158 rbind(
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/dports/biology/p5-transdecoder/TransDecoder-TransDecoder-v5.4.0/util/misc/
H A Drpart_scores.Rscript22 data = read.table(data_file, header=T, com='', row.names=1)
24 rand_idx = grep("rand", row.names(data))
26 rand_data = data[rand_idx,]
27 reg_data = data[-rand_idx,]
33 reg_data = data.frame(reg_data, myvar='YES')
35 target_data = rbind(rand_data, reg_data)
38 write.table(target_data, 'adj.data', quote=F, sep="\t")
58 len_normalize_adj = function(data) {
60 data = data[data$seq_length <= max_length,]
61 data = data[rev(order(data$seq_length)),]
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/dports/math/R-cran-raster/raster/R/
H A Dcrosstab.R30 res <- do.call(table, c(res, useNA='ifany'))
39 d <- do.call(table, c(d, useNA='ifany'))
41 res <- rbind(res, d)
73 res <- stats::xtabs(f, data=res, addNA=useNA) functionVar
92 …res <- table(first=round(getValues(x), digits=digits), second=round(getValues(y), digits=digits), …
99 …d <- table( round(getValuesBlock(x, row=tr$row[i], nrows=tr$nrows[i]), digits=digits), round(getVa…
109 res = rbind(res, cbind(first, second, count))
113 res <- stats::xtabs(count~first+second, data=res) functionVar
/dports/math/R/R-4.1.2/src/library/stats/R/
H A Dftable.R28 x <- table(x, exclude = exclude)
34 x <- table(..., exclude = exclude)
93 tt <- if(is.data.frame(data)) terms(formula, data=data)
110 data <- as.table(data)
133 m$data <- as.data.frame(data)
135 if(!is.null(data) && is.environment(data)) {
217 cbind(rbind(matrix("", nrow = length(xcv), ncol = length(xrv)),
225 cbind(rbind(matrix("", nrow = length(xcv)-1, ncol = length(xrv)),
242 mat <- cbind(rbind(cbind(matrix("", nrow = l.xcv-1, ncol = l.xrv-1),
251 DATA <- rbind(if(length(xcv)) t(makeLabels(xcv)),
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/dports/math/libRmath/R-4.1.1/src/library/stats/R/
H A Dftable.R28 x <- table(x, exclude = exclude)
34 x <- table(..., exclude = exclude)
93 tt <- if(is.data.frame(data)) terms(formula, data=data)
110 data <- as.table(data)
133 m$data <- as.data.frame(data)
135 if(!is.null(data) && is.environment(data)) {
217 cbind(rbind(matrix("", nrow = length(xcv), ncol = length(xrv)),
225 cbind(rbind(matrix("", nrow = length(xcv)-1, ncol = length(xrv)),
242 mat <- cbind(rbind(cbind(matrix("", nrow = l.xcv-1, ncol = l.xrv-1),
251 DATA <- rbind(if(length(xcv)) t(makeLabels(xcv)),
[all …]
/dports/math/R-cran-memisc/memisc/
H A DNAMESPACE315 S3method(rbind,data.set)
337 S3method(as.data.frame,percentage.table)
338 S3method(as.data.frame,xpercentage.table)
341 S3method(rbind,ftable)
343 S3method(rbind,ftable_matrix)
469 importFrom(data.table,as.data.table)
470 S3method(as.data.table,data.set)
471 # export(as.data.table.data.set)
472 # exportMethods(as.data.table)
493 S3method(as.data.frame,means.table)
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/dports/devel/R-cran-vcd/vcd/man/
H A Dstructable.Rd10 \alias{rbind.structable}
17 \alias{as.table.structable}
21 high-dimensional contingency table constructed by recursive
25 \method{structable}{formula}(formula, data,
32 \item{data}{a data frame, list or environment containing the variables
36 Ignored if \code{data} is a contingency table.}
38 the data contain \code{NA}s.
39 Ignored if \code{data} is a contingency table}
43 \code{"table"} or \code{"ftable"}.}
70 \code{\link{rbind}}, \code{\link{length}}, \code{\link{dim}}, and
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/dports/math/R-cran-VGAM/VGAM/man/
H A Dolym.Rd4 \docType{data}
13 data(olym08)
14 data(olym12)
17 A data frame with 87 or 85 observations on the following 6 variables.
36 % This is a simple two-way contingency table of counts.
67 barplot(rbind(gold, silver, bronze),
75 barplot(rbind(gold, silver, bronze),
/dports/math/R-cran-car/car/R/
H A Dscatter3d.R25 scatter3d.formula <- function(formula, data, subset, radius, xlab, ylab, zlab, id=FALSE, ...){ argument
29 if (is.matrix(eval(m$data, sys.frame(sys.parent()))))
30 m$data <- as.data.frame(data)
106 counts <- table(groups)
270 … rgl::rgl.lines(as.vector(rbind(x,x)), as.vector(rbind(y,fitted)), as.vector(rbind(z,z)),
276 zz <- as.vector(rbind(z, z, z, z))
310 … rgl::rgl.lines(as.vector(rbind(xx,xx)), as.vector(rbind(yy,fitted)), as.vector(rbind(zz,zz)),
349 … rgl::rgl.lines(as.vector(rbind(xx,xx)), as.vector(rbind(yy,fitted)), as.vector(rbind(zz,zz)),
424 counts <- table(groups)
519 v <- rbind(v, rep(1,ncol(v)))
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