將三列數據幀重塑爲矩陣（「長」到「寬」格式）

Question

我有一個data.frame，看起來像這樣。

x a 1 
x b 2 
x c 3 
y a 3 
y b 3 
y c 2 

我想這個矩陣形式，所以我可以餵它到熱圖做一個情節。結果應該是這樣的：

a b c 
x 1 2 3 
y 3 3 2 

我試圖從重塑包cast和我試圖寫一個手動功能做到這一點，但我似乎並沒有能夠得到它的權利。

Answer 1

有很多方法可以做到這一點。這個答案從我最喜歡的方式開始，但也收集各種方式從答案到散佈在這個網站周圍的類似問題。

tmp <- data.frame(x=gl(2,3, labels=letters[24:25]), 
        y=gl(3,1,6, labels=letters[1:3]), 
        z=c(1,2,3,3,3,2)) 

使用reshape2：

library(reshape2) 
acast(tmp, x~y, value.var="z") 

使用矩陣索引：

with(tmp, { 
    out <- matrix(nrow=nlevels(x), ncol=nlevels(y), 
       dimnames=list(levels(x), levels(y))) 
    out[cbind(x, y)] <- z 
    out 
}) 

使用xtabs：

xtabs(z~x+y, data=tmp) 

您還可以使用reshape，作爲她的建議e：Convert table into matrix by column names，儘管之後你必須做一些小操作來刪除多餘的列並獲取正確的名稱（未顯示）。

> reshape(tmp, idvar="x", timevar="y", direction="wide") 
    x z.a z.b z.c 
1 x 1 2 3 
4 y 3 3 2 

還有sparseMatrix的Matrix包內，如下所示：R - convert BIG table into matrix by column names

> with(tmp, sparseMatrix(i = as.numeric(x), j=as.numeric(y), x=z, 
+      dimnames=list(levels(x), levels(y)))) 
2 x 3 sparse Matrix of class "dgCMatrix" 
    a b c 
x 1 2 3 
y 3 3 2 

從plyr庫daply功能也可以使用，在這裏：https://stackoverflow.com/a/7020101/210673

> library(plyr) 
> daply(tmp, .(x, y), function(x) x$z) 
    y 
x a b c 
    x 1 2 3 
    y 3 3 2 

來自reshape2的dcast也適用，如下所示：Reshape data for values in one column，但是您會得到一個data.frame，其值爲x。

> dcast(tmp, x~y, value.var="z") 
    x a b c 
1 x 1 2 3 
2 y 3 3 2 

同樣，spread從「tidyr」也將這樣的改造工作：

library(tidyr) 
spread(tmp, y, z) 
# x a b c 
# 1 x 1 2 3 
# 2 y 3 3 2 

Answer 2

的問題是，一些歲，但也許有些人還是感興趣的備選答案。

如果你不想加載任何包，您可以使用此功能：

#' Converts three columns of a data.frame into a matrix -- e.g. to plot 
#' the data via image() later on. Two of the columns form the row and 
#' col dimensions of the matrix. The third column provides values for 
#' the matrix. 
#' 
#' @param data data.frame: input data 
#' @param rowtitle string: row-dimension; name of the column in data, which distinct values should be used as row names in the output matrix 
#' @param coltitle string: col-dimension; name of the column in data, which distinct values should be used as column names in the output matrix 
#' @param datatitle string: name of the column in data, which values should be filled into the output matrix 
#' @param rowdecreasing logical: should the row names be in ascending (FALSE) or in descending (TRUE) order? 
#' @param coldecreasing logical: should the col names be in ascending (FALSE) or in descending (TRUE) order? 
#' @param default_value numeric: default value of matrix entries if no value exists in data.frame for the entries 
#' @return matrix: matrix containing values of data[[datatitle]] with rownames data[[rowtitle]] and colnames data[coltitle] 
#' @author Daniel Neumann 
#' @date 2017-08-29 
data.frame2matrix = function(data, rowtitle, coltitle, datatitle, 
          rowdecreasing = FALSE, coldecreasing = FALSE, 
          default_value = NA) { 

    # check, whether titles exist as columns names in the data.frame data 
    if ((!(rowtitle%in%names(data))) 
     || (!(coltitle%in%names(data))) 
     || (!(datatitle%in%names(data)))) { 
    stop('data.frame2matrix: bad row-, col-, or datatitle.') 
    } 

    # get number of rows in data 
    ndata = dim(data)[1] 

    # extract rownames and colnames for the matrix from the data.frame 
    rownames = sort(unique(data[[rowtitle]]), decreasing = rowdecreasing) 
    nrows = length(rownames) 
    colnames = sort(unique(data[[coltitle]]), decreasing = coldecreasing) 
    ncols = length(colnames) 

    # initialize the matrix 
    out_matrix = matrix(NA, 
         nrow = nrows, ncol = ncols, 
         dimnames=list(rownames, colnames)) 

    # iterate rows of data 
    for (i1 in 1:ndata) { 
    # get matrix-row and matrix-column indices for the current data-row 
    iR = which(rownames==data[[rowtitle]][i1]) 
    iC = which(colnames==data[[coltitle]][i1]) 

    # throw an error if the matrix entry (iR,iC) is already filled. 
    if (!is.na(out_matrix[iR, iC])) stop('data.frame2matrix: double entry in data.frame') 
    out_matrix[iR, iC] = data[[datatitle]][i1] 
    } 

    # set empty matrix entries to the default value 
    out_matrix[is.na(out_matrix)] = default_value 

    # return matrix 
    return(out_matrix) 

} 

工作原理：

myData = as.data.frame(list('dim1'=c('x', 'x', 'x', 'y','y','y'), 
          'dim2'=c('a','b','c','a','b','c'), 
          'values'=c(1,2,3,3,3,2))) 

myMatrix = data.frame2matrix(myData, 'dim1', 'dim2', 'values') 

myMatrix 
> a b c 
> x 1 2 3 
> y 3 3 2