slicing - which dataframe in r




將三列數據幀重塑為矩陣(“長”到“寬”格式) (2)

我有一個像這樣的數據data.frame

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

我想要矩陣形式的這個,所以我可以把它提供給heatmap來做一個情節。 結果應該如下所示:

    a    b    c
x   1    2    3
y   3    3    2

我已經嘗試從重塑包中cast ,並且我已經嘗試編寫一個手動函數來執行此操作,但我似乎無法正確完成。


問題已經有幾年了,但也許有些人仍然對其他答案感興趣。

如果你不想加載任何包,你可以使用這個函數:

#' 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)

}

怎麼運行的:

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

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)

您也可以使用reshape ,如下所示: 通過列名稱將表格轉換為矩陣 ,但之後您必須執行一些操作以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

Matrix包中也有sparseMatrix ,如下所示: R - 按列名將BIG表轉換為矩陣

> 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

也可以使用plyr庫中的daply函數,如下所示: https://.com/a/7020101/210673 : plyr

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

dcast的dcast也可以工作,如下所示: 為一列中的值 dcast整形數據 ,但是您會得到一個包含x值列的data.frame。

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

同樣,從“tidyr” spread也可以用於這種轉變:

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






reshape