重塑具有缺失值和多个感兴趣变量的大型矩阵

Question

我需要将大型数据集重组为特定格式以供进一步分析。现在数据是长格式的，每个点都有多个记录。我需要重塑数据，使每个点都有一条记录，但它会添加许多新的时间特定数据列。我看过以前类似的 posts 但我需要最终将几个当前变量转换为列，但我找不到这样的例子。有没有办法在一次重塑中完成这个，或者我必须做几次然后将新列连接在一起？在我 post 这个例子之前的另一个问题是并不是所有的点在每个时间步都被采样，所以我需要这些值显示为 NA。例如，（见下面的数据）SitePoint A1 在 2012 年根本没有被采样，SitePoint A10 在 2012 年的第一轮中没有被采样，但是 K83 被采样了九次。

mydatain <- structure(list(SitePoint = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 6L, 6L), .Label = c("A1", "A10", "K145", "K83", "T15", 
"T213"), class = "factor"), Year_Rotation = structure(c(1L, 2L, 
3L, 4L, 5L, 6L, 1L, 2L, 3L, 4L, 5L, 6L, 8L, 9L, 1L, 2L, 4L, 5L, 
6L, 7L, 8L, 9L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 1L, 2L, 3L, 
4L, 5L, 6L, 7L, 8L, 9L, 1L, 7L), .Label = c("2010_1", "2010_2", 
"2010_3", "2011_1", "2011_2", "2011_3", "2012_1", "2012_2", "2012_3"
), class = "factor"), MR_Fire = structure(c(5L, 6L, 6L, 2L, 9L, 
9L, 5L, 6L, 6L, 2L, 9L, 9L, 7L, 8L, 16L, 17L, 21L, 22L, 23L, 
25L, 3L, 4L, 10L, 11L, 12L, 13L, 14L, 15L, 18L, 19L, 20L, 1L, 
2L, 2L, 5L, 6L, 6L, 11L, 11L, 12L, 7L, 24L), .Label = c("0", 
"1", "10", "11", "12", "13", "14", "15", "2", "23", "24", "25", 
"35", "36", "37", "39", "40", "47", "48", "49", "51", "52", "53", 
"8", "9"), class = "factor"), fire_seas = structure(c(2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 
1L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 1L, 3L), .Label = c("dry", "fire", "wet"
), class = "factor"), OptTSF = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 
1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 
0L, 1L, 1L)), .Names = c("SitePoint", "Year_Rotation", "MR_Fire", 
"fire_seas", "OptTSF"), row.names = c(31L, 32L, 33L, 34L, 35L, 
36L, 67L, 68L, 69L, 70L, 71L, 72L, 73L, 74L, 10543L, 10544L, 
10545L, 10546L, 10547L, 10548L, 10549L, 10550L, 14988L, 14989L, 
14990L, 14991L, 14992L, 14993L, 14994L, 14995L, 14996L, 17370L, 
17371L, 17372L, 17373L, 17374L, 17375L, 17376L, 17377L, 17378L, 
19353L, 19354L), class = "data.frame")

最终我需要这样的东西：

myfinal <- structure(list(SitePoint = structure(1:6, .Label = c("A1", "A10", 
"K145", "K83", "T15", "T213"), class = "factor"), MR_Fire_2010_1 = c(12L, 
12L, 39L, 23L, 0L, 14L), MR_Fire_2010_2 = c(13L, 13L, 40L, 24L, 
1L, NA), MR_Fire_2010_3 = c(13L, 13L, NA, 25L, 1L, NA), MR_Fire_2011_1 = c(1L, 
1L, 51L, 35L, 12L, NA), MR_Fire_2011_2 = c(2L, 2L, 52L, 36L, 
13L, NA), MR_Fire_2011_3 = c(2L, 2L, 53L, 37L, 13L, NA), MR_Fire_2012_1 = c(NA, 
NA, 9L, 47L, 24L, 8L), MR_Fire_2012_2 = c(NA, 14L, 10L, 48L, 
24L, NA), MR_Fire_2012_3 = c(NA, 15L, 11L, 49L, 25L, NA), season_2010_1 = structure(c(2L, 
2L, 1L, 2L, 2L, 1L), .Label = c("dry", "fire"), class = "factor"), 
    season_2010_2 = structure(c(2L, 2L, 1L, 2L, 2L, NA), .Label = c("dry", 
    "fire"), class = "factor"), season_2010_3 = structure(c(1L, 
    1L, NA, 1L, 1L, NA), .Label = "fire", class = "factor"), 
    season_2011_1 = structure(c(2L, 2L, 1L, 2L, 2L, NA), .Label = c("dry", 
    "fire"), class = "factor"), season_2011_2 = structure(c(2L, 
    2L, 1L, 2L, 2L, NA), .Label = c("dry", "fire"), class = "factor"), 
    season_2011_3 = structure(c(2L, 2L, 1L, 2L, 2L, NA), .Label = c("dry", 
    "fire"), class = "factor"), season_2012_1 = structure(c(NA, 
    NA, 2L, 1L, 1L, 2L), .Label = c("fire", "wet"), class = "factor"), 
    season_2012_2 = structure(c(NA, 1L, 2L, 1L, 1L, NA), .Label = c("fire", 
    "wet"), class = "factor"), season_2012_3 = structure(c(NA, 
    1L, 2L, 1L, 1L, NA), .Label = c("fire", "wet"), class = "factor"), 
    OptTSF_2010_1 = c(1L, 1L, 0L, 1L, 1L, 1L), OptTSF_2010_2 = c(1L, 
    1L, 0L, 1L, 1L, NA), OptTSF_2010_3 = c(1L, 1L, NA, 1L, 1L, 
    NA), OptTSF_2011_1 = c(1L, 1L, 0L, 0L, 1L, NA), OptTSF_2011_2 = c(1L, 
    1L, 0L, 0L, 1L, NA), OptTSF_2011_3 = c(1L, 1L, 0L, 0L, 1L, 
    NA), OptTSF_2012_1 = c(NA, NA, 1L, 0L, 0L, 1L), OptTSF_2012_2 = c(NA, 
    1L, 1L, 0L, 0L, NA), OptTSF_2012_3 = c(NA, 1L, 1L, 0L, 0L, 
    NA)), .Names = c("SitePoint", "MR_Fire_2010_1", "MR_Fire_2010_2", 
"MR_Fire_2010_3", "MR_Fire_2011_1", "MR_Fire_2011_2", "MR_Fire_2011_3", 
"MR_Fire_2012_1", "MR_Fire_2012_2", "MR_Fire_2012_3", "season_2010_1", 
"season_2010_2", "season_2010_3", "season_2011_1", "season_2011_2", 
"season_2011_3", "season_2012_1", "season_2012_2", "season_2012_3", 
"OptTSF_2010_1", "OptTSF_2010_2", "OptTSF_2010_3", "OptTSF_2011_1", 
"OptTSF_2011_2", "OptTSF_2011_3", "OptTSF_2012_1", "OptTSF_2012_2", 
"OptTSF_2012_3"), class = "data.frame", row.names = c(NA, -6L
))

实际数据集大约是 23656 条记录 X 15 个变量，因此手工操作很可能会导致严重的头痛和潜在的错误。任何帮助或建议表示赞赏。如果在其他地方已经回答了这个问题，我们深表歉意。我找不到任何直接适用的东西；一切似乎都与三列有关，只有其中一列被提取为新变量。谢谢

SP

Answer 1

您可以使用 reshape 使用以下代码将数据框的结构从长更改为宽：

reshape(mydatain,timevar="Year_Rotation",idvar="SitePoint",direction="wide")

Answer 2

dcast 来自 data.table 的开发版本，即 v1.9.5 可以 同时投射多个列 。它可以从 here.

安装

library(data.table) ## v1.9.5+
dcast(setDT(mydatain), SitePoint~Year_Rotation,
         value.var=c('MR_Fire', 'fire_seas', 'OptTSF'))

重塑具有缺失值和多个感兴趣变量的大型矩阵

Reshape a large matrix with missing values and multiple vars of interest

r

reshape