'X' must be numeric error in Decorana/VEGAN function after subsetting in R 中
'X' must be numeric error in Decorana/VEGAN function after subsetting in R
我一直在 rowSums(veg) 中得到这个 error:Error :
'x' must be numeric
我从一个大数据集中提取了一小部分子集，当我 运行 DCA 排序时，我不断收到上述错误消息。我检查了，但我没有显示行中的字符数据。
install.packages("vegan")
library(vegan)
Dataveg2018A <- subset(DatasetMerg, Year == "2018" & Block == "A",
select = 4:7)
ord1<-decorana(Dataveg2018A)
有人可以告诉我我做错了什么吗？
子集 (DatasetMerg) 的示例数据
structure(list(Year = structure(c(3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), .Names = c("18A01",
"18A02", "18A03", "18A04", "18A05", "18A06", "18A07", "18A08",
"18A09", "18A10", "18A11", "18A12", "18A13", "18A14", "18A15",
"18A16", "18A17", "18A18", "18A19", "18A20"), .Label = c("2001",
"2008", "2018"), class = "factor"), Block = structure(c(1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L), .Names = c("18A01", "18A02", "18A03", "18A04", "18A05",
"18A06", "18A07", "18A08", "18A09", "18A10", "18A11", "18A12",
"18A13", "18A14", "18A15", "18A16", "18A17", "18A18", "18A19",
"18A20"), .Label = c("A", "B", "C", "D", "E", "F", "G", "H",
"I", "J", "X"), class = "factor"), Plot = structure(1:20, .Names = c("18A01",
"18A02", "18A03", "18A04", "18A05", "18A06", "18A07", "18A08",
"18A09", "18A10", "18A11", "18A12", "18A13", "18A14", "18A15",
"18A16", "18A17", "18A18", "18A19", "18A20"), .Label = c(" 1",
" 2", " 3", " 4", " 5", " 6", " 7", " 8", " 9", "10", "11", "12",
"13", "14", "15", "16", "17", "18", "19", "20", "21", "22", "23",
"24", "25", "26", "27", "28", "29", "30", "31", "32", "33", "34",
"35", "36", "37", "38", "39", "40", "41", "42", "43", "44", "45",
"46"), class = "factor"), Agrimonia.eupatoria = structure(c(3L,
2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L), .Names = c("18A01", "18A02", "18A03", "18A04", "18A05",
"18A06", "18A07", "18A08", "18A09", "18A10", "18A11", "18A12",
"18A13", "18A14", "18A15", "18A16", "18A17", "18A18", "18A19",
"18A20"), .Label = c("0", "1", "2", "6"), class = "factor"),
Agrostis.capillaris = structure(c(1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Names = c("18A01",
"18A02", "18A03", "18A04", "18A05", "18A06", "18A07", "18A08",
"18A09", "18A10", "18A11", "18A12", "18A13", "18A14", "18A15",
"18A16", "18A17", "18A18", "18A19", "18A20"), .Label = c("0",
"2", "3", "4", "6"), class = "factor"), Agrostis.gigantea = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 3L, 2L, 1L, 3L, 3L,
4L, 3L, 1L, 1L), .Names = c("18A01", "18A02", "18A03", "18A04",
"18A05", "18A06", "18A07", "18A08", "18A09", "18A10", "18A11",
"18A12", "18A13", "18A14", "18A15", "18A16", "18A17", "18A18",
"18A19", "18A20"), .Label = c("0", "2", "3", "4", "6"), class = "factor"),
Agrostis.stolonifera = structure(c(5L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Names = c("18A01",
"18A02", "18A03", "18A04", "18A05", "18A06", "18A07", "18A08",
"18A09", "18A10", "18A11", "18A12", "18A13", "18A14", "18A15",
"18A16", "18A17", "18A18", "18A19", "18A20"), .Label = c("0",
"1", "18", "2", "3", "38", "4", "6", "68", "8"), class = "factor")),
.Names = c("Year",
"Block", "Plot", "Agrimonia.eupatoria", "Agrostis.capillaris",
"Agrostis.gigantea", "Agrostis.stolonifera"), row.names = c("18A01",
"18A02", "18A03", "18A04", "18A05", "18A06", "18A07", "18A08",
"18A09", "18A10", "18A11", "18A12", "18A13", "18A14", "18A15",
"18A16", "18A17", "18A18", "18A19", "18A20"), class = "data.frame")
所有 你的变量都是非数字（因子），在原始 DatasetMerg 及其子集（Dataveg2018A）中。您可以看到这个发出命令 str(DatasetMerg) ，它将所有变量作为因子（及其子集相同）。您还可以在自己的完整显示 DatasetMerg 中看到这一点，其中所有物种数据都作为因子给出。这只是您的第一个物种，您为其提供的数据为：
Agrostis.capillaris = structure(c(1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Names = c("18A01",
"18A02", "18A03", "18A04", "18A05", "18A06", "18A07", "18A08",
"18A09", "18A10", "18A11", "18A12", "18A13", "18A14", "18A15",
"18A16", "18A17", "18A18", "18A19", "18A20"), .Label = c("0",
"2", "3", "4", "6"), class = "factor")
请注意最后的定义 class = "factor"。这些值（所有 1L）给出了您的因子水平的索引，这些水平在 .Label 中给出。所以你所有的数据都是一个（1L）并且这些显示为 .Labels[1L] == c("0", "2", "3", "4", "6")[1L] == "0" 这是非数字（一个字符）。
我一直在 rowSums(veg) 中得到这个 error:Error :
'x' must be numeric
我从一个大数据集中提取了一小部分子集，当我 运行 DCA 排序时，我不断收到上述错误消息。我检查了，但我没有显示行中的字符数据。
install.packages("vegan")
library(vegan)
Dataveg2018A <- subset(DatasetMerg, Year == "2018" & Block == "A",
select = 4:7)
ord1<-decorana(Dataveg2018A)
有人可以告诉我我做错了什么吗？
子集 (DatasetMerg) 的示例数据
structure(list(Year = structure(c(3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), .Names = c("18A01",
"18A02", "18A03", "18A04", "18A05", "18A06", "18A07", "18A08",
"18A09", "18A10", "18A11", "18A12", "18A13", "18A14", "18A15",
"18A16", "18A17", "18A18", "18A19", "18A20"), .Label = c("2001",
"2008", "2018"), class = "factor"), Block = structure(c(1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L), .Names = c("18A01", "18A02", "18A03", "18A04", "18A05",
"18A06", "18A07", "18A08", "18A09", "18A10", "18A11", "18A12",
"18A13", "18A14", "18A15", "18A16", "18A17", "18A18", "18A19",
"18A20"), .Label = c("A", "B", "C", "D", "E", "F", "G", "H",
"I", "J", "X"), class = "factor"), Plot = structure(1:20, .Names = c("18A01",
"18A02", "18A03", "18A04", "18A05", "18A06", "18A07", "18A08",
"18A09", "18A10", "18A11", "18A12", "18A13", "18A14", "18A15",
"18A16", "18A17", "18A18", "18A19", "18A20"), .Label = c(" 1",
" 2", " 3", " 4", " 5", " 6", " 7", " 8", " 9", "10", "11", "12",
"13", "14", "15", "16", "17", "18", "19", "20", "21", "22", "23",
"24", "25", "26", "27", "28", "29", "30", "31", "32", "33", "34",
"35", "36", "37", "38", "39", "40", "41", "42", "43", "44", "45",
"46"), class = "factor"), Agrimonia.eupatoria = structure(c(3L,
2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L), .Names = c("18A01", "18A02", "18A03", "18A04", "18A05",
"18A06", "18A07", "18A08", "18A09", "18A10", "18A11", "18A12",
"18A13", "18A14", "18A15", "18A16", "18A17", "18A18", "18A19",
"18A20"), .Label = c("0", "1", "2", "6"), class = "factor"),
Agrostis.capillaris = structure(c(1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Names = c("18A01",
"18A02", "18A03", "18A04", "18A05", "18A06", "18A07", "18A08",
"18A09", "18A10", "18A11", "18A12", "18A13", "18A14", "18A15",
"18A16", "18A17", "18A18", "18A19", "18A20"), .Label = c("0",
"2", "3", "4", "6"), class = "factor"), Agrostis.gigantea = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 3L, 2L, 1L, 3L, 3L,
4L, 3L, 1L, 1L), .Names = c("18A01", "18A02", "18A03", "18A04",
"18A05", "18A06", "18A07", "18A08", "18A09", "18A10", "18A11",
"18A12", "18A13", "18A14", "18A15", "18A16", "18A17", "18A18",
"18A19", "18A20"), .Label = c("0", "2", "3", "4", "6"), class = "factor"),
Agrostis.stolonifera = structure(c(5L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Names = c("18A01",
"18A02", "18A03", "18A04", "18A05", "18A06", "18A07", "18A08",
"18A09", "18A10", "18A11", "18A12", "18A13", "18A14", "18A15",
"18A16", "18A17", "18A18", "18A19", "18A20"), .Label = c("0",
"1", "18", "2", "3", "38", "4", "6", "68", "8"), class = "factor")),
.Names = c("Year",
"Block", "Plot", "Agrimonia.eupatoria", "Agrostis.capillaris",
"Agrostis.gigantea", "Agrostis.stolonifera"), row.names = c("18A01",
"18A02", "18A03", "18A04", "18A05", "18A06", "18A07", "18A08",
"18A09", "18A10", "18A11", "18A12", "18A13", "18A14", "18A15",
"18A16", "18A17", "18A18", "18A19", "18A20"), class = "data.frame")
所有 你的变量都是非数字（因子），在原始 DatasetMerg 及其子集（Dataveg2018A）中。您可以看到这个发出命令 str(DatasetMerg) ，它将所有变量作为因子（及其子集相同）。您还可以在自己的完整显示 DatasetMerg 中看到这一点，其中所有物种数据都作为因子给出。这只是您的第一个物种，您为其提供的数据为：
Agrostis.capillaris = structure(c(1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Names = c("18A01",
"18A02", "18A03", "18A04", "18A05", "18A06", "18A07", "18A08",
"18A09", "18A10", "18A11", "18A12", "18A13", "18A14", "18A15",
"18A16", "18A17", "18A18", "18A19", "18A20"), .Label = c("0",
"2", "3", "4", "6"), class = "factor")
请注意最后的定义 class = "factor"。这些值（所有 1L）给出了您的因子水平的索引，这些水平在 .Label 中给出。所以你所有的数据都是一个（1L）并且这些显示为 .Labels[1L] == c("0", "2", "3", "4", "6")[1L] == "0" 这是非数字（一个字符）。