我有一个数据框，其中包含有关植被覆盖率和覆盖率百分比的信息，这些信息是使用样方收集的。设置数据框，使每一行代表一个样方。如果一个样方中有多个物种，则它们都列在同一行中，相应的百分比覆盖率始终在下一列中。这是一个例子，物种用4个字母代码表示：
问题在于物种没有按任何特定顺序记录，而且并非所有物种都出现在每个样方中。每个样方也可以有任意数量的物种。我需要能够提取每个物种及其各自的覆盖范围，并将它们放入另一个数据框中以进行进一步分析。例如，上述示例数据中的物种“bope”如下所示：
非常感谢任何帮助。 布赖恩
【问题讨论】：
您可以通过将数据重新整形为长格式然后按行值过滤来完成此操作。
df = data.frame(Quadrat = 1:6, Date = seq.Date(as.Date("2014-01-01"), by = 1, length = 6), Species_1 = c("unk1", "bope", "bope", "stgu", "bg","bope"),
covrage = sample(1:100,6), Species_2 = c("bope", "bial", "stgu", "bg","unk1", "bg"), covrage2 = sample(1:100,6))
> df
Quadrat Date Species_1 covrage Species_2 covrage2
1 1 2014-01-01 unk1 76 bope 63
2 2 2014-01-02 bope 82 bial 33
3 3 2014-01-03 bope 41 stgu 5
4 4 2014-01-04 stgu 6 bg 45
5 5 2014-01-05 bg 65 unk1 21
6 6 2014-01-06 bope 15 bg 96
df$Species_1 = as.character(df$Species_1)
df$Species_2 = as.character(df$Species_2)
df2 = reshape(df, varying = list(c("Species_1", "Species_2"), c("covrage", "covrage2")), v.names = c("Species", "Covrage"), direction = "long")
> df2
Quadrat Date time Species Covrage id
1.1 1 2014-01-01 1 unk1 76 1
2.1 2 2014-01-02 1 bope 82 2
3.1 3 2014-01-03 1 bope 41 3
4.1 4 2014-01-04 1 stgu 6 4
5.1 5 2014-01-05 1 bg 65 5
6.1 6 2014-01-06 1 bope 15 6
1.2 1 2014-01-01 2 bope 63 1
2.2 2 2014-01-02 2 bial 33 2
3.2 3 2014-01-03 2 stgu 5 3
4.2 4 2014-01-04 2 bg 45 4
5.2 5 2014-01-05 2 unk1 21 5
6.2 6 2014-01-06 2 bg 96 6
> df2[df2$Species == "bope", colnames(df2) %in% c("Quadrat", "Covrage")]
Quadrat Covrage
2.1 2 82
3.1 3 41
6.1 6 15
1.2 1 63
【讨论】：
如果您不希望按日期显示，让我忽略日期列，
这是一个示例数据框
species1 = replicate(20, paste(sample(LETTERS, 5), collapse = ""))
coverage1 = rnorm(20, 50, 30)
species2 = sample(species1)
coverage2 = sample(1:100, 20,replace = TRUE)
df = data.frame(species1, coverage1, species2, coverage2)
df
species1 coverage1 species2 coverage2
1 KIRGD -6.1879727 OBHTY 96
2 SXKAB 70.4472228 GUROP 40
3 LSWME 59.4121446 OMABR 29
4 KVSRD 53.8434373 PAQCJ 12
5 KHRUD 62.8253485 SXKAB 57
6 FOAGY 83.1087433 WUEMQ 4
7 QHYZL 52.2393233 KIRGD 47
8 EGDHA 82.2169139 RJKUS 72
9 GXFAR 58.1819166 SXNGO 16
10 SXNGO -0.6093836 QHYZL 2
11 ZJQOA 99.1073472 KHRUD 28
12 PAQCJ -1.0029008 TEPIZ 40
13 TEPIZ 55.5824570 WNLYJ 31
14 RJKUS 55.7524571 GDQOV 27
15 WUEMQ 9.4777950 LSWME 9
16 GDQOV 31.9365398 KVSRD 28
17 OBHTY 5.8709309 GXFAR 89
18 OMABR -20.5623502 ZJQOA 85
19 WNLYJ 75.9212241 FOAGY 11
20 GUROP 60.7119029 EGDHA 38
获取每个物种的覆盖率
species = unique(df$species1, df$species2)
sapply(species, function(x)df[grep(x, df$species1),]$coverage2)
cols = grep("coverage", colnames(df))
coverage = lapply(cols, function(y)sapply(species, function(x)df[grep(x, df[,(y-1)]),][,y]) )
df2 = data.frame(species, coverage1 = coverage[[1]], coverage2 = coverage[[2]])
df2
species coverage1 coverage2
1 KIRGD -6.1879727 47
2 SXKAB 70.4472228 57
3 LSWME 59.4121446 9
4 KVSRD 53.8434373 28
5 KHRUD 62.8253485 28
6 FOAGY 83.1087433 11
7 QHYZL 52.2393233 2
8 EGDHA 82.2169139 38
9 GXFAR 58.1819166 89
10 SXNGO -0.6093836 16
11 ZJQOA 99.1073472 85
12 PAQCJ -1.0029008 12
13 TEPIZ 55.5824570 40
14 RJKUS 55.7524571 72
15 WUEMQ 9.4777950 4
16 GDQOV 31.9365398 27
17 OBHTY 5.8709309 96
18 OMABR -20.5623502 29
19 WNLYJ 75.9212241 31
20 GUROP 60.7119029 40
【讨论】：