我想为多个列中的多个值提取一些摘要统计信息。我的数据如下
id pace type value abundance
51 (T) (JC) (L) 0
51 (T) (JC) (L) 0
51 (T) (JC) (H) 0
52 (T) (JC) (H) 0
52 (R) (JC) (H) 0
53 (T) (JC) (L) 1
53 (T) (JC) (H) 1
53 (R) (JC) (H) 1
53 (R) (JC) (H) 1
53 (R) (JC) (H) 1
54 (T) (BC) <blank> 0
54 (T) (BC) <blank> 0
54 (T) (BC) <blank> 0
我希望有这样的东西
id ptype (T) (R) (L) (H) abundance
51 (JC) 3 0 2 1 0
52 (JC) 1 1 0 2 0
53 (JC) 2 3 1 4 1
54 (BC) 3 0 0 0 0
我已经开始编写一些代码:
for (i in levels(df$id))
{
extract.event <- df[df$id==i,]# To identify each section
ppace <- table(extract.event$pace) #count table of pace
ptype <- extract.event$type[1] # extract the first line to be the type
nvalues <- table(extract.event$value) #count table of value
nabundance <- min(extract.event$abundance) #minimum of abundance
d <- cbind(ppace,ptype,forbeh,nvalues,nabundance)
但是我在合并值时遇到了问题，尤其是在无用的状态下打印出一个空表时。我不希望按名称提取数据，因为数据框中有太多名称。有任何想法吗？我认为这可能与plyr软件包有关，但仍不确定...
谢谢，
优雅
最佳答案
我不得不重写您的data.frame(以备将来引用，请粘贴dput的结果，因为我们讨厌重写您的数据)，但这是我的尝试。我猜你正在寻找一些类似于聚合函数的东西:
df <- data.frame(id = as.factor(c(51,51,51,52,52,53,53,53,53,53,54,54,54)),
pace = c("(T)","(T)","(T)","(T)","(R)","(T)","(T)","(R)","(R)","(R)","(T)","(T)","(T)"),
type = c("(JC)","(JC)","(JC)","(JC)","(JC)","(JC)","(JC)","(JC)","(JC)","(JC)","(BC)","(BC)","(BC)"), value = c("(L)","(L)","(H)","(H)","(H)","(L)","(H)","(H)","(H)","(H)","<blank>","<blank>","<blank>"),
abundance = c(0,0,0,0,0,1,1,1,1,1,0,0,0))
smallnames <- colnames(do.call("cbind",as.list(aggregate(cbind(value, pace, abundance) ~ id + type, data = lapply(df, as.character), table))))
smallnames
[1] "id" "type" "(H)" "(L)" "<blank>" "(R)" "(T)" "0"
[9] "1"
df.new <- do.call("data.frame", as.list(aggregate(cbind(value, pace, abundance) ~ id + type, data = lapply(df, as.character), table)))
colnames(df.new) <- smallnames
df.new$abundance <- df.new$`1`
df.new
id type (H) (L) <blank> (R) (T) 0 1 abundance
1 54 (BC) 0 0 3 0 3 3 0 0
2 51 (JC) 1 2 0 0 3 3 0 0
3 52 (JC) 2 0 0 1 1 2 0 0
4 53 (JC) 4 1 0 3 2 0 5 5
df.final <- df.new[, -which(colnames(df.new) %in% c("<blank>","0","1"))]
df.final
id type (H) (L) (R) (T) abundance
1 54 (BC) 0 0 0 3 0
2 51 (JC) 1 2 0 3 0
3 52 (JC) 2 0 1 1 0
4 53 (JC) 4 1 3 2 5
让我知道这是您要查找的内容还是遇到问题。
关于r - 如何获取每个唯一ID的摘要，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/43646725/