如何獲取每個唯一ID的摘要

Question

我想爲多列中的多個值提取一些摘要統計信息。我的數據看起來如下

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 

，我希望這樣的事情

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 

我已經開始寫一些代碼：

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) 

，但我遇到了合併值問題，尤其是當nabundance打印出一張空白表格時。我不想按名稱提取，因爲數據框中有很多名字。有任何想法嗎？我想這可能是是與plyr包，但仍不能確定......

感謝，

格雷斯

Answer 1

我不得不重寫你的data.frame（以供將來參考，請貼上結果因爲我們討厭重寫你的數據），但這是我的嘗試。我猜你正在尋找沿聚合函數線的東西：

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 

讓我知道這是你正在尋找，或者如果你有麻煩了什麼。