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在使用 unique() function 之后,如何從具有重復案例的 data.frame 中獲取行的索引?

[英]How can I get the index of the rows, from a data.frame with repeated cases, after using the unique() function?

我正在清理我的數據庫“Visitas”,因為它是由每周來醫院一次的患者組成的,所以我重復了很多次相同的主題,而我只是有興趣將患者考慮一次。

我使用unique() function 來獲取“真實”患者數量,但現在我無法從原始數據庫中獲取它。

我試圖用這些情況創建一個向量,然后使用 which() 來獲取索引,但它不起作用。

我在下面留下一些代碼。

# Visitas_act: active patients who are still going to the hospital
# Visitas_mod: the initial 'Visitas' database but almost cleaned.
# codeep: patient code, identifier

Visitas_mod <- Visitas_mod[Visitas_act, ]
unique(Visitas_mod[, 'codeep'])
Visitas_r <- unique(Visitas_mod[, 'codeep'])

我試過了,但它不起作用,因為索引在“Visitas_mod”數據庫中不匹配

tut <- which(Visitas_mod[, 'codeep'] == Visitas_r)    
Visitas_mod <- Visitas_mod[tut, ]

我不完全理解你的問題,但我最好的猜測是這樣的,如果你有任何問題或者我弄錯了,只是評論:)

#create dummy names
names <- cbind(row.names(mtcars),c(1:32))
visit <- sample(names[,1],400,replace = T)
df <- as.data.frame(x = visit)
id <- names[match(df$visit,names),2]
df <- cbind(df,id)


#get vector of unique visitors
uniqV <- unique(df$visit)
#this returns the index of first occurence of a visitor in the dataframe
match(uniqV,df$visit)

Output:

 1   2   3   5   6   7   8   9  11  12  13  14  15  20  21  23  24  25  28  30  32  37  46
47  53  58  64  68  85  90 107 120

所有位置都可以用代碼的這個續部分來完成

#return all position of unique visitor in dataset
test <- function(x) {
  which(df$visit %in% x)
}

matches <- sapply(uniqV,test)

out <- cbind(as.character(uniqV), unlist(lapply(matches, paste, collapse =",")))

Output:

1   Ford Pantera L  1,98,116,127,128,136,142,189,208,210,217,254,273,275,277,298,313,360
2   Hornet Sportabout   2,19,29,78,81,112,144,234,294,303,322,332,387
3   Merc 280C   3,4,39,159,173,188,308,309,312,351,389
4   Merc 230    5,18,48,77,106,150,161,211,219,240,241,270,299,306,330,365,383
5   Dodge Challenger    6,74,154,172,222,268,336,352,367
6   Valiant 7,26,207,235,258,265,392,397
7   Porsche 914-2   8,45,102,113,117,119,121,131,149,151,224,288,329,343,350,362,394
8   Fiat X1-9   9,10,65,95,135,170,271,282,285,346,380

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