我有兩個資料框。我想Value根據匹配值將df B轉移到 df AT和Sample.
Data frame A
Person T Sample Value
1 A 1
1 A 2
1 A 3
1 B 1
1 B 2
1 B 3
2 A 1
2 A 2
2 A 3
2 B 1
2 B 2
2 B 3
2 C 1
2 C 2
2 C 3
...
Data frame B
T Sample Value
A 1 30.2
A 2 12.5
A 3 77.5
B 1 22.2
B 2 11.0
B 3 23.6
我的解決方案目前是兩個嵌套的 for 回圈，這太慢了，因為資料幀非常大。我怎樣才能更有效地做到這一點，例如與申請家庭？
for (i in 1:nrow(A)) {
for (p in 1:nrow(B)) {
if(A$T[i] == B$T[p] & A$Sample[i] == B$Sample[p]){
A$Value[i] <- B$Value[p]
}
}
}
uj5u.com熱心網友回復：
不需要使用任何應用函式，只需像這樣合并 A 和 B。
A <- structure(list(Person = c(1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L), T = c("A", "A", "A", "B", "B", "B",
"A", "A", "A", "B", "B", "B", "C", "C", "C"), Sample = c(1L,
2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L)), row.names = c(NA,
-15L), class = c("data.frame"))
B <- structure(list(T = c("A", "A", "A", "B", "B", "B"), Sample = c(1L,
2L, 3L, 1L, 2L, 3L), Value = c(30.2, 12.5, 77.5, 22.2, 11, 23.6
)), row.names = c(NA, -6L), class = c("data.frame"))
# all = T if you wish to keep all in A without values in B
merge(A, B, by = c("T", "Sample"), all = T)
T Sample Person Value
1 A 1 1 30.2
2 A 1 2 30.2
3 A 2 2 12.5
4 A 2 1 12.5
5 A 3 2 77.5
6 A 3 1 77.5
7 B 1 1 22.2
8 B 1 2 22.2
9 B 2 1 11.0
10 B 2 2 11.0
11 B 3 2 23.6
12 B 3 1 23.6
13 C 1 2 NA
14 C 2 2 NA
15 C 3 2 NA
uj5u.com熱心網友回復：
為此，我傾向于使用現有的連接功能。如：
left_join(
select(dfA, -Value),
dfB,
by = c('T', 'Sample')
)
資料：
dfA <- structure(list(Person = c(1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), T = c("A", "A", "A", "B", "B", "B", "A", "A", "A", "B", "B", "B", "C", "C", "C"), Sample = c(1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L), Value = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA)), class = "data.frame", row.names = c(NA, -15L))
dfB <- structure(list(T = c("A", "A", "A", "B", "B", "B"), Sample = c(1L, 2L, 3L, 1L, 2L, 3L), Value = c(30.2, 12.5, 77.5, 22.2, 11, 23.6 )), class = "data.frame", row.names = c(NA, -6L))
輸出
Person T Sample Value
1 1 A 1 30.2
2 1 A 2 12.5
3 1 A 3 77.5
4 1 B 1 22.2
5 1 B 2 11.0
6 1 B 3 23.6
7 2 A 1 30.2
8 2 A 2 12.5
9 2 A 3 77.5
10 2 B 1 22.2
11 2 B 2 11.0
12 2 B 3 23.6
13 2 C 1 NA
14 2 C 2 NA
15 2 C 3 NA
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標籤：r
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