我有一個 for 回圈，它回傳三個連續資料點上最佳擬合的斜率。
我的資料：
dput(DIP)
structure(list(DSI = c(4, 6, 8, 10, 12, 14, 16, 18, 20, 22),
Flask1 = c(0.062, 0.117, 0.33, 0.617, 1.194, 1.855, 1.706,
1.537, 1.453, 1.467), Flask2 = c(0.045, 0.133, 0.319, 0.609,
1.189, 1.788, 1.616, 1.463, 1.368, 1.396), Flask3 = c(0.045,
0.129, 0.327, 0.603, 1.134, 1.658, 1.555, 1.385, 1.34, 1.4
), Flask4 = c(0.046, 0.117, 0.308, 0.554, 0.964, 1.478, 1.544,
1.34, 1.334, 1.34)), row.names = c(NA, -10L), spec = structure(list(
cols = list(DSI = structure(list(), class = c("collector_double",
"collector")), `Flask 1` = structure(list(), class = c("collector_double",
"collector")), `Flask 2` = structure(list(), class = c("collector_double",
"collector")), `Flask 3` = structure(list(), class = c("collector_double",
"collector")), `Flask 4` = structure(list(), class = c("collector_double",
"collector"))), default = structure(list(), class = c("collector_guess",
"collector")), delim = ","), class = "col_spec"), problems = <pointer: 0x000001f6ae38ab20>, class = c("spec_tbl_df",
"tbl_df", "tbl", "data.frame"))
回圈：
slopes <- rep(NA, nrow(DIP)-2)
for( i in 1:length(slopes)){
slopes[i] <- lm(Flask1 ~ DSI, data=DIP[i:(i 2), ])$coefficients[2]
}
print(slopes)
哪個回傳
[1] 0.06700 0.12500 0.21600 0.30950 0.12800 -0.07950 -0.06325 -0.01750
我試圖使這個回圈成為一個函式，這樣我就可以將它用于我資料中的其他列以及其他資料。我試過這個功能：
get_slopes <- function (Data, X, Y) {
slopes <- rep(NA, nrow(Data)-2)
for( i in 1:length(slopes)){
slopes[i] <- lm(Y ~ X, data=Data[i:(i 2), ])$coefficients[2]
}
print(slopes)
}
但是當我跑步時
get_slopes(Data = DIP, X = DIP$DSI, Y = DIP$Flask1)
它回傳
[1] 0.09684848 0.09684848 0.09684848 0.09684848 0.09684848 0.09684848 0.09684848 0.09684848
我哪里錯了？如何更改我的函式以回傳與回圈前置函式相同的值？
uj5u.com熱心網友回復：
試試這個，
get_slopes <- function (Data, X, Y) {
slopes <- rep(NA, nrow(Data)-2)
for( i in 1:length(slopes)){
slopes[i] <- lm(paste(Y ,"~", X), data=Data[i:(i 2), ])$coefficients[2]
}
print(slopes)
}
進而，
get_slopes(Data = DIP, X = "DSI", Y = "Flask1")
或者，您可以使用該purrr::map_dbl()功能，例如
get_slopes <- function(Data, X, Y) {
purrr::map_dbl(1:length(Data), ~ lm(paste(Y, "~", X), data=Data[.x:(.x 2), ])$coefficients[2])
}
get_slopes(Data = DIP, X = "DSI", Y = "Flask1")
[1] 0.0670 0.1250 0.2160 0.3095 0.1280
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