中的R由因子

Question

分組我有由樣本分組的3個參數測量值的數據幀一個數據幀中刪除異常值：

ORD  curv exp rep   mu   lam  abs 
1 Combi pH=7 Curva_F_Cor Exp_F Rep1 0.15637365 714.947.305 0.4990000 
2 Combi pH=7 Curva_F_Cor Exp_F Rep10 0.12817901 6.797.925.883 0.4914276 
3 Combi pH=7 Curva_F_Cor Exp_F Rep11 0.13392221 6.765.638.528 0.5261217 
4 Combi pH=7 Curva_F_Cor Exp_F Rep2 0.09683254 6.671.151.868 0.4236507 
5 Combi pH=7 Curva_F_Cor Exp_F Rep3 0.11249738 6.868.057.298 0.4899013 
6 Combi pH=7 Curva_F_Cor Exp_F Rep4 0.10878719 6.829.856.006 0.4876704 
7 Combi pH=7 Curva_F_Cor Exp_F Rep5 0.11019295 6.758.654.665 0.4871269 
8 Combi pH=7 Curva_F_Cor Exp_F Rep6 0.12100511 6.733.007.508 0.4923079 
9 Combi pH=7 Curva_F_Cor Exp_F Rep7 0.09803942 6.791.743.116 0.4185484 
10 Combi pH=7 Curva_F_Cor Exp_F Rep8 0.13842086 6.909.115.228 0.5392007 
11 Combi pH=7 Curva_F_Cor Exp_F Rep9 0.12778964 6.779.856.345 0.5475924 
12 ORD0793 Curva_F_Cor Exp_F Rep1 0.13910441 7.051.072.489 0.4706000 
13 ORD0793 Curva_F_Cor Exp_F Rep2 0.12603702 7.143.108.903 0.4436000 
14 ORD0793 Curva_F_Cor Exp_F Rep3 0.12670842 6.989.806.663 0.4258000 
15 ORD0795 Curva_F_Cor Exp_F Rep1 0.12982122 7.029.434.508 0.4996000 
16 ORD0795 Curva_F_Cor Exp_F Rep2 0.13648100 6.776.386.442 0.4896000 
17 ORD0795 Curva_F_Cor Exp_F Rep3 0.13593685 7.161.375.293 0.4766000 
18 ORD0799 Curva_F_Cor Exp_F Rep1 0.13906691 7.065.198.206 0.4806000 
19 ORD0799 Curva_F_Cor Exp_F Rep2 0.14822216 70.824.584 0.4640000 
20 ORD0799 Curva_F_Cor Exp_F Rep3 0.10630870 6.669.130.811 0.4686809 
21 ORD0839 Curva_F_Cor Exp_F Rep1 0.16717843 6.133.730.567 0.5458000 
22 ORD0839 Curva_F_Cor Exp_F Rep2 0.09995048 7.119.564.022 0.4026000 
23 ORD0839 Curva_F_Cor Exp_F Rep3 0.15911022 7.321.225.246 0.5118000 
24 ORD0843 Curva_F_Cor Exp_F Rep1 0.12508123 6.579.839.732 0.5458217 
25 ORD0843 Curva_F_Cor Exp_F Rep2 0.16396603 6.536.282.149 0.5210000 
26 ORD0843 Curva_F_Cor Exp_F Rep3 0.15029945 7.015.299.122 0.4838000 
27 ORD0847 Curva_F_Cor Exp_F Rep1 0.11697558 7.076.730.379 0.4148000 
28 ORD0847 Curva_F_Cor Exp_F Rep2 0.15276497 7.181.749.575 0.5088000 
29 ORD0847 Curva_F_Cor Exp_F Rep3 0.15533901 710.518.294 0.5348000 
30 ORD0856 Curva_F_Cor Exp_F Rep1 0.11217122 7.940.648.197 0.4130000 
31 ORD0856 Curva_F_Cor Exp_F Rep2 0.12010424 8.359.758.086 0.4446000 
32 ORD0856 Curva_F_Cor Exp_F Rep3 0.13337373 811.057.251 0.4780000 

我想以去除包含在ORD列中的每個樣品的畝林的離羣值和絕對。

我在這個論壇上發現了一個函數來刪除異常值：

remove_outliers <- function(x, na.rm = TRUE, ...) { 
    qnt <- quantile(x, probs=c(.25, .75), na.rm = na.rm, ...) 
    H <- 1.5 * IQR(x, na.rm = na.rm) 
    y <- x 
    y[x < (qnt[1] - H)] <- NA 
    y[x > (qnt[2] + H)] <- NA 
    y 
} 

，但我只知道如何應用它們的數值向量或使用lapply應用功能將數據幀的每一列，但我不知道如何將tje函數應用於按樣本分組的數據框。喜歡的東西remove_outliers(mu~ORD, data=df, na.rm=TRUE)

我要感謝所有幫助

Answer 1

我們可以使用函數從dplyr實現這一目標。您可能希望將group_by列作爲組，並使用mutate來更新您的列。

library(dplyr) 

通過指定列名和函數，您可以只應用一列，如下所示。

# Apply the finction to one column 
dt2 <- dt %>% 
    group_by(ORD) %>% 
    mutate(mu = remove_outliers(mu)) 

您也可以通過使用mutate_at在vars()指定多個列名應用此多列。

# Apply the function to multiple columns 
dt3 <- dt %>% 
    group_by(ORD) %>% 
    mutate_at(vars(mu, abs), funs(remove_outliers)) 

Answer 2

替代地，在基礎R考慮by這產生由列出的因素，df$ORD切片dataframes的列表。之後，行將所有df元素綁定到一個編譯的數據框中。並使用sapply來處理數字列上的功能：

dflist <- by(df, df$ORD, function(i){ 
    i[c("mu","lam","abs")] <- sapply(i[c("mu","lam","abs")], remove_outliers) 
    return(i) 
}) 

newdf <- do.call(rbind, dflist) 
rownames(newdf) <- NULL