在列表的每个数据框中添加一行，其中包含某些行的平均值

debugcn 发表于 Dev

马尔·多里

我有一个名为my_list的数据帧列表。以下是my_list中数据框的示例。

> print(df1)    
       A          B         Names
1   0.8262825   0.734412    Baseline
2   1.0100000   0.734412    Sample1
3   0.8262825   0.734412    Sample2
4   1.0100000   0.734412    Sample3
5   0.8262825   0.734412    Sample4
6   1.0100000   0.734412    Sample5
7   0.8262825   0.734412    Sample6
8   1.0100000   0.734412    Sample7
9   0.8262825   0.734412    Sample8
10  1.0100000   0.734412    Sample9
11  0.8262825   0.734412    Sample10
12  1.0100000   NA          AASHTO

我想向my_list中的每个数据框添加一个新行，此数据帧包含列A和B的平均值，但在列名中具有“基线”和“ AASHTO”的行除外。（因此，只有Sample1到Sample10的行的均值）

最后，我想将Name列设置为my_list中每个数据框的行名，并从列表中的所有数据框中删除Names列。

my_list中每个数据框的预期结果将是

                A          B         
Baseline    0.8262825   0.734412    
Sample1     1.0100000   0.734412    
Sample2     0.8262825   0.734412    
Sample3     1.0100000   0.734412    
Sample4     0.8262825   0.734412    
Sample5     1.0100000   0.734412    
Sample6     0.8262825   0.734412    
Sample7     1.0100000   0.734412    
Sample8     0.8262825   0.734412    
Sample9     1.0100000   0.734412    
Sample10    0.8262825   0.734412
Mean        0.8156500   0.734412
AASHTO      1.0100000   NA

非常感谢您的帮助。

阿克伦

我们可以遍历listwith lapply，获取colMeans列“ A”，“ B”的列，排除“名称”为“ Baseline”或“ AASHTO”的行，然后rbind获取原始数据集

lst2 <-  lapply(lst1, function(x) {
   means <- colMeans(x[!x$Names %in% c("Baseline", "AASHTO"),
            c('A', 'B')], na.rm = TRUE)
        d1 <- rbind(x, data.frame(Names = "Mean", as.list(means)))
        row.names(d1) <- d1$Names
        d1[setdiff(names(d1), "Names")]
             })

或使用 tidyverse

library(dplyr)
library(purrr)
library(tibble)
map(lst1, ~ .x %>%
            add_row(Names = 'Mean', 
              A = mean(.$A[!.$Names %in% c("Baseline", "AASHTO")], 
                     na.rm = TRUE),
              B = mean(.$B[!.$Names %in% c("Baseline", "AASHTO")], na.rm = TRUE)) %>%
         `row.names<-`(., NULL) %>%
             column_to_rownames('Names'))

数据

lst1 <- list(structure(list(A = c(0.8262825, 1.01, 0.8262825, 1.01, 0.8262825, 
1.01, 0.8262825, 1.01, 0.8262825, 1.01, 0.8262825, 1.01), B = c(0.734412, 
0.734412, 0.734412, 0.734412, 0.734412, 0.734412, 0.734412, 0.734412, 
0.734412, 0.734412, 0.734412, NA), Names = c("Baseline", "Sample1", 
"Sample2", "Sample3", "Sample4", "Sample5", "Sample6", "Sample7", 
"Sample8", "Sample9", "Sample10", "AASHTO")), class = "data.frame", row.names = c("1", 
"2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12")), structure(list(
    A = c(0.8262825, 1.01, 0.8262825, 1.01, 0.8262825, 1.01, 
    0.8262825, 1.01, 0.8262825, 1.01, 0.8262825, 1.01), B = c(0.734412, 
    0.734412, 0.734412, 0.734412, 0.734412, 0.734412, 0.734412, 
    0.734412, 0.734412, 0.734412, 0.734412, NA), Names = c("Baseline", 
    "Sample1", "Sample2", "Sample3", "Sample4", "Sample5", "Sample6", 
    "Sample7", "Sample8", "Sample9", "Sample10", "AASHTO")), class = "data.frame", row.names = c("1", 
"2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12")))

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