如何在 R 中将列表列表转换为整洁的 tibble 或 data.frame

Question

我有以下列表：

my_lol <- structure(list(coolfactor_score = list(structure(c(0.164477631065473, 
0.198253819406019, 0.396414447052519, 0.133118603987442, 0.107735498488546
), .Names = c("B", "Mac", "NK", "Neu", "Stro")), structure(c(0.186215537135912, 
0.18408529174803, 0.375349920115798, 0.247664923324821, 0.006684327675438
), .Names = c("B", "Mac", "NK", "Neu", "Stro"))), sr_crt = list(
    structure(list(crt = 0.133118603987442, sr = 0.407076876403305), .Names = c("crt", 
    "sr")), structure(list(crt = 0.18408529174803, sr = 0.0829181742326453), .Names = c("crt", 
    "sr"))), sample_names = c("Sample1", "Sample2")), .Names = c("coolfactor_score", 
"sr_crt", "sample_names"))

看起来像这样：

> my_lol
$coolfactor_score
$coolfactor_score[[1]]
        B       Mac        NK       Neu      Stro 
0.1644776 0.1982538 0.3964144 0.1331186 0.1077355 

$coolfactor_score[[2]]
          B         Mac          NK         Neu        Stro 
0.186215537 0.184085292 0.375349920 0.247664923 0.006684328 


$sr_crt
$sr_crt[[1]]
$sr_crt[[1]]$crt
[1] 0.1331186

$sr_crt[[1]]$sr
[1] 0.4070769


$sr_crt[[2]]
$sr_crt[[2]]$crt
[1] 0.1840853

$sr_crt[[2]]$sr
[1] 0.08291817



$sample_names
[1] "Sample1" "Sample2"
# Note that the number of samples can be more than 2 and cell type more than 5.

我怎样才能把它整理到这个数据框中（小标题）

CellType    Sample    CoolFactorScore  SR            CRT
B           Sample1   0.1644776        0.4070769     0.1331186
Mac         Sample1   0.1982538        0.4070769     0.1331186
NK          Sample1   0.3964144        0.4070769     0.1331186
Neu         Sample1   0.1331186        0.4070769     0.1331186
Stro        Sample1   0.1077355        0.4070769     0.1331186
B           Sample2   0.186215537      0.08291817    0.1840853
Mac         Sample2   0.184085292      0.08291817    0.1840853
NK          Sample2   0.375349920      0.08291817    0.1840853
Neu         Sample2   0.247664923      0.08291817    0.1840853
Stro        Sample2   0.006684328      0.08291817    0.1840853

Answer 1

使用基础 R 的一种方式：

mylist <- lapply(1:2, function(i) {
  #this is the important bit where you extract the corresponding elements
  #of sample 1 first and sample 2 second.
  df <- data.frame(lapply(my_lol, '[', i))
  names(df) <- c('CoolFactorScore', 'CRT', 'SR', 'Sample')
  df$CellType <- rownames(df)
  row.names(df) <- NULL
  df
})

do.call(rbind, mylist)

输出：

  CoolFactorScore       CRT         SR  Sample CellType
1      0.164477631 0.1331186 0.40707688 Sample1        B
2      0.198253819 0.1331186 0.40707688 Sample1      Mac
3      0.396414447 0.1331186 0.40707688 Sample1       NK
4      0.133118604 0.1331186 0.40707688 Sample1      Neu
5      0.107735498 0.1331186 0.40707688 Sample1     Stro
6      0.186215537 0.1840853 0.08291817 Sample2        B
7      0.184085292 0.1840853 0.08291817 Sample2      Mac
8      0.375349920 0.1840853 0.08291817 Sample2       NK
9      0.247664923 0.1840853 0.08291817 Sample2      Neu
10     0.006684328 0.1840853 0.08291817 Sample2     Stro

Answer 2

这是一个不太优雅的方法：

int <- lapply(1:2, function(x) do.call(data.frame, 
              c(list(CoolFactorScore=my_lol[[1]][[x]]), 
                my_lol[[2]][[x]], 
                list(Sample=my_lol[[3]][[x]])))) 
do.call(rbind, int)

      CoolFactorScore       crt         sr  Sample
B         0.164477631 0.1331186 0.40707688 Sample1
Mac       0.198253819 0.1331186 0.40707688 Sample1
NK        0.396414447 0.1331186 0.40707688 Sample1
Neu       0.133118604 0.1331186 0.40707688 Sample1
Stro      0.107735498 0.1331186 0.40707688 Sample1
B1        0.186215537 0.1840853 0.08291817 Sample2
Mac1      0.184085292 0.1840853 0.08291817 Sample2
NK1       0.375349920 0.1840853 0.08291817 Sample2
Neu1      0.247664923 0.1840853 0.08291817 Sample2
Stro1     0.006684328 0.1840853 0.08291817 Sample2

Answer 3

这是一个使用 data.table 包的功能的无循环解决方案。

library(data.table)

第 1 步：解开列表

unlist(my_lol) -> tmp1

第 2 步：转置并将其转换为 data.table
这样，您将获得可以由原始数据组成的最宽表。应根据要求将其转换（在进一步的步骤中）为长表。

as.data.table(t(tmp1)) -> tmp2

第 3 步：需要手动将“sample_names1”和“sample_names2”转换为“Sample”。
如果您想泛化到多个 sample_names 值，则应根据可能值的语法修改此步骤。（此版本适用于以下 sample_names 值语法：'Sample1'、'Sample2 '、'Sample3' 等等。）

names(tmp2) <- gsub('sample_names\\d+', 'Sample', names(tmp2))

第四步：根据tmp2表的字段名创建度量字段名

measure <- unique(names(tmp2))

第 5 步：从宽表 (tmp2) 创建更长的表 (tmp3)

tmp3 <- melt(tmp2, 
             measure.vars = patterns(measure), 
             value.name = measure)

第 6 步：根据请求重命名列

names(tmp3) <- gsub('coolfactor_score.', '', names(tmp3))
names(tmp3) <- gsub('sr_crt.', '', names(tmp3))
setnames(tmp3, 'crt', 'CRT')
setnames(tmp3, 'sr', 'SR')

第 7 步：从 tmp3 创建更长的表（mylist）

mylist <- melt(tmp3,
               id.vars = c('Sample',
                           'CRT',
                           'SR'),
               measure.vars = c('B', 
                                'Mac',  
                                'NK',   
                                'Neu',
                                'Stro'),
               value.name = 'CoolFactorScore',
               variable.name = 'CellType')

第 8 步：根据请求重新排序列

setcolorder(mylist, c('CellType', 'Sample', 'CoolFactorScore', 'SR', 'CRT'))

第 9 步：根据请求重新排序行

mylist <- mylist[order(Sample, CellType)]