从许多对象的列表中提取数据框 [英] extracting a dataframe from a list over many objects

问题描述

我在R中有1000多个对象( z )，每个对象包含三个数据帧( df1 ， df2 ， df3 )具有不同的结构.

I have over a 1000 objects (z) in R, each containing three dataframes (df1, df2, df3) with different structures.

z1 $ df1 …… z1000 $ df1

z1 $ df2 … z1000 $ df2

z1 $ df3 … z1000 $ df3

我创建了这些对象的列表(因此list1包含z1到z1000)，并尝试使用 lapply 为所有对象提取一种类型的数据帧( df2 )，然后将它们合并到一个数据框.

I created a list of these objects (list1 thus contains z1 thru z1000) and tried to use lapply to extract one type of dataframe (df2) for all objects, and then merge them to one single dataframe.

对于单个对象，它看起来像这样:

For a single object it would look like this:

df15<- z15$df2 # I transferred the index of z to the extracted df

我尝试使用 lapply 进行了一些编码，而忽略了索引的传输(我可以为此创建另一个列表).但是我不知道应该使用什么功能.

I tried some code with lapply, ignoring the transfer of the index (I can create another list for that). However I don’t know what function I should use.

List2 <- lapply(list1, function(x))

我尝试避免使用循环，因为循环太多了，向量化也快得多.我的想法是我从错误的角度看待它.

I try to avoid using a loop because there's so many and vectorization is so much quicker. I have the idea I'm looking at it from the wrong angle.

后续合并可以如下进行:

Subsequent merging can be done as follows:

merged <- do.call(rbind, list2)

谢谢您的建议.

推荐答案

一个选项可能是使用 lapply 提取 data.frame ，然后使用 bind_rows 来自 dplyr .

One option could be using lapply to extract data.frame and then use bind_rows from dplyr.

## The data
df1 <- data.frame(id = c(1:10), name = c(LETTERS[1:10]), stringsAsFactors = FALSE)
df2 <- data.frame(id = 11:20, name = LETTERS[11:20], stringsAsFactors = FALSE)
df3 <- data.frame(id = 21:30, name = LETTERS[15:24], stringsAsFactors = FALSE)
df4 <- data.frame(id = 121:130, name = LETTERS[15:24], stringsAsFactors = FALSE)

z1 <- list(df1 = df1, df2 = df2, df3 = df3)
z2 <- list(df1 = df1, df2 = df2, df3 = df3)
z3 <- list(df1 = df1, df2 = df2, df3 = df3)
z4 <- list(df1 = df1, df2 = df2, df3 = df4) #DFs can contain different data

# z <- list(z1, z2, z3, z4)
# Dynamically populate list z with many list object
z <- as.list(mget(paste("z",1:4,sep="")))


df1_all <- bind_rows(lapply(z, function(x) x$df1))
df2_all <- bind_rows(lapply(z, function(x) x$df2))
df3_all <- bind_rows(lapply(z, function(x) x$df3))


## Result for df3_all
> tail(df3_all)
##    id name
## 35 125    S
## 36 126    T
## 37 127    U
## 38 128    V
## 39 129    W
## 40 130    X

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