与R中的多个数据帧相同的功能 [英] Same function over multiple data frames in R

问题描述

我对R很新，这是一个非常简单的问题。我发现了很多类似的东西，我想要但不完全是这样。基本上我有多个数据帧，我只想在所有数据帧中运行相同的功能。一个for循环可以工作，但我不知道如何正确地设置它来调用数据帧。似乎最喜欢用R的lapply方法。我已经玩了get函数，也没有用。如果这是一个重复的问题，我很抱歉。任何帮助将不胜感激！

这是我的简化示例：
2数据框：df1，df2

  df1 
开始停止ID 
 0 10 x 
 10 20 y 
 20 30 z 
 
 df2 
开始停止ID 
 0 10 a 
 10 20 b 
 20 30 c 
  

我想要的是一个第四列，平均起始和停止两个dfs

  df1 
开始停止ID平均
 0 10 x 5 
 10 20 y 15 
 20 30 z 25 
  

我可以一次执行一个数据框：

  df1 $ Avg <  -  rowMeans（subset（df1，select = c（start，stop）），na.rm = TRUE）
  

但是我想在所有数据框上运行它。

任何帮助将不胜感激！

解决方案

创建数据框列表，然后使用lapply将功能应用于它们。

  df.list<  -  list（df1，df2，...）
 res<  -  lapply df.list，function（x）rowMeans（subset（x，select = c（start，stop）），na.rm = TRUE））
＃保留原始data.frame也
 res< ;  -  lapply（df.list，function（x）cbind（x，rowmean= rowMeans（subset（x，select = c（start，stop）），na.rm = TRUE）））
  

然后，lapply将按顺序将每个数据框中的数据输入x。

I am new to R, and this is a very simple question. I've found a lot of similar things to what I want but not exactly it. Basically I have multiple data frames and I simply want to run the same function across all of them. A for-loop could work but I'm not sure how to set it up properly to call data frames. It also seems most prefer the lapply approach with R. I've played with the get function as well to no avail. I apologize if this is a duplicated question. Any help would be greatly appreciated!

Here's my over simplified example: 2 data frames: df1, df2

df1
start stop ID
0     10   x
10    20   y
20    30   z

df2
start stop ID
0     10   a
10    20   b
20    30   c

what I want is a 4th column with the average of start and stop for both dfs

df1
start stop ID  Avg
0     10   x    5 
10    20   y    15
20    30   z    25

I can do this one data frame at a time with:

df1$Avg <- rowMeans(subset(df1, select = c(start, stop)), na.rm = TRUE)

but I want to run it on all of the dataframes.

Any help would be greatly appreciated!

解决方案

Make a list of data frames then use lapply to apply the function to them all.

df.list <- list(df1,df2,...)
res <- lapply(df.list, function(x) rowMeans(subset(x, select = c(start, stop)), na.rm = TRUE))
# to keep the original data.frame also
res <- lapply(df.list, function(x) cbind(x,"rowmean"=rowMeans(subset(x, select = c(start, stop)), na.rm = TRUE)))

The lapply will then feed in each data frame as x sequentially.

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