当隐含ID列时，合并csv文件中的许多数据帧吗? [英] Merge many data frames from csv files, when ID column is implied?

问题描述

我想将一堆数据帧合并在一起(因为如果您只处理w/a，似乎很多操作会更容易，但是如果我做错了，请更正我).

I'd like to merge a bunch of data frames together (because it seems many operations are easier if you're only dealing w/ one, but correct me if I'm wrong).

目前，我有一个这样的数据帧:

Currently I have one data frame like this:

ID, var1, var2
A,  2,    2
B,  4,    5
.
.
Z,  3,    2

每个ID都在一行中，并带有多个单独的测量值

Each ID is on a single row w/ several single measurements

我还有一个csv文件，其中包含对每个ID的重复测量，例如:

I also have a csv file w/ repeated measurement for each ID, like:

文件名= ID_B.csv

filename = ID_B.csv

time, var4, var5
0,    1,    2
1,    4,    5
2,    1,    6
...

我想要的是:

ID, time, va1, var2, var4, var5
...
B,  0,    4,   5,    1,    2,
B,  1,    4,   5,    4,    5,
B,  2,    4,   5,    1,    6,
...

我真的不在乎列顺序.我能想到的唯一解决方案是将ID列添加到每个csv文件，然后遍历它们多次调用merge().有没有更优雅的方法?

I don't really care about the column order. The only solution I can think of is to add the ID column to each csv file then loop through them calling merge() several times. Is there a more elegant approach?

推荐答案

我的理解是，您需要从文件名中提取ID，然后将导入的csv与现有数据框合并.

My understanding is that you need to extract the ID from the filename, and then merge the imported csv with the existing dataframe.

df1 <- read.csv(textConnection("ID, var1, var2
A,  2,    2
B,  4,    5"))

# assuming the imported csv-files are in working directory
filenames <- list.files(getwd(), pattern = "ID_[A-Z].csv")

# extract ID from filename
ids <- gsub("ID_([A-Z]).csv", "\\1", filenames)

# import csv-files and append ID
library(plyr)
import <- mdply(filenames, read.csv)
import$ID <- ids[import$Var1]
import$Var1 <- NULL

# merge imported csv-files and the existing dataframe
merge(df1, import)  

结果:

ID var1 var2 time var4 var5
1  B    4    5    0    1    2
2  B    4    5    1    4    5
3  B    4    5    2    1    6

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