在R或python中基于一列和不同顺序连接文件

我有3个选项卡分隔的文件，如以下3个示例：

示例文件：

AB  45.2    4.56    0.21
FG  78.1    54.1    36.1
HG  98.1    25.0    12.6
TR  1.2 3.25    65.1


TR  5.2 41.6    10.21
HG  8.1 23.1    56.1
FG  9   32.0    32.6
AB  12.2    31.25   5.1


HG  15.2    21.6    20.21
TR  31.1    32.1    66.1
AB  12.1    12.0    62.6
FG  11.3    31.25   54.1

它们中的第一列有相似的项目，但顺序不同。我想根据第1列加入文件，并创建一个与预期输出类似的新文件：

预期产量

AB  45.2    4.56    0.21    12.2    31.25   5.1 12.1    12.0    62.6
FG  78.1    54.1    36.1    9   32.0    32.6    11.3    31.25   54.1
HG  98.1    25.0    12.6    8.1 23.1    56.1    15.2    21.6    20.21
TR  1.2 3.25    65.1    5.2 41.6    10.21   31.1    32.1    66.1

---

我试图在

R和pandas

中使用

join

函数，但它们没有返回预期的输出。你知道我如何在python或R中做到这一点吗？

在R中，你可以使用

Reduce

和

merge

Reduce(function(x, y) merge(x, y, by = 'V1'), list(df1, df2, df3))
#If there are lot of dataframes use `mget` and `ls`
#Reduce(function(x, y) merge(x, y, by = 'V1'), mget(ls(pattern = "df\\d+")))

#  V1   V2    V3    V4   V5   V6   V7   V8   V9  V10
#1 AB 45.2  4.56  0.21 12.2 31.2  5.1 12.1 12.0 62.6
#2 FG 78.1 54.10 36.10  9.0 32.0 32.6 11.3 31.2 54.1
#3 HG 98.1 25.00 12.60  8.1 23.1 56.1 15.2 21.6 20.2
#4 TR  1.2  3.25 65.10  5.2 41.6 10.2 31.1 32.1 66.1

数据

其中，数据中的一列在所有数据帧中都是通用的，而其余的数据帧具有不同的名称

df1 <- structure(list(V1 = structure(1:4, .Label = c("AB", "FG", "HG", 
"TR"), class = "factor"), V2 = c(45.2, 78.1, 98.1, 1.2), V3 = c(4.56, 
54.1, 25, 3.25), V4 = c(0.21, 36.1, 12.6, 65.1)), 
class = "data.frame", row.names = c(NA, -4L))

df2 <- structure(list(V1 = structure(4:1, .Label = c("AB", "FG", "HG", 
"TR"), class = "factor"), V5 = c(5.2, 8.1, 9, 12.2), V6 = c(41.6, 
23.1, 32, 31.25), V7 = c(10.21, 56.1, 32.6, 5.1)), class = "data.frame", 
row.names = c(NA, -4L))

df3 <- structure(list(V1 = structure(c(3L, 4L, 1L, 2L), .Label = c("AB", 
"FG", "HG", "TR"), class = "factor"), V8 = c(15.2, 31.1, 12.1, 
11.3), V9 = c(21.6, 32.1, 12, 31.25), V10 = c(20.21, 66.1, 62.6, 
54.1)), class = "data.frame", row.names = c(NA, -4L))

---

df1我们可以在
tidyverse
中使用
reduce
和
internal\u-join
（在
R
中）

数据
df1最好是显示您的代码，看起来您需要
pd.concat（[df1，df2，df3]，axis=1）
它在加入之前对列进行排序吗？它将沿着索引加入
library(dplyr)
library(purrr)
mget(paste0('df', 1:3)) %>%
   reduce(inner_join)

df1 <- structure(list(V1 = structure(1:4, .Label = c("AB", "FG", "HG", 
"TR"), class = "factor"), V2 = c(45.2, 78.1, 98.1, 1.2), V3 = c(4.56, 
54.1, 25, 3.25), V4 = c(0.21, 36.1, 12.6, 65.1)), 
class = "data.frame", row.names = c(NA, -4L))

df2 <- structure(list(V1 = structure(4:1, .Label = c("AB", "FG", "HG", 
"TR"), class = "factor"), V5 = c(5.2, 8.1, 9, 12.2), V6 = c(41.6, 
23.1, 32, 31.25), V7 = c(10.21, 56.1, 32.6, 5.1)), class = "data.frame", 
row.names = c(NA, -4L))

df3 <- structure(list(V1 = structure(c(3L, 4L, 1L, 2L), .Label = c("AB", 
"FG", "HG", "TR"), class = "factor"), V8 = c(15.2, 31.1, 12.1, 
11.3), V9 = c(21.6, 32.1, 12, 31.25), V10 = c(20.21, 66.1, 62.6, 
54.1)), class = "data.frame", row.names = c(NA, -4L))