按预定义列串联/合并数据框列表 [英] Concatenating/Merging List of Dataframes by Predefined columns

问题描述

我有以下数据帧列表:

import pandas as pd
rep1 = pd.DataFrame.from_items([('Probe', ['x', 'y', 'z']), ('Gene', ['foo', 'bar', 'qux']), ('RP1',[1.00,23.22,11.12])], orient='columns')
rep2 = pd.DataFrame.from_items([('Probe', ['x', 'y', 'z']), ('Gene', ['foo', 'bar', 'qux']), ('RP2',[11.33,31.25,22.12])], orient='columns')
rep3 = pd.DataFrame.from_items([('Probe', ['x', 'y', 'z']), ('Gene', ['foo', 'bar', 'qux'])], orient='columns')
tmp = []
tmp.append(rep1)
tmp.append(rep2)
tmp.append(rep3)

# In actuality the DF could be more than 3.

哪个会产生:

In [53]: tmp
Out[53]:
[  Probe Gene    RP1
 0     x  foo   1.00
 1     y  bar  23.22
 2     z  qux  11.12,   Probe Gene    RP2
 0     x  foo  11.33
 1     y  bar  31.25
 2     z  qux  22.12,   Probe Gene
 0     x  foo
 1     y  bar
 2     z  qux]

我想要做的是连接该数据帧列表，以便得到以下结果:

What I want to do is to concatenate that list of dataframes so that it results in this:

  Probe Gene      RP1        RP2
0     x  foo     1.00      11.33
1     y  bar    23.22      31.25
2     z  qux    11.12      22.12

请注意，rep3仅包含两列.在连接的过程中，我们希望将其自动丢弃.

Note that rep3 only contain two columns. In the process of concatenating, we hope to automatically discard it.

我尝试使用此代码，但无济于事.正确的方法是什么?

I tried with this code but no avail. What's the right way to do it?

In [57]: full_df = pd.concat(tmp,axis=1).fillna(0)

In [58]: full_df
Out[58]:
  Probe Gene    RP1 Probe Gene    RP2 Probe Gene
0     x  foo   1.00     x  foo  11.33     x  foo
1     y  bar  23.22     y  bar  31.25     y  bar
2     z  qux  11.12     z  qux  22.12     z  qux

推荐答案

我不确定这是否是正确的方法，但是一种整洁的方法是使用减少:

I'm not sure this is the right way to do this, but a kind-of neat way is to use reduce:

In [11]: reduce(pd.merge, tmp)
Out[11]:
  Probe Gene    RP1    RP2
0     x  foo   1.00  11.33
1     y  bar  23.22  31.25
2     z  qux  11.12  22.12

---

这基本上等同于:

---

This is basically equivalent to:

tmp[0].merge(tmp[1]).merge(tmp[2])...

注意:这意味着如果tmp中有很多DataFrame，它的效率可能不如concat.

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