将多索引添加到 Pandas 数据帧并保持当前索引
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Add multi-index to pandas dataframe and keep current index
提问by TheChymera
I am trying to merge time-course data from different participants. I am iteratively extracting a dataframe per participant and concatenating them at the end of the loop. Before I concatenate, I would like to add the ID of my participants to an additional index.
我正在尝试合并来自不同参与者的时间课程数据。我迭代地为每个参与者提取一个数据帧，并在循环结束时将它们连接起来。在连接之前，我想将参与者的 ID 添加到附加索引中。
This seems REALLY straightforward, but I was unable to find anything on this issue :(
这看起来真的很简单，但我在这个问题上找不到任何东西:(
I would like to turn this
我想转这个
col
0 1
1 1.1
2 NaN
Into:
进入：
col
ID 0 1
1 1.1
2 NaN
I know I could make a new index like:
我知道我可以创建一个新索引，例如：
multindex = [np.array(ID*len(data)),np.array(np.arange(len(data)))]
But that's inelegant without end, and - seeing as I am measuring with high frequency over half an hour - would even get kind of slow :/
但那是无止境的不优雅，而且 - 看到我在半小时内高频测量 - 甚至会变得有点慢：/
I would like to mention that I have recently found my question to be a duplicate of this other question. However mine apparently has more upvotes and better answers. “Prepend” apparently doesn't seem to draw as many hits.
我想提一下，我最近发现我的问题与另一个问题重复。然而，我的显然有更多的赞成和更好的答案。“Prepend”显然没有吸引那么多点击。
回答by HYRY
Maybe you can use keysargument of concat:
也许您可以使用以下keys参数concat：
import numpy as np
import pandas as pd
df1 = pd.DataFrame(np.random.rand(3, 2))
df2 = pd.DataFrame(np.random.rand(4, 2))
df3 = pd.DataFrame(np.random.rand(5, 2))
print pd.concat([df1, df2, df3], keys=["A", "B", "C"])
output:
输出：
0 1
A 0 0.863774 0.794880
1 0.578503 0.418619
2 0.215317 0.146167
B 0 0.655829 0.116917
1 0.862316 0.812847
2 0.500126 0.689218
3 0.653439 0.270427
C 0 0.825213 0.882963
1 0.579436 0.332047
2 0.456948 0.718893
3 0.795074 0.826773
4 0.049676 0.697471
If you want to append other dataframes later:
如果您想稍后附加其他数据帧：
df4 = pd.DataFrame(np.random.rand(6, 2))
pd.concat([df, pd.concat([df4], keys=["D"])])
