pandas 如何重新索引多索引数据帧
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How to reindex a MultiIndex dataframe
提问by BradB
Is there a way to reindex two dataframes (of differing levels) so that they share a common index across all levels?
有没有办法重新索引两个数据帧（不同级别），以便它们在所有级别共享一个公共索引？
Demo:
演示：
Create a basic Dataframe named 'A':
创建一个名为“A”的基本数据框：
index = np.array(['AUD','BRL','CAD','EUR','INR'])
data = np.random.randint(1, 20, (5,5))
A = pd.DataFrame(data=data, index=index, columns=index)
Create a MultiIndex Dataframe named 'B':
创建一个名为“B”的多索引数据帧：
np.random.seed(42)
midx1 = pd.MultiIndex.from_product([['Bank_1', 'Bank_2'],
['AUD','CAD','EUR']], names=['Bank', 'Curency'])
B = pd.DataFrame(np.random.randint(10,25,6), midx1)
B.columns = ['Notional']
Basic DF:
基本DF：
>>> Dataframe A:
AUD BRL CAD EUR INR
AUD 7 19 11 11 4
BRL 8 3 2 12 6
CAD 2 1 12 12 17
EUR 10 16 15 15 19
INR 12 3 5 19 7
MultiIndex DF:
多索引DF：
>>> Dataframe B:
Notional
Bank Curency
Bank_1 AUD 16
CAD 13
EUR 22
Bank_2 AUD 24
CAD 20
EUR 17
The goal is to:
目标是：
1) reindex B so that its currency level includes each currency in A's index. B would then look like this (see BRL and INR included, their Notional values are not important):
1) 重新索引 B，使其货币水平包括 A 指数中的每种货币。B 看起来像这样（见 BRL 和 INR，它们的名义值并不重要）：
Notional
Bank Curency
Bank_1 AUD 16
CAD 13
EUR 22
BRL 0
INR 0
Bank_2 AUD 24
CAD 20
EUR 17
BRL 0
INR 0
2) reindex A so that it includes each Bank from the first level of B's index. A would then look like this:
2) 重新索引 A，使其包括 B 索引的第一级中的每个银行。A 看起来像这样：
AUD BRL CAD EUR INR
Bank_1 AUD 7 19 11 11 4
BRL 8 3 2 12 6
CAD 2 1 12 12 17
EUR 10 16 15 15 19
INR 12 3 5 19 7
Bank_2 AUD 7 19 11 11 4
BRL 8 3 2 12 6
CAD 2 1 12 12 17
EUR 10 16 15 15 19
INR 12 3 5 19 7
The application of this will be on much larger dataframes so I need a pythonic way to do this.
这个的应用将在更大的数据帧上，所以我需要一种pythonic的方式来做到这一点。
For context, ultimately I want to multiply A and B. I am trying to reindex to get matching indices as that was shown as a clean way to multiply dataframes of various index levels here: Pandas multiply dataframes with multiindex and overlapping index levels
对于上下文，最终我想将 A 和 B 相乘。我正在尝试重新索引以获得匹配的索引，因为这被显示为一种将各种索引级别的数据帧相乘的干净方法： Pandas 将数据帧与多索引和重叠索引级别相乘
Thank you for any help.
感谢您的任何帮助。
回答by YOBEN_S
To get the B using reindex
得到 B 使用 reindex
B.reindex( pd.MultiIndex.from_product([B.index.levels[0],
A.index], names=['Bank', 'Curency']),fill_value=0)
Out[62]:
Notional
Bank Curency
Bank_1 AUD 16
BRL 0
CAD 13
EUR 22
INR 0
Bank_2 AUD 24
BRL 0
CAD 20
EUR 17
INR 0
To get the A using concat
得到 A 使用 concat
pd.concat([A]*2,keys=B.index.levels[0])
Out[69]:
AUD BRL CAD EUR INR
Bank
Bank_1 AUD 10 5 10 14 1
BRL 17 1 14 10 8
CAD 3 7 3 15 2
EUR 17 1 15 2 16
INR 7 15 6 7 4
Bank_2 AUD 10 5 10 14 1
BRL 17 1 14 10 8
CAD 3 7 3 15 2
EUR 17 1 15 2 16
INR 7 15 6 7 4
