我正在使用 pandas concat 來比較 2 個具有相同列和行的資料框：
import pandas as pd
df=pd.read_csv(r'C:\Users\compare\T1.csv')
df2=pd.read_csv(r'C:\Users\compare\T2.csv')
index=['contract','RB','payee','fund']
df_all = pd.concat([df.set_index(index), df2.set_index(index)],
axis='columns', keys=['First', 'Second'])
df_final = df_all.swaplevel(axis='columns')[df.columns[54:56]]
df_final
輸出是：
SD1 SD2
First Second First Second
contract RB payee fund
AG72916Z 2 1 W42 15622.9 15622.9 15622.9 15489.2
4 1 W44 14697.8 14697.8 14697.8 14572.1
8 1 W48 7388.56 7388.56 7388.56 7325.37
AL0024AZ C3 1 202 226.585 226.59 220.366 220.37
S3 1 204 804.059 804.06 781.99 781.99
我的問題是如何在每個 Second 之后添加一個不同的列，以便我可以輕松地判斷比較結果，輸出應該如下所示：
SD1 SD2
First Second differ First Second differ
contract RB payee fund
AG72916Z 2 1 W42 15622.9 15622.9 0 15622.9 15489.2 133.7
4 1 W44 14697.8 14697.8 0 14697.8 14572.1 125.7
8 1 W48 7388.56 7388.56 0 7388.56 7325.37 63.19
AL0024AZ C3 1 202 226.585 226.59 0.05 220.366 220.37 -0.004
S3 1 204 804.059 804.06 0.01 781.99 781.99 0
uj5u.com熱心網友回復：
有點棘手但有必要繼續訂購：
out = df_final.stack(level=0).assign(Diff=lambda x: x['First'] - x['Second']) \
.stack().unstack(level=[-2, -1])
print(out)
# Output
SD1 SD2
First Second Diff First Second Diff
contract RB payee fund
AG72916Z 2 1 W42 15622.900 15622.90 0.000 15622.900 15489.20 133.700
4 1 W44 14697.800 14697.80 0.000 14697.800 14572.10 125.700
8 1 W48 7388.560 7388.56 0.000 7388.560 7325.37 63.190
AL0024AZ C3 1 202 226.585 226.59 -0.005 220.366 220.37 -0.004
S3 1 204 804.059 804.06 -0.001 781.990 781.99 0.000
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