我想通過索引減去兩個資料幀：
# importing pandas as pd
import pandas as pd
# Creating the second dataframe
df1 = pd.DataFrame({"Type":['T1', 'T2', 'T3', 'T4', 'T5'],
"A":[10, 11, 7, 8, 5],
"B":[21, 5, 32, 4, 6],
"C":[11, 21, 23, 7, 9],
"D":[1, 5, 3, 8, 6]},
index =["2001", "2002", "2003", "2004", "2005"])
df1
# Creating the first dataframe
df2 = pd.DataFrame({"A":[1, 2, 2, 2],
"B":[3, 2, 4, 3],
"C":[2, 2, 7, 3],
"D":[1, 3, 2, 1]},
index =["2000", "2002", "2003", "2004"])
df2
# Desired
df = pd.DataFrame({"Type":['T1', 'T2', 'T3', 'T4', 'T5'],
"A":[10, 9, 5, 6, 5],
"B":[21, 3, 28, 1, 6],
"C":[11, 19, 16, 4, 9],
"D":[1, 2, 1, 7, 5]},
index =["2001", "2002", "2003", "2004", "2005"])
df
df1.subtract(df2)
但是，它在某些情況下會回傳 NA，如果不可扣除，我想保留第一個 df1 的值。
uj5u.com熱心網友回復：
您可以使用以下方法處理 NaN：
df1.subtract(df2).combine_first(df1).dropna(how='all')
輸出：
A B C D Type
2001 10.0 21.0 11.0 1.0 T1
2002 9.0 3.0 19.0 2.0 T2
2003 5.0 28.0 16.0 1.0 T3
2004 6.0 1.0 4.0 7.0 T4
2005 5.0 6.0 9.0 6.0 T5
uj5u.com熱心網友回復：
您可以使用select_dtypes選擇正確的資料型別，然后減去reindex資料：
(df1.select_dtypes(include='number')
.sub(df2.reindex(df1.index, fill_value=0))
.join(df1.select_dtypes(exclude='number'))
)
輸出：
A B C D Type
2001 10 21 11 1 T1
2002 9 3 19 2 T2
2003 5 28 16 1 T3
2004 6 1 4 7 T4
2005 5 6 9 6 T5
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