通过使用 Python 在两个 excel 中找出其他事务

Question

我有 2 个 excel csv 文件，如下所示

df1 =  {'Transaction_Name':['SC-001_Homepage', 'SC-002_Homepage', 'SC-001_Signinlink'], 'Count': [1, 0, 2]}
df1 = pd.DataFrame(df1, columns=df1.keys())
df2 =  {'Transaction_Name':['SC-001_Homepage', 'SC-002_Homepage', 'SC-001_Signinlink', 'SC-002_Signinlink'], 'Count': [2, 1, 2, 1]}
df2 = pd.DataFrame(df2, columns=df2.keys())

在 df2 中，我可以看到有一个名为"SC-002_Signinlink"的额外事务，该事务在 df1 中不存在。有人可以帮我如何仅找到那些额外的交易并将其打印到文件中吗？

到目前为止，我已经完成了以下工作来获取交易......

merged_df = pd.merge(df1, df2, on = 'Transaction_Name', suffixes=('_df1', '_df2'), how='outer')

Answer 1

在合并中使用指标=True：

df1 =  {'Transaction_Name':['SC-001_Homepage', 'SC-002_Homepage', 'SC-001_Signinlink'], 'Count': [1, 0, 2]}
df1 = pd.DataFrame(df1, columns=df1.keys())
df2 =  {'Transaction_Name':['SC-001_Homepage', 'SC-002_Homepage', 'SC-001_Signinlink', 'SC-002_Signinlink'], 'Count': [2, 1, 2, 1]}
df2 = pd.DataFrame(df2, columns=df2.keys())
df = pd.merge(df1, df2, on='Transaction_Name', how='outer', indicator=True)
# As we do not merge on Count, we have 2 count columns (Count_x & Count_y)
# So we create a Count column which is the addition of the 2
df.Count_x = df.Count_x.fillna(0)
df.Count_y = df.Count_y.fillna(0)
print(df.dtypes)
df['Count'] = df.Count_x + df.Count_y
df = df.loc[df._merge != 'both', ['Transaction_Name', 'Count']]
print(df)
# Missing transactions list :
print(df.Transaction_Name.values.tolist())

打印输出(df.dtypes(

Transaction_Name      object
Count_x              float64
Count_y                int64
_merge              category
dtype: object

打印输出(DF(

    Transaction_Name  Count
3  SC-002_Signinlink    1.0

打印输出(DF.Transaction_Name.values.tolist(((

['SC-002_Signinlink']