Question

如何使用python代码实现低于预期的结果？

[DF1]                                    [DF2]

**Name** **Configure**                 **Name**
MD0001       2G                         MD0001
MD0002       3G                         MD0001
MD0003       4G                         MD0001
                                        MD0002
                                        MD0002
                                        MD0003
                                        MD0003
                                        MD0003

预期结果：

Name    Configure
MD0001  2G
MD0001  2G
MD0001  2G
MD0002  3G
MD0002  3G
MD0003  4G
MD0003  4G
MD0003  4G

到目前为止，这是我的代码：

data_xlsx = pd.read_excel(data,skiprows=1,sheet_name='KPI')
new_xlsx = pd.read_excel(new, skiprows=1,sheet_name='KPI')
data_df = pd.Dataframe[data_xlsx ]
new_xlsx = pd.Dataframe[new_xlsx ]

Answer 1

您应该使用合并或联接。这是熊猫完成类似SQL的联接的方式。

# mock up the test dataframes
df1 = pd.DataFrame.from_records(
    columns=["Name", "Configure"],
    data = [
        ("MD0001", "2G"),
        ("MD0002", "3G"),
        ("MD0003", "4G")
    ]
)

df2 = pd.DataFrame.from_records(
    columns = ["Name"],
    data = [
        ("MD0001",),
        ("MD0001",),
        ("MD0001",),
        ("MD0002",),
        ("MD0002",),
        ("MD0003",),
        ("MD0003",),
        ("MD0003",)
    ]
)

# index df1 on Name
df1 = df1.set_index("Name")

# then join it to df2
df2.join(df1['Configure'], on="Name")

输出：

    Name    Configure
0   MD0001  2G
1   MD0001  2G
2   MD0001  2G
3   MD0002  3G
4   MD0002  3G
5   MD0003  4G
6   MD0003  4G
7   MD0003  4G

将数据框与列值匹配相结合

1 个答案: