Question

我正在尝试执行以下操作：

给出df1中的一行，如果str（row ['code']）在df2 ['code']的任何行中，那么我希望df2 ['lamer_url_1']和df2 ['shopee_url_1]中的所有行']取自df1的相应值。然后继续进行df1 ['code'] ...的下一行...

'''

==============

初始表格：

df1

     code                  lamer_url_1                 shopee_url_1

0  L61B18H089                       b                            a

1  L61S19H014                       e                            d

2  L61S19H015                       z                            y

df2

  code             lamer_url_1   shopee_url_1   lamer_url_2  shopee_url_2

0 L61B18H089-F1424         NaN           NaN          NaN           NaN

1 L61S19H014-S1500         NaN           NaN          NaN           NaN

2 L61B18H089-F1424         NaN           NaN          NaN           NaN

==============

预期输出：

df2

   code              lamer_url_1  shopee_url_1  lamer_url_2  shopee_url_2
0  L61B18H089-F1424           b             a          NaN           NaN

1  L61S19H014-S1500           e             d          NaN           NaN

2  L61B18H089-F1424           b             a          NaN           NaN

'''

Answer 1

我假设来自“ df2”的“代码”的共同部分是“-”之前的字符。我还假设从“ df1”开始，我们想要“ lamer_url_1”，“ shopee_url_1”，从“ df2”开始，我们想要“ lamer_url_2”，“ shopee_url_2”（如果我输入错了，请在注释中纠正我，以便我可以完善代码）：

df1.set_index(df1['code'], inplace=True)
df2.set_index(df2['code'].apply(lambda x: x.split('-')[0]), inplace=True)
df2.index.names = ['code_join']

df3 = pd.merge(df2[['code', 'lamer_url_2', 'shopee_url_2']],
               df1[['lamer_url_1', 'shopee_url_1']],
               left_index=True, right_index=True)

检查一个数据框单元格是否包含另一个数据框单元格中的值

1 个答案: