Python 扩展数据帧中的行

我有以下数据：

product Sales_band  Hour_id sales
prod_1  HIGH           1    200
prod_1  HIGH           3    100
prod_1  HIGH           4    300
prod_1  VERY HIGH      2    100
prod_1  VERY HIGH      5    253
prod_1  VERY HIGH      6    234

要根据小时id值添加行。hour\u id变量可以取值范围为1到10。因此，上面相同的数据将在缺少小时ID的地方展开。虚拟输出为：（缺少小时id时sales=0）

如何使用python dataframe实现这一点。

与以下一起使用：

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每个产品和销售带应该有10行吗？是的，这应该是非常理想的最终输出。成功了。将阅读有关set_索引和reindex的更多信息。

product Sales_band  Hour_id sales
prod_1  HIGH           1    200
prod_1  HIGH           2    0
prod_1  HIGH           3    100
prod_1  HIGH           4    300
prod_1  HIGH           5    0
prod_1  HIGH           6    0
prod_1  HIGH           7    0
prod_1  HIGH           8    0
prod_1  HIGH           9    0
prod_1  HIGH           10   0
prod_1  VERY HIGH      1    0
prod_1  VERY HIGH      2    100
prod_1  VERY HIGH      3    0
prod_1  VERY HIGH      4    0
prod_1  VERY HIGH      5    253
prod_1  VERY HIGH      6    234
prod_1  VERY HIGH      7    0
prod_1  VERY HIGH      8    0
prod_1  VERY HIGH      9    0
prod_1  VERY HIGH      10   0

print (df.groupby(['product','Sales_band'])['Hour_id','sales']
         .apply(lambda x: x.set_index('Hour_id').reindex(range(1, 11), fill_value=0))
         .reset_index())

   product Sales_band  Hour_id  sales
0   prod_1       HIGH        1    200
1   prod_1       HIGH        2      0
2   prod_1       HIGH        3    100
3   prod_1       HIGH        4    300
4   prod_1       HIGH        5      0
5   prod_1       HIGH        6      0
6   prod_1       HIGH        7      0
7   prod_1       HIGH        8      0
8   prod_1       HIGH        9      0
9   prod_1       HIGH       10      0
10  prod_1  VERY HIGH        1      0
11  prod_1  VERY HIGH        2    100
12  prod_1  VERY HIGH        3      0
13  prod_1  VERY HIGH        4      0
14  prod_1  VERY HIGH        5    253
15  prod_1  VERY HIGH        6    234
16  prod_1  VERY HIGH        7      0
17  prod_1  VERY HIGH        8      0
18  prod_1  VERY HIGH        9      0
19  prod_1  VERY HIGH       10      0