以下是指向原始数据集源的链接: dataset for capacity和dataset for type
或修改版本dataset modified1和dataset modified2
我有两个数据帧要合并:
first_df=pd.DataFrame([['2001','Abu Dhabi','100-','462'],['2001','Abu Dhabi','100','44'],['2001','Abu Dhabi','200','462'],['2001','Dubai','100-','40'],['2001','Dubai','100','30'],['2001','Dubai','200','51'],['2002','Abu Dhabi','100-','300'],['2002','Abu Dhabi','100','220'],['2002','Abu Dhabi','200','56'],['2002','Dubai','100-','55'],['2002','Dubai','100','67'],['2002','Dubai','200','89']],columns=['Year','Emirate','Capacity','Number'])
second_df=pd.DataFrame([['2001','Abu Dhabi','Performed','45'],['2001','Abu Dhabi','Not Performed','76'],['2001','Dubai','Performed','90'],['2001','Dubai','Not Performed','50'],['2002','Abu Dhabi','Performed','78'],['2002','Abu Dhabi','Not Performed','45'],['2002','Dubai','Performed','76'],['2002','Dubai','Not Performed','58']],columns=['Year','Emirate','Type','Value'])
所以我为两个数据帧设置了多索引:
first=first_df.set_index(['Year','Emirate'])
second=second_df.set_index(['Year','Emirate'])
合并后:
merged=first.merge(second,how='outer',right_index=True,left_index=True)
结果如下:
| Year , Emirate | Capacity | count | friday | count |
|:----------------------|:-----------|--------:|:--------------|--------:|
| ('2001', 'Abu Dhabi') | 100- | 462 | Performed | 45 |
| ('2001', 'Abu Dhabi') | 100- | 462 | Not Performed | 76 |
| ('2001', 'Abu Dhabi') | 100 | 44 | Performed | 45 |
| ('2001', 'Abu Dhabi') | 100 | 44 | Not Performed | 76 |
| ('2001', 'Abu Dhabi') | 200 | 657 | Performed | 45 |
| ('2001', 'Abu Dhabi') | 200 | 657 | Not Performed | 76 |
| ('2001', 'Dubai') | 100- | 40 | Performed | 90 |
| ('2001', 'Dubai') | 100- | 40 | Not Performed | 50 |
| ('2001', 'Dubai') | 100 | 30 | Performed | 90 |
| ('2001', 'Dubai') | 100 | 30 | Not Performed | 50 |
| ('2001', 'Dubai') | 200 | 51 | Performed | 90 |
| ('2001', 'Dubai') | 200 | 51 | Not Performed | 50 |
| ('2002', 'Abu Dhabi') | 100- | 300 | Performed | 78 |
| ('2002', 'Abu Dhabi') | 100- | 300 | Not Performed | 45 |
| ('2002', 'Abu Dhabi') | 100 | 220 | Performed | 78 |
| ('2002', 'Abu Dhabi') | 100 | 220 | Not Performed | 45 |
| ('2002', 'Abu Dhabi') | 200 | 56 | Performed | 78 |
| ('2002', 'Abu Dhabi') | 200 | 56 | Not Performed | 45 |
| ('2002', 'Dubai') | 100- | 55 | Performed | 76 |
| ('2002', 'Dubai') | 100- | 55 | Not Performed | 58 |
| ('2002', 'Dubai') | 100 | 67 | Performed | 76 |
| ('2002', 'Dubai') | 100 | 67 | Not Performed | 58 |
| ('2002', 'Dubai') | 200 | 89 | Performed | 76 |
| ('2002', 'Dubai') | 200 | 89 | Not Performed | 58 |
并试图得出以下结果:
joined=pd.concat([first,second])
| Year , Emirate | Capacity | Number | Type | Value |
|:----------------------|:-----------|---------:|:--------------|--------:|
| ('2001', 'Abu Dhabi') | 100- | 462 | nan | nan |
| ('2001', 'Abu Dhabi') | 100 | 44 | nan | nan |
| ('2001', 'Abu Dhabi') | 200 | 657 | nan | nan |
| ('2001', 'Dubai') | 100- | 40 | nan | nan |
| ('2001', 'Dubai') | 100 | 30 | nan | nan |
| ('2001', 'Dubai') | 200 | 51 | nan | nan |
| ('2002', 'Abu Dhabi') | 100- | 300 | nan | nan |
| ('2002', 'Abu Dhabi') | 100 | 220 | nan | nan |
| ('2002', 'Abu Dhabi') | 200 | 56 | nan | nan |
| ('2002', 'Dubai') | 100- | 55 | nan | nan |
| ('2002', 'Dubai') | 100 | 67 | nan | nan |
| ('2002', 'Dubai') | 200 | 89 | nan | nan |
| ('2001', 'Abu Dhabi') | nan | nan | Performed | 45 |
| ('2001', 'Abu Dhabi') | nan | nan | Not Performed | 76 |
| ('2001', 'Dubai') | nan | nan | Performed | 90 |
| ('2001', 'Dubai') | nan | nan | Not Performed | 50 |
| ('2002', 'Abu Dhabi') | nan | nan | Performed | 78 |
| ('2002', 'Abu Dhabi') | nan | nan | Not Performed | 45 |
| ('2002', 'Dubai') | nan | nan | Performed | 76 |
| ('2002', 'Dubai') | nan | nan | Not Performed | 58 |
所以连接在一起的两个数据帧不应该有重复(比如第一次合并)或者下移(比如concat变量)。 有什么解决方案可以使两个数据帧很好地对齐?你知道吗
下面是所需输出的样子:
| | Year | Emirate | Capacity | Number | Type | Value |
|---:|-------:|:----------|:-----------|---------:|:--------------|--------:|
| 0 | | | 100- | 462 | Performed | 45 |
| 1 | | Abu Dhabi | 100 | 44 | Not Performed | 76 |
| 2 | | | 200 | 657 | NaN | nan |
| 3 | 2001 | | 100- | 40 | Performed | 90 |
| 4 | | Dubai | 100 | 30 | Not Performed | 50 |
| 5 | | | 200 | 51 | NaN | nan |
| 6 | | | 100- | 300 | Performed | 78 |
| 7 | | Abu Dhabi | 100 | 220 | Not Performed | 45 |
| 8 | 2002 | | 200 | 56 | NaN | nan |
| 9 | | | 100- | 55 | Performed | 76 |
| 10 | | Dubai | 100 | 67 | Not Performed | 58 |
| 11 | | | 200 | 89 | NaN | nan |
enter code here
我在这里看到了问题所在,当您在
['year','Emirate']
上连接数据时,它会导致交叉连接。e、 g 2001年阿布扎比与2001年阿布扎比在“已执行和未执行”两个数据框中加入。基本上这是m x n关系连接的数据集。除非指定一个可以唯一标识每一行的主键,否则最终会得到相同的结果。你知道吗我假设您的数据还不正确,因为您的预期输出是可能的,但现在不符合您的逻辑。你知道吗
在
second_df
中缺少第三个key column
,即capacity
。如果我们添加这个列并执行left merge
,我们就可以实现预期的输出。你知道吗顺便说一句,我们不需要将列设置为索引,因此解决方案如下所示。你知道吗
输出
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