python - Pandas csv itertools 组合

Question

我的数据集看起来像这样，

Col1    Col2    Col3
A       10      x1
B       100     x2
C       1000    x3

这就是我的输出，

Col1    Col2    Col3    Col4    Col5    Col6    Col7    Col8    Col9
A       10      x1      Empty   Empty   Empty   Empty   Empty   Empty
B       100     x2      Empty   Empty   Empty   Empty   Empty   Empty
C       1000    x3      Empty   Empty   Empty   Empty   Empty   Empty
A       10      x1      B       100     x2      Empty   Empty   Empty
B       100     x2      C       1000    x3      Empty   Empty   Empty
A       10      x1      B       100     x2      C       1000    x3

感谢本网站的帮助，这可以通过 -

来完成

arr = list(itertools.chain.from_iterable(
[[j for i in el for j in i] for el in itertools.combinations(df.values.tolist(), i)]
for i in range(1, len(df)+1)
)
)

pd.DataFrame(arr)

但是如果数据集如下，

        Col1 Col2   Col3   Structure
        A    10     x1     1
        B    100    x2     1
        C    1000   x3     2

输出需要是这样的 -

  Col1    Col2    Col3      Col4    Col5    Col6    Col7    Col8    Col9    Answer
    A       10      x1      Empty   Empty   Empty   Empty   Empty   Empty   No
    B       100     x2      Empty   Empty   Empty   Empty   Empty   Empty   No
    C       1000    x3      Empty   Empty   Empty   Empty   Empty   Empty   Yes
    A       10      x1      B       100     x2      Empty   Empty   Empty   Yes
    B       100     x2      C       1000    x3      Empty   Empty   Empty   No
    A       10      x1      B       100     x2      C       1000    x3      No

这基本上是说 A 和 B 是"is"，因为它们处于相同的结构中，而 C 本身是"is"，因为它本身在结构中。 所有其他行(例如 A、B、ABC)均为“否”，因为它们不在同一结构中。如何获得上面想要的表格？

代码，

arr = list(itertools.chain.from_iterable(
[[j for i in el for j in i] for el in itertools.combinations(df.values.tolist(), i)]
for i in range(1, len(df)+1)
)
)

pd.DataFrame(arr)

给我这个输出，

    Col1    Col2    Col3    Col4    Col5    Col6    Col7    Col8    Col9
    A       10      x1      Empty   Empty   Empty   Empty   Empty   Empty
    B       100     x2      Empty   Empty   Empty   Empty   Empty   Empty
    C       1000    x3      Empty   Empty   Empty   Empty   Empty   Empty
    A       10      x1      B       100     x2      Empty   Empty   Empty
    B       100     x2      C       1000    x3      Empty   Empty   Empty
    A       10      x1      B       100     x2      C       1000    x3

如何将“答案”列添加到此输出以获得最终表格？

Answer 1

由于 DataFrame 的结构，我们知道当我们应用 itertools.combinations 时，Structure 列将首先显示在第三列中，然后每隔四个列显示一次以下栏目:

  0     1   2   3     4       5     6    7     8       9     10   11
0  A    10  x1   1  None     NaN  None  NaN  None     NaN  None  NaN
1  B   100  x2   1  None     NaN  None  NaN  None     NaN  None  NaN
2  C  1000  x3   2  None     NaN  None  NaN  None     NaN  None  NaN
3  A    10  x1   1     B   100.0    x2  1.0  None     NaN  None  NaN
4  A    10  x1   1     C  1000.0    x3  2.0  None     NaN  None  NaN
5  B   100  x2   1     C  1000.0    x3  2.0  None     NaN  None  NaN
6  A    10  x1   1     B   100.0    x2  1.0     C  1000.0    x3  2.0

我们可以使用它来仅索引 Structure 列，检查它们是否包含组的所有成员，然后删除它们:

checker = df.groupby('Structure').size().to_dict()

def helper(row):                                               
    u = row[~row.isnull()].values                              
    return (len(np.unique(u)) == 1) & (checker[u[0]] == len(u))

s = out[out.columns[3::4]].apply(helper, 1).replace({False: 'No', True: 'Yes'})

0     No
1     No
2    Yes
3    Yes
4     No
5     No
6     No
dtype: object

删除其他列并分配给 DataFrame:

out.drop(out.columns[3::4], 1).assign(final=s)

   0     1   2     4       5     6     8       9    10 final
0  A    10  x1  None     NaN  None  None     NaN  None    No
1  B   100  x2  None     NaN  None  None     NaN  None    No
2  C  1000  x3  None     NaN  None  None     NaN  None   Yes
3  A    10  x1     B   100.0    x2  None     NaN  None   Yes
4  A    10  x1     C  1000.0    x3  None     NaN  None    No
5  B   100  x2     C  1000.0    x3  None     NaN  None    No
6  A    10  x1     B   100.0    x2     C  1000.0    x3    No