两个数据帧的有效组合，无需复制和还原| python

Question

我有两个数据帧与数千行，我需要结合成一个数据帧没有重复和逆转。例如：

数据帧1

drug1
drug2
drug3

数据帧2

disease1
disease2
disease3

因此，输出数据帧将是：

输出数据帧

drug1 disease1
drug1 disease2
drug1 disease3
drug2 disease1
drug2 disease2
drug2 disease3 
drug3 disease1
drug3 disease2
drug3 disease3

我不想要包含以下内容的输出组合：

disease1 drug1
drug1 drug1
disease1 disease1 

实际上，我使用pd.merge来尝试它，但是它返回复制和恢复，而且花费了很长时间，因为在数据帧1和2中有数千个

需要帮忙吗

Answer 1

纯粹在pandas中的一种方法是创建MultiIndex from product，然后将其转换为数据帧：

>>> df1
       0
0  drug1
1  drug2
2  drug3
>>> df2
          0
0  disease1
1  disease2
2  disease3

df3 = (pd.MultiIndex.from_product([df1[0],df2[0]])
       .to_frame()
       .reset_index(drop=True))

>>> df3
       0         1
0  drug1  disease1
1  drug1  disease2
2  drug1  disease3
3  drug2  disease1
4  drug2  disease2
5  drug2  disease3
6  drug3  disease1
7  drug3  disease2
8  drug3  disease3

Answer 2

尝试此解决方案：

from pandas import DataFrame, merge

df1['key'] = 1
df2['key'] = 1

result = df1.merge(df2, on='key').drop('key', axis=1)

Answer 3

设置

df1 = pd.DataFrame(dict(col1=[f"drug{i}" for i in range(1, 4)]))
df2 = pd.DataFrame(dict(col2=[f"disease{i}" for i in range(1, 4)]))

---

merge在指定列上

df1.assign(A=1).merge(df2.assign(A=1)).drop('A', 1)

    col1      col2
0  drug1  disease1
1  drug1  disease2
2  drug1  disease3
3  drug2  disease1
4  drug2  disease2
5  drug2  disease3
6  drug3  disease1
7  drug3  disease2
8  drug3  disease3

---

理解力

pd.DataFrame([
    (i, j) for i in df1.col1
           for j in df2.col2
], columns=['col1', 'col2'])

---

pandas.concat

任意两个数据帧的叉积的推广

i = df1.index.repeat(len(df2))
j = np.tile(df2.index, len(df1))

pd.concat([
    df1.loc[i].reset_index(drop=True),
    df2.loc[j].reset_index(drop=True)
], sort=True, axis=1)