将系列添加到作为其他两个交集的数据帧

Question

Suppose I have a dataframe like this

column1   column2
   1        8
   2        9
   20       1 
   4        2
   56
   6
   2

I want a result like this :

column1   column2   column3
   1        8          1
   2        9          2
   20       1 
   4        2
   56
   6
   2

So I want a result in the column 3

Answer 1

column = [1, 2, 20, 4, 56, 6, 2]
column = [8, 9, 1, 2]
list_1 = []

for item1 in column1:
    for item2 in column2:
        if item1 == item2:
            list_1.append(item1)
        else:
            print("NO MATCH")
z = list(set(list_1))
print(z)

Answer 2

Using set.intersection with pd.DataFrame.loc :

L = list(set(df['column1']) & set(df['column2']))
df.loc[np.arange(len(L)), 'column3'] = L

print(df)

   column1  column2  column3
0        1      8.0      1.0
1        2      9.0      2.0
2       20      1.0      NaN
3        4      2.0      NaN
4       56      NaN      NaN
5        6      NaN      NaN
6        2      NaN      NaN

You should be aware this isn't vectorised and somewhat against the grain with Pandas / NumPy, hence a solution which uses regular Python objects.