python - 如何根据 2 个数据框中的列匹配创建列表？ Python

Question

在我的实际数据集中，数据为 3500 万行 x 20 列，data2 为 4000 行 x 10 列。虽然这段代码可以工作，但需要很长时间，以至于我的系统会超时。因此，我正在寻找一种替代解决方案来运行得更快。

import pandas as pd

data = pd.DataFrame({'variable1':[1,2,3,4,0,6,7], 'variable2':[1,2,3,4,5,6,7], 'variable3':[1,200,3,4,50,6,7], 'variable4':[1,2,3,4,5,6,7]})

data2 = pd.DataFrame({'variable1':[2,0], 'variable2':[2,5], 'variable3':[200,50], 'variable4':[17,20]})


target = []

for i in range(len(data)):
    for j in range(len(data2)):
        if (data['variable1'].iloc[i] == data2['variable1'].iloc[j]) and (data['variable2'].iloc[i] == data2['variable2'].iloc[j]):
            target.append("Yes")
        else: target.append("No")

Proper output would be:
[[1,1,1,1,"No"],
[2,2,200,2,"Yes"],
[3,3,3,3,"No"],
[4,4,4,4,"No"],
[0,5,50,5,"Yes"],
[6,6,6,6,"No"],
[7,7,7,7,"No"]]

Answer 1

MultiIndex.isin

c = ['variable1', 'variable2']
data['match'] = data.set_index(c).index.isin(data2.set_index(c).index)

---

   variable1  variable2  variable3  variable4  match
0          1          1          1          1  False
1          2          2        200          2   True
2          3          3          3          3  False
3          4          4          4          4  False
4          0          5         50          5   True
5          6          6          6          6  False
6          7          7          7          7  False