List 我希望将以下数据帧转换为一个列表
取决于您想要的是平面列表还是嵌套列表 嵌套列表List 我希望将以下数据帧转换为一个列表,list,pandas,dataframe,List,Pandas,Dataframe,取决于您想要的是平面列表还是嵌套列表 嵌套列表 Sl No Vertical Verticale Code Org Work Location \ 0 1.0 IT 5 New Delhi 1 2.0 IT 5 Raipur 2 3.0 Infrastructure
Sl No Vertical Verticale Code Org Work Location \
0 1.0 IT 5 New Delhi
1 2.0 IT 5 Raipur
2 3.0 Infrastructure 7 Coimbatore
3 4.0 Telecom 3 Chennai
4 5.0 Telecom 3 Ahmedabad
5 6.0 IT 5 Chennai
6 7.0 IT 5 Chennai
7 8.0 IT Products 6 Bangalore
8 9.0 IT 5 Chennai
9 10.0 IT 5 Chennai
10 11.0 Telecom 3 Bangalore
11 12.0 IT 5 Mysore
12 13.0 IT Products 6 Navi Mumbai
13 14.0 Telecom 3 Bangalore
14 15.0 Infrastructure 7 Chennai
15 16.0 IT 5 Chennai
16 17.0 IT 5 Chennai
17 18.0 Infrastructure 7 Coimbatore
18 19.0 Telecom 3 Chennai
19 20.0 Telecom 3 Bangalore
20 21.0 Telecom 3 Bengalore
21 22.0 IT 5 Chennai
df.values.tolist()
[[0, 1.0, 'IT', '5', 'New', 'Delhi', nan, nan],
[1, 2.0, 'IT', '5', 'Raipur', nan, nan, nan],
[2, 3.0, 'Infrastructure', '7', 'Coimbatore', nan, nan, nan],
[3, 4.0, 'Telecom', '3', 'Chennai', nan, nan, nan],
[4, 5.0, 'Telecom', '3', 'Ahmedabad', nan, nan, nan],
[5, 6.0, 'IT', '5', 'Chennai', nan, nan, nan],
[6, 7.0, 'IT', '5', 'Chennai', nan, nan, nan],
[7, 8.0, 'IT', 'Products', '6', 'Bangalore', nan, nan],
[8, 9.0, 'IT', '5', 'Chennai', nan, nan, nan],
[9, 10.0, 'IT', '5', 'Chennai', nan, nan, nan],
[10, 11.0, 'Telecom', '3', 'Bangalore', nan, nan, nan],
[11, 12.0, 'IT', '5', 'Mysore', nan, nan, nan],
[12, 13.0, 'IT', 'Products', '6', 'Navi', 'Mumbai', nan],
[13, 14.0, 'Telecom', '3', 'Bangalore', nan, nan, nan],
[14, 15.0, 'Infrastructure', '7', 'Chennai', nan, nan, nan],
[15, 16.0, 'IT', '5', 'Chennai', nan, nan, nan],
[16, 17.0, 'IT', '5', 'Chennai', nan, nan, nan],
[17, 18.0, 'Infrastructure', '7', 'Coimbatore', nan, nan, nan],
[18, 19.0, 'Telecom', '3', 'Chennai', nan, nan, nan],
[19, 20.0, 'Telecom', '3', 'Bangalore', nan, nan, nan],
[20, 21.0, 'Telecom', '3', 'Bengalore', nan, nan, nan],
[21, 22.0, 'IT', '5', 'Chennai', nan, nan, nan]]
Sl No Vertical Verticale Code Org Work Location \
0 1.0 IT 5 New Delhi
1 2.0 IT 5 Raipur
2 3.0 Infrastructure 7 Coimbatore
3 4.0 Telecom 3 Chennai
4 5.0 Telecom 3 Ahmedabad
5 6.0 IT 5 Chennai
6 7.0 IT 5 Chennai
7 8.0 IT Products 6 Bangalore
8 9.0 IT 5 Chennai
9 10.0 IT 5 Chennai
10 11.0 Telecom 3 Bangalore
11 12.0 IT 5 Mysore
12 13.0 IT Products 6 Navi Mumbai
13 14.0 Telecom 3 Bangalore
14 15.0 Infrastructure 7 Chennai
15 16.0 IT 5 Chennai
16 17.0 IT 5 Chennai
17 18.0 Infrastructure 7 Coimbatore
18 19.0 Telecom 3 Chennai
19 20.0 Telecom 3 Bangalore
20 21.0 Telecom 3 Bengalore
21 22.0 IT 5 Chennai
df.values.tolist()
[[0, 1.0, 'IT', '5', 'New', 'Delhi', nan, nan],
[1, 2.0, 'IT', '5', 'Raipur', nan, nan, nan],
[2, 3.0, 'Infrastructure', '7', 'Coimbatore', nan, nan, nan],
[3, 4.0, 'Telecom', '3', 'Chennai', nan, nan, nan],
[4, 5.0, 'Telecom', '3', 'Ahmedabad', nan, nan, nan],
[5, 6.0, 'IT', '5', 'Chennai', nan, nan, nan],
[6, 7.0, 'IT', '5', 'Chennai', nan, nan, nan],
[7, 8.0, 'IT', 'Products', '6', 'Bangalore', nan, nan],
[8, 9.0, 'IT', '5', 'Chennai', nan, nan, nan],
[9, 10.0, 'IT', '5', 'Chennai', nan, nan, nan],
[10, 11.0, 'Telecom', '3', 'Bangalore', nan, nan, nan],
[11, 12.0, 'IT', '5', 'Mysore', nan, nan, nan],
[12, 13.0, 'IT', 'Products', '6', 'Navi', 'Mumbai', nan],
[13, 14.0, 'Telecom', '3', 'Bangalore', nan, nan, nan],
[14, 15.0, 'Infrastructure', '7', 'Chennai', nan, nan, nan],
[15, 16.0, 'IT', '5', 'Chennai', nan, nan, nan],
[16, 17.0, 'IT', '5', 'Chennai', nan, nan, nan],
[17, 18.0, 'Infrastructure', '7', 'Coimbatore', nan, nan, nan],
[18, 19.0, 'Telecom', '3', 'Chennai', nan, nan, nan],
[19, 20.0, 'Telecom', '3', 'Bangalore', nan, nan, nan],
[20, 21.0, 'Telecom', '3', 'Bengalore', nan, nan, nan],
[21, 22.0, 'IT', '5', 'Chennai', nan, nan, nan]]
你的问题是？你是在请求许可吗？当然，去吧；好的。第一个列表就是我想要的。第一个列表是嵌套的。我想知道如何继续使用python