<p>IIUC公司：</p>
<pre><code>from itertools import combinations
pd.DataFrame([
[k, c0, c1] for k, tof in df.groupby('id').tof
for c0, c1 in combinations(tof, 2)
], columns=['id', 'tof0', 'tof1'])
id tof0 tof1
0 43.0 1999991.0 2095230.0
1 43.0 1999991.0 4123105.0
2 43.0 1999991.0 5560423.0
3 43.0 2095230.0 4123105.0
4 43.0 2095230.0 5560423.0
5 43.0 4123105.0 5560423.0
6 46.0 2098996.0 2114971.0
7 46.0 2098996.0 4130033.0
8 46.0 2098996.0 4355096.0
9 46.0 2114971.0 4130033.0
10 46.0 2114971.0 4355096.0
11 46.0 4130033.0 4355096.0
12 82.0 2055207.0 2093996.0
13 82.0 2055207.0 4193587.0
14 82.0 2093996.0 4193587.0
15 90.0 2059360.0 2083762.0
16 90.0 2059360.0 2648235.0
17 90.0 2059360.0 4212177.0
18 90.0 2083762.0 2648235.0
19 90.0 2083762.0 4212177.0
20 90.0 2648235.0 4212177.0
</code></pre>
<hr/>
<h3>说明</h3>
<p>这是一个列表理解，返回由数据帧构造函数包装的列表列表。<a href="https://www.pythonforbeginners.com/basics/list-comprehensions-in-python" rel="nofollow noreferrer">Look up comprehensions to understand better.</a></p>
<pre><code>from itertools import combinations
pd.DataFrame([
# name series of tof values
# ↓ ↓
[k, c0, c1] for k, tof in df.groupby('id').tof
# items from combinations
# first second
# ↓ ↓
for c0, c1 in combinations(tof, 2)
], columns=['id', 'tof0', 'tof1'])
</code></pre>
