<p>这与cs95使用<code>reindex</code>所做的非常接近</p>
<pre><code>s,y=i1.reindex(s0.index.levels[0],tolerance=pd.Timedelta(days=2),method='nearest')
s0.loc[s[y!=-1]]
</code></pre>
<p>如果需要,将索引级别1更改为l1</p>
<pre><code>s=s0.index.levels[0].values
t=abs((i1[:,None]-s))/np.timedelta64(1, 'D')<=2
f=s0.loc[s[t.any(0)]].reset_index(level=1)
f.index=f.index.map(dict(zip(s[t.any(0)],i1[t.any(1)])))
f.set_index('ID',append=True,inplace=True)
f
Out[458]:
stuff
date ID
2018-11-30 S 0
O 0
J 0
H 0
D 0
2018-12-31 U 2
S 2
A 2
J 2
L 2
2019-01-15 K 3
U 3
V 3
S 3
H 3
</code></pre>
<hr/>
<h3>piR编辑</h3>
<p>我这样重新配置了</p>
<pre><code>lvl0, lvl1 = s0.index.levels
_, indexer = i1.reindex(lvl0, tolerance=tol, method='nearest')
newlvl0 = i1[indexer]
msklvl0 = newlvl0[indexer != -1]
newidx = s0.index.set_levels([newlvl0, lvl1])
s0.set_axis(newidx, inplace=False).loc[msklvl0]
date ID
2018-11-30 S 0
O 0
J 0
H 0
D 0
2018-12-31 U 2
S 2
A 2
J 2
L 2
2019-01-15 K 3
U 3
V 3
S 3
H 3
Name: stuff, dtype: int64
</code></pre>