擅长:python、mysql、java
<p><strong>编辑</strong>:更新评论人建议。在</p>
<p>您需要执行左连接:</p>
<pre><code>Exp = pd.DataFrame(
pd.to_datetime(['1989-06-01', '1989-07-01', '1989-08-01', '1989-09-01', '1989-10-01']),
columns=['Exp'])
</code></pre>
<p>给出:</p>
^{pr2}$
<p>以及</p>
<pre><code>CL = pd.DataFrame(
[68.800026, 68.620026, 68.930023, 68.990021, 69.110023],
index = pd.to_datetime(['1989-06-01', '1989-06-04', '1989-06-05', '1989-06-06', '1989-06-09']),
columns = ['CL'])
</code></pre>
<p>给予</p>
<pre><code> CL
1989-06-01 68.800026
1989-06-04 68.620026
1989-06-05 68.930023
1989-06-06 68.990021
1989-06-09 69.110023
</code></pre>
<p>然后:</p>
<pre><code>(CL
.reset_index()
.merge(Exp, how='left', right_on='Exp', left_on='index')
.set_index('index')
.rename(columns={'Exp': 'R'}))
</code></pre>
<p>返回您要查找的内容</p>
<pre><code> CL R
index
1989-06-01 68.800026 1989-06-01
1989-06-04 68.620026 NaN
1989-06-05 68.930023 NaN
1989-06-06 68.990021 NaN
1989-06-09 69.110023 NaN
</code></pre>
<p>因为循环数据帧不是熊猫做事的方式。在</p>