擅长:python、mysql、java
<p>使用<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.append.html" rel="nofollow noreferrer">^{<cd1>}</a>和<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.idxmax.html" rel="nofollow noreferrer">^{<cd3>}</a>创建的第二个<code>df2</code>作为第一个<code>True</code>值,并按<code>loc</code>过滤:</p>
<pre><code>df = df1.append(df2.loc[(df2['A'] >= df1['A'].values[-1]).idxmax():])
print (df)
A B
0 0.00 514.51
1 0.75 514.51
2 1.10 514.42
3 3.52 514.41
4 5.59 514.43
4 6.00 531.00
5 7.00 532.00
</code></pre>
<p><strong>细节</strong>:</p>
<pre><code>print (df2.loc[(df2['A'] >= df1['A'].values[-1]).idxmax():])
A B
4 6.0 531.0
5 7.0 532.0
</code></pre>