擅长:python、mysql、java
<p>IIUC:存在<code>.empty</code>属性:</p>
<p>数据帧:</p>
<pre><code>In [86]: pd.DataFrame().empty
Out[86]: True
In [87]: pd.DataFrame([1,2,3]).empty
Out[87]: False
</code></pre>
<p>系列:</p>
<pre><code>In [88]: pd.Series().empty
Out[88]: True
In [89]: pd.Series([1,2,3]).empty
Out[89]: False
</code></pre>
<p>注意:与<code>df.empty</code>方法相比,检查DF的长度(<code>len(df)</code>)可以节省几毫秒;-)</p>
<pre><code>In [142]: df = pd.DataFrame()
In [143]: %timeit df.empty
8.25 µs ± 22.4 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)
In [144]: %timeit len(df)
2.35 µs ± 7.56 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)
In [145]: df = pd.DataFrame(np.random.randn(10*5, 3), columns=['a', 'b', 'c'])
In [146]: %timeit df.empty
15.3 µs ± 269 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)
In [147]: %timeit len(df)
3.58 µs ± 12.2 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)
</code></pre>