擅长:python、mysql、java
<p>更容易使用:</p>
<blockquote>
<p>pandas.to_numeric</p>
<p><a href="http://pandas.pydata.org/pandas-docs/version/0.17.0/generated/pandas.to_numeric.html" rel="noreferrer">http://pandas.pydata.org/pandas-docs/version/0.17.0/generated/pandas.to_numeric.html</a></p>
</blockquote>
<pre><code>import pandas as pd
df = pd.DataFrame({'eps': ['1', 1.6, '1.6', 'a', '', 'a1']})
df['eps'] = pd.to_numeric(df['eps'], errors='coerce')
</code></pre>
<p>“强制”将任何值错误转换为<code>NaN</code></p>
<pre><code>df['eps'].astype('float')
0 1.0
1 1.6
2 1.6
3 NaN
4 NaN
5 NaN
Name: eps, dtype: float64
</code></pre>
<p>然后可以应用其他函数而不出现错误:</p>
<pre><code>df['eps'].round()
0 1.0
1 2.0
2 2.0
3 NaN
4 NaN
5 NaN
Name: eps, dtype: float64
</code></pre>