擅长:python、mysql、java
<p>从<code>carContactTel</code>列创建一个新的数据帧,然后使用<a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.set_axis.html" rel="nofollow noreferrer">^{<cd2>}</a>+<a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.add_prefix.html" rel="nofollow noreferrer">^{<cd3>}</a>根据要求对列进行整合,最后使用<a href="https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.fillna.html" rel="nofollow noreferrer">^{<cd4>}</a>将<code>NaN</code>值替换为空字符串:</p>
<pre><code>df1 = pd.DataFrame(carContactDF['carContactTel'].tolist())
df1 = (
df1.set_axis(df1.columns + 1, 1).add_prefix('carContactTel')
.fillna('').replace('^tel\s*', '', regex=True)
)
</code></pre>
<p>结果:</p>
<pre><code>print(df1)
carContactTel1 carContactTel2 carContactTel3
0
1 432424
2 84958358
3 5434645 534535 3242342
</code></pre>