擅长:python、mysql、java
<p>您可以使用由<code>Series</code>或<code>list comprehension</code>生成的所有值的<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.isin.html" rel="nofollow noreferrer">^{<cd1>}</a>by <code>list</code>:</p>
<pre><code>a = pd.Series(range(1, 15)).astype(str).str.zfill(2).radd('E')
row_data = raw_df.loc[raw_df.col0.isin(a)]
</code></pre>
<p>细节:</p>
<pre><code>print (a)
0 E01
1 E02
2 E03
3 E04
4 E05
5 E06
6 E07
7 E08
8 E09
9 E10
10 E11
11 E12
12 E13
13 E14
dtype: object
</code></pre>
<p>备选方案:</p>
<pre><code>a = ['E{:02d}'.format(x) for x in range(1, 15)]
print (a)
['E01', 'E02', 'E03', 'E04', 'E05', 'E06', 'E07',
'E08', 'E09', 'E10', 'E11', 'E12', 'E13', 'E14']
</code></pre>
<p>备选方案2,谢谢<a href="https://stackoverflow.com/questions/47940850/multiple-incrementing-conditional-clauses-in-pandas/47940883#comment82851103_47940883">KPLauritzen</a>:</p>
<pre><code>conditions = [f'E{x:02}' for x in range(1, 15)]
</code></pre>