<p>首先,让我们构造您的<code>side_df</code>:</p>
<pre><code>side_df = pd.DataFrame([['sample-test'], ['query_sample'], ['us-east-1-sample']]
, columns=['AccessName'])
fixed_series = pd.Series(['fixed_value'] * len(side_df), name='PolicyArn').to_frame()
side_df_extended = pd.concat([side_df, fixed_series], axis=1)
print(side_df_extended)
AccessName PolicyArn
0 sample-test fixed_value
1 query_sample fixed_value
2 us-east-1-sample fixed_value
</code></pre>
<p>假设<code>full_df</code>如下所示:</p>
<pre><code> AccessName PolicyArn
0 arn:aws:glue:sample arn:aws:iam::971340810992:policy/service-role/
1 arn:aws:glue:sample2 arn:aws:iam::971340810992:policy/service-role/
2 arn:aws:s3:::sample3 arn:aws:iam::971340810992:policy/service-role/
3 arn:aws:glue:sample4 arn:aws:iam::971340810992:policy/service-role/
4 arn:aws:s3:::sample5 arn:aws:iam::971340810992:policy/service-role/
</code></pre>
<p>现在,让我们获取具有您的条件的行的索引,例如:</p>
<pre><code>indices = full_df['AccessName'] == 'arn:aws:glue:sample2'
rows = full_df[indices].index.tolist()
rows
[1]
</code></pre>
<p>现在,您希望在您的条件发生后附加<code>side_df</code>:</p>
<pre><code>final_df = pd.concat([full_df.iloc[:(rows[0] + 1)], side_df_extended, full_df.iloc[(rows[0] + 1):]], ignore_index=True)
final_df
AccessName PolicyArn
0 arn:aws:glue:sample arn:aws:iam::971340810992:policy/service-role/
1 arn:aws:glue:sample2 arn:aws:iam::971340810992:policy/service-role/
2 sample-test fixed_value
3 query_sample fixed_value
4 us-east-1-sample fixed_value
5 arn:aws:s3:::sample3 arn:aws:iam::971340810992:policy/service-role/
6 arn:aws:glue:sample4 arn:aws:iam::971340810992:policy/service-role/
7 arn:aws:s3:::sample5 arn:aws:iam::971340810992:policy/service-role/
</code></pre>