擅长:python、mysql、java
<p>您可以使用<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.combine_first.html">^{<cd1>}</a>或<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.fillna.html">^{<cd2>}</a>:</p>
<pre><code>print df['feedback_id'].combine_first(df['_id'])
0 568a8c25cac4991645c287ac
1 568df45b177e30c6487d3603
2 568df434832b090048f34974
3 568cd22e9e82dfc166d7dff1
4 568df3f0832b090048f34711
5 568e5a38b4a797c664143dda
Name: feedback_id, dtype: object
print df['feedback_id'].fillna(df['_id'])
0 568a8c25cac4991645c287ac
1 568df45b177e30c6487d3603
2 568df434832b090048f34974
3 568cd22e9e82dfc166d7dff1
4 568df3f0832b090048f34711
5 568e5a38b4a797c664143dda
Name: feedback_id, dtype: object
</code></pre>