<p>为了将<code>NaN</code>替换为每组最常见的值,<code>Medicine_ID</code>可以使用<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.groupby.html" rel="nofollow noreferrer">^{<cd3>}</a>与{a2}和{a3}一起使用<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.value_counts.html" rel="nofollow noreferrer">^{<cd7>}</a>之后的第一个值{<cd6>}:</p>
<pre><code>df = pd.DataFrame({'A':list('abcdefabcdef'),
'Counterfeit_Weight':[np.nan,5.0,5.0,np.nan,2.0,4.1,3.0,
np.nan,6.1,np.nan,4.1,4.1],
'Medicine_ID':list('caabbbaaabbb')})
print (df)
A Counterfeit_Weight Medicine_ID
0 a NaN c
1 b 5.0 a
2 c 5.0 a
3 d NaN b
4 e 2.0 b
5 f 4.1 b
6 a 3.0 a
7 b NaN a
8 c 6.1 a
9 d NaN b
10 e 4.1 b
11 f 4.1 b
</code></pre>
<hr/>
^{pr2}$