<p>您可以使用:</p>
<p>第一次测试是否匹配缺少的值:</p>
<pre><code>print (df.isna())
CODE Date PRCP TAVG TMAX TMIN
0 False False False False True True
1 False False False False True True
2 False False False False True False
3 False False False False True False
4 False False False False True False
5 False False False False True True
6 False False False False True False
7 False False False False True False
8 False False False False True False
</code></pre>
<hr/>
<pre><code>#columsn for test missing values
cols = ['TMAX','TMIN','TAVG']
#CODe to index, filter columns and create one Series
m = df.set_index('CODE')[cols].isna().unstack()
#create consecutive groups and count them with maximal count per column and group
df = (m.ne(m.shift()).cumsum()
.where(m)
.groupby(level=[0,1]).value_counts()
.max(level=[0,1])
.unstack(0)
.add_suffix('_maxcnullcount'))
print (df)
TMAX_maxcnullcount TMIN_maxcnullcount
CODE
AE000041196 9 2
</code></pre>