擅长:python、mysql、java
<p>我认为您需要用<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.str.split.html" rel="nofollow noreferrer">^{<cd2>}</a>拆分<code>apply</code>,并用<code>str[1]</code>选择:</p>
<pre><code>print (data_activationsLV)
['14468 7.8', '14469 7.8']
print (data_activationsF)
['14468 7.2', '14469 7.1', '14470 7.9', '14471 9.5']
print (data_activationsPC)
['14468 7.6', '14470 8.1', '14471 9.9']
df15LV = pd.Series(data_activationsLV)
df15F = pd.Series(data_activationsF)
df15PC = pd.Series(data_activationsPC)
dfnew2=pd.concat([df15LV,df15F,df15PC], axis=1)
dfnew2 = dfnew2.apply(lambda x: x.str.split().str[1])
#if necessary convert to float
dfnew2 = dfnew2.astype(float)
print (dfnew2)
0 1 2
0 7.8 7.2 7.6
1 7.8 7.1 8.1
2 NaN 7.9 9.9
3 NaN 9.5 NaN
</code></pre>
<p>另一种解决方案是使用<code>list comprehension</code>进行拆分:</p>
^{2}$