擅长:python、mysql、java
<p><strong>对于问题1</strong>只需一个示例数据集即可。。你知道吗</p>
<pre><code>>>> df
A B C
0 foo 2 3
1 foo NaN NaN
2 foo 1 4
3 bar NaN NaN
4 foo NaN NaN
</code></pre>
<p><code>df.dropna(thresh=2)</code>遍历所有行,并保留至少有2个非na值的每一行。所有行至少有两个非na值,因此不会删除它们。你知道吗</p>
<pre><code>>>> df.dropna(thresh=2)
A B C
0 foo 2 3
2 foo 1 4
</code></pre>
<p>NaN计数大于2的值:</p>
<pre><code>>>> df.loc[df.isna().sum(axis=1) >= 2]
A B C
0 foo NaN NaN
2 foo NaN NaN
4 foo NaN NaN
5 NaN NaN NaN
</code></pre>
<p>要获得mean(),可以尝试如下操作:</p>
<pre><code>>>> df.B.ge(str(2))
0 True
1 False
2 False
3 False
4 False
Name: B, dtype: bool
>>>
>>>
>>> df[df.B.ge(str(2))]
A B C
0 foo 2 3
>>> df[df.B.ge(str(2))]['C'].mean()
3.0
</code></pre>