pandas 熊猫：返回 NaN 行
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Pandas: return NaN rows
提问by Michael Perdue
I am trying to return a df that contains all of the NaNvalues for column == years_expso that I can identify the corresponding id.thomas(basically I'm debugging some data that I parsed by hand). I also need to return a df with all minvalues. This is what I have tried so far:
我试图返回一个包含所有NaN值的 dfcolumn == years_exp以便我可以识别相应的值id.thomas（基本上我正在调试一些我手动解析的数据）。我还需要返回一个包含所有min值的 df 。这是我迄今为止尝试过的：
rr.head(5)
years id.thomas years_exp
55 2005 2 17
56 2006 2 18
57 2007 2 19
58 2008 2 20
59 2009 2 21
c = rr
c = c[c.years_exp == 'NaN']
Error:
错误：
TypeError: invalid type comparison
类型错误：无效的类型比较
I'm using syntax that I copied from a youtube video on Pandas. Does anyone have an idea about the error?
我正在使用从 Pandas 上的 YouTube 视频中复制的语法。有没有人知道这个错误？
回答by jezrael
You need isnullfor checking NaNvalues:
您需要isnull检查NaN值：
print (rr[rr.years_exp.isnull()])
Docs:
文档：
Warning
One has to be mindful that in python (and numpy), the nan's don't compare equal, but None's do. Note that Pandas/numpy uses the fact that np.nan != np.nan, and treats None like np.nan.
警告
必须注意，在 python（和 numpy）中，nan 不相等，但 None 不相等。请注意，Pandas/numpy 使用 np.nan != np.nan 的事实，并将 None 视为 np.nan。
In [11]: None == None
Out[11]: True
In [12]: np.nan == np.nan
Out[12]: False
So as compared to above, a scalar equality comparison versus a None/np.nan doesn't provide useful information.
因此，与上面相比，标量相等比较与 None/np.nan 没有提供有用的信息。
In [13]: df2['one'] == np.nan
Out[13]:
a False
b False
c False
d False
e False
f False
g False
h False
Name: one, dtype: bool
回答by Antonin Bouscarel
You can try with
你可以试试
c = c.loc[c.years_exp == 'NaN']
or
或者
c = c.loc[c.years_exp == None]
or
或者
c = c.loc[c.years_exp.isnull()]
