熊猫。DataFrame.fillna-TypeError：只有整数标量数组可以转换为标量索引

Question

我想从官方熊猫留档...DataFrame.fillna所以基本上用值1填充dfhtml" target="_blank">数据框“myc”列中的NaN值。

数据帧

df
   myc    B   C  D
0  NaN  2.0 NaN  0
1  0.2  4.0 NaN  1
2  NaN  NaN NaN  5
3  NaN  3.0 NaN  4

代码1

values = {'myc': 1}
df.fillna(value=values)

成果目标1

    myc B   C   D
0   1.0 2.0 NaN 0
1   0.2 4.0 NaN 1
2   1.0 NaN NaN 5
3   1.0 3.0 NaN 4

误差表第1页

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-21-6a9e5a691bca> in <module>
      1 values = {'myc': 1}
----> 2 df.fillna(value=values)

~/anaconda3/lib/python3.8/site-packages/pandas/core/frame.py in fillna(self, value, method, axis, inplace, limit, downcast)
   4315         downcast=None,
   4316     ) -> Optional["DataFrame"]:
-> 4317         return super().fillna(
   4318             value=value,
   4319             method=method,

~/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py in fillna(self, value, method, axis, inplace, limit, downcast)
   6071                     if k not in result:
   6072                         continue
-> 6073                     obj = result[k]
   6074                     obj.fillna(v, limit=limit, inplace=True, downcast=downcast)
   6075                 return result if not inplace else None

~/anaconda3/lib/python3.8/site-packages/pandas/core/frame.py in __getitem__(self, key)
   2876                 if self.columns.nlevels > 1:
   2877                     return self._getitem_multilevel(key)
-> 2878                 return self._get_item_cache(key)
   2879 
   2880         # Do we have a slicer (on rows)?

~/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py in _get_item_cache(self, item)
   3539 
   3540             loc = self.columns.get_loc(item)
-> 3541             values = self._mgr.iget(loc)
   3542             res = self._box_col_values(values, loc)
   3543 

~/anaconda3/lib/python3.8/site-packages/pandas/core/internals/managers.py in iget(self, i)
    986         Return the data as a SingleBlockManager.
    987         """
--> 988         block = self.blocks[self.blknos[i]]
    989         values = block.iget(self.blklocs[i])
    990 

TypeError: only integer scalar arrays can be converted to a scalar index

代码2我后来还尝试列出any_feature列df['any_feature']的独特特性。唯一（）

错误2

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-39-934988075beb> in <module>
----> 1 df['any_feature'].unique()

~/anaconda3/lib/python3.8/site-packages/pandas/core/frame.py in __getitem__(self, key)
   2876                 if self.columns.nlevels > 1:
   2877                     return self._getitem_multilevel(key)
-> 2878                 return self._get_item_cache(key)
   2879 
   2880         # Do we have a slicer (on rows)?

~/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py in _get_item_cache(self, item)
   3539 
   3540             loc = self.columns.get_loc(item)
-> 3541             values = self._mgr.iget(loc)
   3542             res = self._box_col_values(values, loc)
   3543 

~/anaconda3/lib/python3.8/site-packages/pandas/core/internals/managers.py in iget(self, i)
    986         Return the data as a SingleBlockManager.
    987         """
--> 988         block = self.blocks[self.blknos[i]]
    989         values = block.iget(self.blklocs[i])
    990 

TypeError: only integer scalar arrays can be converted to a scalar index

尝试解决方案

• Not dictionary - Pandas: Getting "TypeError: only integer scalar arrays can be converted to a scalar index" while trying to merge data frames
• Not dictionary - Only integer scalar arrays can be converted to a scalar index how to resolve
• not answered - How to resolve Python TypeError: "only integer scalar arrays can be converted to a scalar index"
• Not dictionary - TypeError: only integer scalar arrays can be converted to a scalar index with 1D numpy indices array
• Not dictionary - numpy array TypeError: only integer scalar arrays can be converted to a scalar index
• Not dictionary - TypeError: only integer scalar arrays can be converted to a scalar index when use Pandas Fillna
• I don't want to convert it - How to convert index of a pandas dataframe into a column?
• I have tried running the following code to test if that object is a dataframe and it said true so it is - https://stackoverflow.com/a/14809149/10270590
  • INPUT

       isinstance(df, pd.DataFrame)
    

Answer 1

简单解决方案

• 导出数据帧到csv：df.to_csv（r'somefilename.csv'， index=False）
• 将saem数据加载回DataFrame：df1=pd.read_csv（"r'somefilename.csv"）

Answer 2

你的代码中发生了一些奇怪的事情，因为：

• 只能在myc列中替换NaN，
• 但您的结果也包含替换的值，例如，在C列中，NaN被替换为2

只运行以下代码（与代码分开）：

import pandas as pd
import io

txt = '''myc,B,C,D
NaN,2.0,NaN,0
3.0,4.0,NaN,1
NaN,NaN,NaN,5
NaN,3.0,NaN,4'''

df = pd.read_csv(io.StringIO(txt))
result = df.fillna(value={'myc': 1})

结果应该是：

   myc    B   C  D
0  1.0  2.0 NaN  0
1  3.0  4.0 NaN  1
2  1.0  NaN NaN  5
3  1.0  3.0 NaN  4

如果您得到相同的结果，那么显然您的代码有问题，但是在其他地方（在您呈现的代码片段之外）。

另一个需要更改的细节是，值是Pandas的一个属性，您不应该使用具有相同名称的变量。