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

Question

我正在尝试从熊猫官方文档中执行this。 pandas.DataFrame.fillna 所以基本上用 1 的值填充 df 数据框的“myc”列中的 NaN 值。

数据数据框

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)

结果目标 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

错误消息 1

---------------------------------------------------------------------------
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

CODE 2 我后来也尝试列出 any_feature 列的独特功能 df['any_feature'].unique()

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

尝试过的解决方案

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• 我不想转换它 - How to convert index of a pandas dataframe into a column?
• 我尝试运行以下代码来测试该对象是否为数据框，并且它说是真的，所以它是 - https://stackoverflow.com/a/14809149/10270590
  • 输入

       isinstance(df, pd.DataFrame)
    

  • 输出 True

Answer 1

您的代码中发生了一些奇怪的事情，因为：

• NaN 的替换应该仅在 myc 列中发生，
• 但您的结果也包含替换值，例如在 C column 和 NaN 被替换为 2。

只运行以下代码（与您的代码分开）：

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

如果你得到相同的结果，那么显然有 您的代码有问题，但在其他地方 （在您提供的那段代码之外）。

另一个需要改变的细节是 values 是一个属性 Pandas，你不应该使用同名的变量。

Answer 2

简单的解决方案

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