pandas.hashtable.PyObjectHashTable.get_item 中的 Python pandas groupby 键错误

Question

我在 Pandas 中做的似乎是一个简单的分组。该列是一个字符串列，没有 NaN 或奇怪的字符串。但是，我不断收到以下错误。有谁知道为什么会发生这种情况？我觉得这可能与我的数据有关，但似乎一切正常......

我正在运行 by_user = df.groupby('User')

和堆栈跟踪:

by_user = df.groupby('User')
File "c:\Anaconda\lib\site-packages\pandas\core\generic.py", line 2773, in groupby
sort=sort, group_keys=group_keys, squeeze=squeeze)
File "c:\Anaconda\lib\site-packages\pandas\core\groupby.py", line 1142, in groupby
return klass(obj, by, **kwds)
File "c:\Anaconda\lib\site-packages\pandas\core\groupby.py", line 388, in __init__ level=level, sort=sort)
File "c:\Anaconda\lib\site-packages\pandas\core\groupby.py", line 2041, in _get_grouper
gpr = obj[gpr]
File "c:\Anaconda\lib\site-packages\pandas\core\frame.py", line 1678, in __getitem__
return self._getitem_column(key)
File "c:\Anaconda\lib\site-packages\pandas\core\frame.py", line 1685, in _get      item_column
return self._get_item_cache(key)
File "c:\Anaconda\lib\site-packages\pandas\core\generic.py", line 1052, in _ge
t_item_cache
values = self._data.get(item)
File "c:\Anaconda\lib\site-packages\pandas\core\internals.py", line 2565, in get
loc = self.items.get_loc(item)
File "c:\Anaconda\lib\site-packages\pandas\core\index.py", line 1181, in get_loc
return self._engine.get_loc(_values_from_object(key))
File "index.pyx", line 129, in pandas.index.IndexEngine.get_loc (pandas\index.
c:3656)
File "index.pyx", line 149, in pandas.index.IndexEngine.get_loc (pandas\index.
c:3534)
File "hashtable.pyx", line 696, in pandas.hashtable.PyObjectHashTable.get_item
(pandas\hashtable.c:11911)
File "hashtable.pyx", line 704, in pandas.hashtable.PyObjectHashTable.get_item
(pandas\hashtable.c:11864)
KeyError: 'User'

df.info():

User Code        175167 non-null object
Version          175167 non-null object
Date Accessed    175167 non-null datetime64[ns]
Series           175167 non-null object
Software         175167 non-null object
User             175167 non-null object

Answer 1

[从评论中移出]

很容易错过列名中的尾随空格，但您可以手动检查 df.columns:

>>> df = pd.DataFrame({"User": [1,2]})
>>> df2 = pd.DataFrame({"User ": [1,2]})
>>> df
   User
0     1
1     2
>>> df2
   User 
0      1
1      2
>>> df.columns
Index([u'User'], dtype='object')
>>> df2.columns
Index([u'User '], dtype='object')

(稍微揭开帷幕，我怀疑可能会发生这样的事情，因为当我模拟自己的 DataFrame 并查看 df.info() 时，我没有看到列名和数字之间的空格与您的输出似乎显示的一样多。)