我正在使用熊猫来计算数据文件的某些统计信息，并出现一些错误。可以通过以下简单的示例代码进行复制：
import pandas as pd
df = pd.DataFrame({'A': [1,2,3,4,5,6,7,8,9],
'B': [1,2,3,1,2,3,1,2,3],
'C': ['a', 'b', 'a', 'b', 'a', 'b', 'a','a', 'b']})
def testFun2(x):
return pd.DataFrame({'xlen': x.shape[0]})
def testFun(x):
b = x['B']
print "b equals to {}".format(b) # This line prints okay
c = x['C']
out = pd.DataFrame()
for a in x['A'].unique():
subx = x[x.A == a]
subxg = testFun2(subx)
out = pd.concat([out, subxg])
return out
df.groupby(['B', 'C']).apply(lambda x: testFun(x))
整个错误输出如下：
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
<ipython-input-21-979d23aa904c> in <module>()
18 return out
19
---> 20 df.groupby(['B', 'C']).apply(lambda x: testFun(x))
C:\Users\Administrator\Anaconda2\lib\site-packages\pandas\core\groupby\groupby.pyc in apply(self, func, *args, **kwargs)
928
929 with _group_selection_context(self):
--> 930 return self._python_apply_general(f)
931
932 return result
C:\Users\Administrator\Anaconda2\lib\site-packages\pandas\core\groupby\groupby.pyc in _python_apply_general(self, f)
934 def _python_apply_general(self, f):
935 keys, values, mutated = self.grouper.apply(f, self._selected_obj,
--> 936 self.axis)
937
938 return self._wrap_applied_output(
C:\Users\Administrator\Anaconda2\lib\site-packages\pandas\core\groupby\groupby.pyc in apply(self, f, data, axis)
2271 # group might be modified
2272 group_axes = _get_axes(group)
-> 2273 res = f(group)
2274 if not _is_indexed_like(res, group_axes):
2275 mutated = True
<ipython-input-21-979d23aa904c> in <lambda>(x)
18 return out
19
---> 20 df.groupby(['B', 'C']).apply(lambda x: testFun(x))
<ipython-input-21-979d23aa904c> in testFun(x)
9
10 def testFun(x):
---> 11 b = x['B']
12 c = x['C']
13 out = pd.DataFrame()
C:\Users\Administrator\Anaconda2\lib\site-packages\pandas\core\frame.pyc in __getitem__(self, key)
2686 return self._getitem_multilevel(key)
2687 else:
-> 2688 return self._getitem_column(key)
2689
2690 def _getitem_column(self, key):
C:\Users\Administrator\Anaconda2\lib\site-packages\pandas\core\frame.pyc in _getitem_column(self, key)
2693 # get column
2694 if self.columns.is_unique:
-> 2695 return self._get_item_cache(key)
2696
2697 # duplicate columns & possible reduce dimensionality
C:\Users\Administrator\Anaconda2\lib\site-packages\pandas\core\generic.pyc in _get_item_cache(self, item)
2487 res = cache.get(item)
2488 if res is None:
-> 2489 values = self._data.get(item)
2490 res = self._box_item_values(item, values)
2491 cache[item] = res
C:\Users\Administrator\Anaconda2\lib\site-packages\pandas\core\internals.pyc in get(self, item, fastpath)
4113
4114 if not isna(item):
-> 4115 loc = self.items.get_loc(item)
4116 else:
4117 indexer = np.arange(len(self.items))[isna(self.items)]
C:\Users\Administrator\Anaconda2\lib\site-packages\pandas\core\indexes\base.pyc in get_loc(self, key, method, tolerance)
3078 return self._engine.get_loc(key)
3079 except KeyError:
-> 3080 return self._engine.get_loc(self._maybe_cast_indexer(key))
3081
3082 indexer = self.get_indexer([key], method=method, tolerance=tolerance)
pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_loc()
pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_loc()
pandas\_libs\hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()
pandas\_libs\hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()
KeyError: 'B'
但是，我发现如果将testFun2更改为更简单的内容，例如：
def testFun2(x):
return 1
然后将不会发生错误。这让我非常困惑-testFun2与b = x['B']行无关，对吗？为什么我首先遇到错误？谢谢！