scidam
Скорее всего, ваш цикл while можно заменить, используя векторные операции в pandas, как-то так:
Возникает такая лютая ошибка:
KeyError Traceback (most recent call last)
<ipython-input-80-2dce6c1f2299> in <module>()
—-> 1 x.loc += 1
C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py in __getitem__(self, key)
1365 except (KeyError, IndexError):
1366 pass
-> 1367 return self._getitem_tuple(key)
1368 else:
1369 # we by definition only have the 0th axis
C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py in _getitem_tuple(self, tup)
856 def _getitem_tuple(self, tup):
857 try:
–> 858 return self._getitem_lowerdim(tup)
859 except IndexingError:
860 pass
C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py in _getitem_lowerdim(self, tup)
1018 return section
1019 # This is an elided recursive call to iloc/loc/etc'
-> 1020 return getattr(section, self.name)
1021
1022 raise IndexingError('not applicable')
C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py in __getitem__(self, key)
1371
1372 maybe_callable = com._apply_if_callable(key, self.obj)
-> 1373 return self._getitem_axis(maybe_callable, axis=axis)
1374
1375 def _is_scalar_access(self, key):
C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py in _getitem_axis(self, key, axis)
1614 raise ValueError('Cannot index with multidimensional key')
1615
-> 1616 return self._getitem_iterable(key, axis=axis)
1617
1618 # nested tuple slicing
C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py in _getitem_iterable(self, key, axis)
1113
1114 if self._should_validate_iterable(axis):
-> 1115 self._has_valid_type(key, axis)
1116
1117 labels = self.obj._get_axis(axis)
C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py in _has_valid_type(self, key, axis)
1470 raise KeyError(
1471 u"None of are in the ".format(
-> 1472 key=key, axis=self.obj._get_axis_name(axis)))
1473 else:
1474
KeyError: ‘None of fight_id\n0 NaN\n1 NaN\n2 NaN\n3 NaN\n4 NaN\n5 NaN\n6 NaN\n7 NaN\n8 NaN\n9 NaN\n10 NaN\n11 NaN\n12 NaN\n13 NaN\n14 NaN\n15 NaN\n16 NaN\n17 NaN\n18 NaN\n19 NaN\n20 NaN\n21 NaN\n22 NaN\n23 NaN\n24 NaN\n25 NaN\n26 NaN\n27 NaN\n28 NaN\n29 NaN\n ..\n49058 NaN\n49059 NaN\n49060 NaN\n49061 NaN\n49062 NaN\n49063 NaN\n49064 NaN\n49065 NaN\n49066 NaN\n49067 NaN\n49068 NaN\n49069 NaN\n49070 NaN\n49071 NaN\n49072 NaN\n49073 NaN\n49074 NaN\n49075 NaN\n49076 NaN\n49077 NaN\n49078 NaN\n49079 NaN\n49080 NaN\n49081 NaN\n49082 NaN\n49083 NaN\n49084 NaN\n49085 NaN\n49086 NaN\n49087 NaN\nName: r1_hero_roles, Length: 49088, dtype: float64 are in the index’