无法在numpy中分割数据帧

Question

无法使用numpy split函数将数据帧的子集分配给

cols =["fLength","fWidth","fSize","fConc","fConcl","fAsym","fM3Long","fAlpha","fDist","class"]
df = pd.read_csv("magic04.data",names = cols)
df['class'] = (df['class']=='g').astype(int)
train, valid, test = np.split(df.sample(frac=1), [int(0.6*len(df)) , int(0.8*len(df)), ])

KeyError                                  Traceback (most recent call last)
/usr/local/lib/python3.9/dist-packages/pandas/core/indexes/base.py in get_loc(self, key, method, tolerance)
3628             try:
-> 3629                 return self._engine.get_loc(casted_key)
3630             except KeyError as err:
17 frames
KeyError: 0
The above exception was the direct cause of the following exception:
KeyError                                  Traceback (most recent call last)
/usr/local/lib/python3.9/dist-packages/pandas/core/indexes/base.py in get_loc(self, key, method, tolerance)
3629                 return self._engine.get_loc(casted_key)
3630             except KeyError as err:
-> 3631                 raise KeyError(key) from err
3632             except TypeError:
3633                 # If we have a listlike key, _check_indexing_error will raise

试着阅读文档，但没有发现任何有用的。

Answer 1

代码中的错误是您试图对pandas数据框架使用numpy例程。实现这一点的最佳方法是将df.sample转换为numpy数组，然后使用np.split()。

试试这个-它在我的VSCode上运行得很好:

npsample=np.array(df.sample(frac=1))
train, valid, test = np.split(npsample, [int(0.6*len(npdata)) , int(0.8*len(npdata)), ])