英文:
Not able to split data frame in numpy
问题
无法使用numpy的split函数将数据框分配给子集。
英文:
Not able to use numpy split function to allocate subsets of dataframe to
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
Tried reading the documentation but didnt find anything useful.
答案1
得分: 0
你的代码错误在于尝试使用NumPy例程处理Pandas数据框。解决方法是将df.sample转换为NumPy数组，然后使用np.split()。
尝试这样做 - 在我的VSCode上运行得非常好：
npsample=np.array(df.sample(frac=1))
train, valid, test = np.split(npsample, [int(0.6*len(npdata)) , int(0.8*len(npdata)), ])
英文:
The error in your code is that you are trying to use a numpy routine with a pandas data frame. The best way to approach this is to convert your df.sample into a numpy array and then use np.split().
Try this - it runs perfectly well on my VSCode:
npsample=np.array(df.sample(frac=1))
train, valid, test = np.split(npsample, [int(0.6*len(npdata)) , int(0.8*len(npdata)), ])
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