원핫인코딩 후 컬럼 개수 불일

• 학습 관련 질문을 남겨주세요. 상세히 작성하면 더 좋아요!

• 질문과 관련된 영상 위치를 알려주면 더 빠르게 답변할 수 있어요

• 먼저 유사한 질문이 있었는지 검색해보세요

•  

  print(train.info())
  print(test.info())
  print(train.isnull().sum())
  print(test.isnull().sum())
  print(train.head())
  print(test.head())
  target = train['총가스사용량'].pop
  # import sklearn
  # print(sklearn.__all__)
  
  print(train.shape, test.shape)
  train = pd.get_dummies(train)
  test = pd.get_dummies(test)
  print(train.shape, test.shape)

  상기 처럼 코딩 후,

• 컬럼값이 26, 25로 불일치하게 나와요. 왜일까요...

• (3196, 6) (1476, 5) (3196, 26) (1476, 25)

• 그래서 그 이후 값들도 에러가 떠요

•  

  from sklearn.model_selection import train_test_split
  
  X_tr, X_val, y_tr, y_val = train_test_split(train, target, test_size=0.2, random_state = 0)

  ---------------------------------------------------------------------------
  

  TypeError                                 Traceback (most recent call last)
  

  /tmp/ipython-input-3028840780.py in <cell line: 0>()
        1 from sklearn.model_selection import train_test_split
        2 
  ----> 3 X_tr, X_val, y_tr, y_val = train_test_split(train, target, test_size=0.2, random_state = 0)
  
  

  ---

  4 frames

  ---

  /usr/local/lib/python3.12/dist-packages/sklearn/utils/validation.py in _num_samples(x)
      397     if hasattr(x, "shape") and x.shape is not None:
      398         if len(x.shape) == 0:
  --> 399             raise TypeError(
      400                 "Input should have at least 1 dimension i.e. satisfy "
      401                 f"`len(x.shape) > 0`, got scalar `{x!r}` instead."
  
  

  TypeError: Input should have at least 1 dimension i.e. satisfy `len(x.shape) > 0`, got scalar `array(<bound method Series.pop of 0        9077.8
  1       10105.5
  2        8603.6
  3       11076.8
  4       10781.4
           ...   
  3191    12294.7
  3192    10410.7
  3193    10473.8
  3194     9657.9
  3195     9961.5
  Name: 총가스사용량, Length: 3196, dtype: float64>, dtype=object)` instead.