python - 需要解压的值太多(预计为 2 个)？

Question

我有数据框可以使用，当我测试/分割数据时，会弹出此错误消息

需要解压的值太多(预计为 2 个)

我只是将目标列 Global 设置为 y 值，将其余列设置为 train_test_split 的 X。不确定从哪里开始解决这个问题

X = df[['Year_of_Release', 'Critic_Score', 'Critic_Count',
       'User_Score', 'User_Count', 'Platform_PC', 'Platform_PS3',
       'Platform_PS4', 'Platform_Wii', 'Platform_X360',
       'Platform_XOne', 'Genre_Action', 'Genre_Adventure', 'Genre_Fighting',
       'Genre_Misc', 'Genre_Platform', 'Genre_Puzzle', 'Genre_Racing',
       'Genre_Role-Playing', 'Genre_Shooter', 'Genre_Simulation',
       'Genre_Sports', 'Genre_Strategy', 'Rating_E', 'Rating_E10+', 'Rating_M',
       'Rating_RP', 'Rating_T']]

y = df[['Global']]

print(X.shape)
print(y.shape)

from sklearn.model_selection import train_test_split

X_train, X_test = train_test_split(X, y, train_size=0.8, test_size=0.2, random_state=42)


X_train, X_val = train_test_split(X_train, train_size=0.8, test_size=0.2, random_state=42)

target = 'Global'
y_train = X_train[target]
y_val = X_val[target]
y_test = X_test[target]

X_train = X_train.drop(columns=target)
X_val = X_val.drop(columns=target)
X_test = X_test.drop(columns=target)

X_train.shape, y_train.shape, X_val.shape, y_val.shape, X_test.shape, y_test.shape

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-75-d3fede999d7b> in <module>()
      1 from sklearn.model_selection import train_test_split
      2 
----> 3 X_train, X_test = train_test_split(X, y, train_size=0.8, test_size=0.2, random_state=42)
      4 
      5 

ValueError: too many values to unpack (expected 2)

Answer 1

X = df[['Year_of_Release', 'Critic_Score', 'Critic_Count',
       'User_Score', 'User_Count', 'Platform_PC', 'Platform_PS3',
       'Platform_PS4', 'Platform_Wii', 'Platform_X360',
       'Platform_XOne', 'Genre_Action', 'Genre_Adventure', 'Genre_Fighting',
       'Genre_Misc', 'Genre_Platform', 'Genre_Puzzle', 'Genre_Racing',
       'Genre_Role-Playing', 'Genre_Shooter', 'Genre_Simulation',
       'Genre_Sports', 'Genre_Strategy', 'Rating_E', 'Rating_E10+', 'Rating_M',
       'Rating_RP', 'Rating_T']]

y = df[['Global']]

print(X.shape)
print(y.shape)

from sklearn.model_selection import train_test_split

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)