如何獲得列車和測試集的虛擬變量？

Question

我想兩個列車&測試集創建分類字段的虛擬變量，然後僅在兩車&測試組共同的特徵訓練分類。我在下面的代碼中運行兩個數據集中創建虛擬變量，但得到TypeError。

我Jupyter筆記本的一個單元下面輸入

def get_features(train, test): 
trainval = list(train.columns.values) # list train features 
testval = list(test.columns.values) # list test features 
features = list(set(trainval) & set(testval)) # check wich features are in common (remove the outcome column) 
features.remove('Id') # remove non-usefull id column 
return features 

def process_features(train,test): 
tables=[test,train] 
for table in tables: 
    table['SoldDt']= table[['MoSold','YrSold']].apply(lambda x : '{}-{}'.format(x[0],x[1]), axis=1) 
    table['YearBuilt']= pd.to_datetime(table.YearBuilt,format="%Y") 
    table['YearRemodAdd']= pd.to_datetime(table.YearRemodAdd,format="%Y") 
    table['SoldDt']= pd.to_datetime(table.SoldDt,format="%m-%Y") 
    table.GarageYrBlt.fillna(1,inplace=True) 
    table.GarageYrBlt=table.GarageYrBlt.apply(int) 
    table.GarageYrBlt.replace(1,'NaT',inplace=True) 
    table['GarageYrBlt']= pd.to_datetime(table.GarageYrBlt,format="%Y") 
    del table['MoSold'] 
    del table['YrSold'] 
    table['MSSubClass']=table['MSSubClass'].apply(str) 
    table['OverallQual']=table['OverallQual'].apply(str) 
    table['OverallCond']=table['OverallCond'].apply(str) 
    table.Alley.fillna("NotAvl",inplace=True) 
    table.BsmtQual.fillna("NB",inplace=True) 
    table.BsmtCond.fillna("NB",inplace=True) 
    table.BsmtExposure.fillna("NB",inplace=True) 
    table.BsmtFinType1.fillna("NB",inplace=True) 
    table.BsmtFinType2.fillna("NB",inplace=True) 
    table.FireplaceQu.fillna("NF",inplace=True) 
    table.GarageType.fillna("NG",inplace=True) 
    table.GarageFinish.fillna("NG",inplace=True) 
    table.GarageQual.fillna("NG",inplace=True) 
    table.GarageCond.fillna("NG",inplace=True) 
    table.PoolQC.fillna("NP",inplace=True) 
    table.Fence.fillna("NFe",inplace=True) 
    table.MiscFeature.fillna("NotAvl",inplace=True) 
    table.LotFrontage.fillna(0,inplace=True) 

    table=table.dropna(inplace=True) 
    table=pd.get_dummies(table) 

features = get_features(train,test) 
return train,test,features 

然後，我調用該函數在不同的細胞

train = pd.read_csv('/mnt/disk2/Data/HousePrices/train.csv') 
test = pd.read_csv('/mnt/disk2/Data/HousePrices/test.csv') 
train,test,features = process_features(train,test) 

我得到以下錯誤

--------------------------------------------------------------------------- 
TypeError         Traceback (most recent call last) 
<ipython-input-17-b2727d6cdc63> in <module>() 
    1 train = pd.read_csv('/mnt/disk2/Data/HousePrices/train.csv') 
    2 test = pd.read_csv('/mnt/disk2/Data/HousePrices/test.csv') 
----> 3 train,test,features = process_features(train,test) 

<ipython-input-16-dc47e5e9f9b6> in process_features(train, test) 
40 
41   table=table.dropna(inplace=True) 
---> 42   table=pd.get_dummies(table) 
43 
44  print ("Getting features...") 

/usr/local/lib/python3.5/dist-packages/pandas/core/reshape.py in  get_dummies(data, prefix, prefix_sep, dummy_na, columns, sparse, drop_first) 
    1102  else: 
    1103  result = _get_dummies_1d(data, prefix, prefix_sep, dummy_na, 
-> 1104         sparse=sparse, drop_first=drop_first) 
    1105  return result 
    1106 

/usr/local/lib/python3.5/dist-packages/pandas/core/reshape.py in _get_dummies_1d(data, prefix, prefix_sep, dummy_na, sparse, drop_first) 
    1123  # if all NaN 
    1124  if not dummy_na and len(levels) == 0: 
-> 1125   return get_empty_Frame(data, sparse) 
    1126 
    1127  codes = codes.copy() 

/usr/local/lib/python3.5/dist-packages/pandas/core/reshape.py in get_empty_Frame(data, sparse) 
    1115    index = data.index 
    1116   else: 
-> 1117    index = np.arange(len(data)) 
    1118   if not sparse: 
    1119    return DataFrame(index=index) 

TypeError: object of type 'NoneType' has no len() 

Answer 1

在這條線

table=table.dropna(inplace=True) 

dropna返回None因爲文檔狀態

inplace : boolean, default False 
    If True, do operation inplace and return None. 

但你試圖把該None值傳遞給get_dummies()。