关于python：one-hot encode：column_values列表必须编码


one-hot encode : list of column_values has to encode

我在列表中有一个列名称，我想对列表中的列进行一次热编码。我想从数据集中对分类变量进行编码。我尝试了几个过程，但它给了我一个错误。

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from sklearn import preprocessing
#training_set_ed is where my .csv file is stored
edited_training_set = 'edited_dataset/test_set.csv'
trainig_set_ed = pd.read_csv(edited_training_set)

column_header = ['cat_var_1','cat_var_2','cat_var_3','cat_var_4','cat_var_5','cat_var_6',
        'cat_var_7','cat_var_8','cat_var_9','cat_var_10','cat_var_11','cat_var_12','cat_var_13',
        'cat_var_14','cat_var_15','cat_var_16','cat_var_17','cat_var_18']
clfs = {c:LabelEncoder() for c in column_header}

for col,clf in clfs.items():

      trainig_set_ed[col] = clfs[col].fit_transform(trainig_set_ed[col])

trainig_set_ed.to_csv('edited_dataset/train_set_encode.csv',sep='\t',encoding='utf-8')

投掷错误

Traceback (most recent call last):
File"preprocessing.py", line 83, in
trainig_set_ed[col] = clfs[col].fit_transform(trainig_set_ed[col])
File"/root/.local/lib/python2.7/site-packages/pandas/core/frame.py", line 2139, in getitem
return self._getitem_column(key)
File"/root/.local/lib/python2.7/site-packages/pandas/core/frame.py", line 2146, in _getitem_column
return self._get_item_cache(key)
File"/root/.local/lib/python2.7/site-packages/pandas/core/generic.py", line 1842, in _get_item_cache
values = self._data.get(item)
File"/root/.local/lib/python2.7/site-packages/pandas/core/internals.py", line 3838, in get
loc = self.items.get_loc(item)
File"/root/.local/lib/python2.7/site-packages/pandas/core/indexes/base.py", line 2524, in get_loc
return self._engine.get_loc(self._maybe_cast_indexer(key))
File"pandas/_libs/index.pyx", line 117, in pandas._libs.index.IndexEngine.get_loc
File"pandas/_libs/index.pyx", line 139, in pandas._libs.index.IndexEngine.get_loc
File"pandas/_libs/hashtable_class_helper.pxi", line 1265, in pandas._libs.hashtable.PyObjectHashTable.get_item
File"pandas/_libs/hashtable_class_helper.pxi", line 1273, in pandas._libs.hashtable.PyObjectHashTable.get_item
KeyError: 'cat_var_6'

谢谢！

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演示：

来源DF：

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In [93]: df
Out[93]:
     a    b    c
0  aaa  xxx  ddd
1  bbb  zzz  bbb
2  ccc  aaa  aaa

解决方案：

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In [94]: from sklearn.preprocessing import LabelEncoder
    ...:
    ...: cols = ['a','b','c']
    ...: clfs = {c:LabelEncoder() for c in cols}
    ...:

In [95]: for col, clf in clfs.items():
    ...:     df[col] = clfs[col].fit_transform(df[col])
    ...:

In [96]: df
Out[96]:
   a  b  c
0  0  1  2
1  1  2  1
2  2  0  0

逆变换：

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In [97]: clfs['a'].inverse_transform(df['a'])
Out[97]: array(['aaa', 'bbb', 'ccc'], dtype=object)

In [98]: clfs['b'].inverse_transform(df['b'])
Out[98]: array(['xxx', 'zzz', 'aaa'], dtype=object)

In [99]: clfs['c'].inverse_transform(df['c'])
Out[99]: array(['ddd', 'bbb', 'aaa'], dtype=object)
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