使用 scikit 学习 DictVectorizer 对特定列进行矢量化时出现问题？

Question

我想了解如何完成我正在玩的简单预测任务 dataset, also is here in a different format. Wich is about the students performance in some course, I would like to vectorize some columns of the dataset in order to not use all the data (just to learn how it works). So I tried the following, with DictVectorizer:

import pandas as pd
from sklearn.feature_extraction import DictVectorizer

training_data = pd.read_csv('/Users/user/Downloads/student/student-mat.csv')

dict_vect = DictVectorizer(sparse=False)

training_matrix = dict_vect.fit_transform(training_data['G1','G2','sex','school','age'])
training_matrix.toarray()

然后我想像这样传递另一个特征行：

testing_data = pd.read_csv('/Users/user/Downloads/student/student-mat_test.csv')
test_matrix = dict_vect.transform(testing_data['G1','G2','sex','school','age'])

这个问题是我得到以下回溯：

/usr/local/Cellar/python/2.7.8_1/Frameworks/Python.framework/Versions/2.7/bin/python2.7 school_2.py
Traceback (most recent call last):
  File "/Users/user/PycharmProjects/PAN-pruebas/escuela_2.py", line 14, in <module>
    X = dict_vect.fit_transform(df['sex','age','address','G1','G2'].values)
  File "school_2.py", line 1787, in __getitem__
    return self._getitem_column(key)
  File "/usr/local/lib/python2.7/site-packages/pandas/core/frame.py", line 1794, in _getitem_column
    return self._get_item_cache(key)
  File "/usr/local/lib/python2.7/site-packages/pandas/core/generic.py", line 1079, in _get_item_cache
    values = self._data.get(item)
  File "/usr/local/lib/python2.7/site-packages/pandas/core/internals.py", line 2843, in get
    loc = self.items.get_loc(item)
  File "/usr/local/lib/python2.7/site-packages/pandas/core/index.py", line 1437, in get_loc
    return self._engine.get_loc(_values_from_object(key))
  File "pandas/index.pyx", line 134, in pandas.index.IndexEngine.get_loc (pandas/index.c:3824)
  File "pandas/index.pyx", line 154, in pandas.index.IndexEngine.get_loc (pandas/index.c:3704)
  File "pandas/hashtable.pyx", line 697, in pandas.hashtable.PyObjectHashTable.get_item (pandas/hashtable.c:12349)
  File "pandas/hashtable.pyx", line 705, in pandas.hashtable.PyObjectHashTable.get_item (pandas/hashtable.c:12300)
KeyError: ('sex', 'age', 'address', 'G1', 'G2')

Process finished with exit code 1

知道如何正确向量化两个数据（即训练和测试）吗？并用 .toarray()

显示两个矩阵

更新

>>>print training_data.info()
/usr/local/Cellar/python/2.7.8_1/Frameworks/Python.framework/Versions/2.7/bin/python2.7 /Users/user/PycharmProjects/PAN-pruebas/escuela_3.py
<class 'pandas.core.frame.DataFrame'>
MultiIndex: 396 entries, (school, sex, age, address, famsize, Pstatus, Medu, Fedu, Mjob, Fjob, reason, guardian, traveltime, studytime, failures, schoolsup, famsup, paid, activities, nursery, higher, internet, romantic, famrel, freetime, goout, Dalc, Walc, health, absences) to (MS, M, 19, U, LE3, T, 1, 1, other, at_home, course, father, 1, 1, 0, no, no, no, no, yes, yes, yes, no, 3, 2, 3, 3, 3, 5, 5)
Data columns (total 3 columns):
id         396 non-null object
content    396 non-null object
label      396 non-null object
dtypes: object(3)
memory usage: 22.7+ KB
None

Process finished with exit code 0

Answer 1

您需要传递一个列表：

test_matrix = dict_vect.transform(testing_data[['G1','G2','sex','school','age']])

您所做的是尝试使用以下键为您的 df 编制索引：

['G1','G2','sex','school','age']

这就是为什么你得到 KeyError 的原因，因为没有像上面这样命名的单列，要 select 多列你需要传递列名列表和双下标 [[col_list]]

示例：

In [43]:

df = pd.DataFrame(columns=['a','b'])
df
Out[43]:
Empty DataFrame
Columns: [a, b]
Index: []
In [44]:

df['a','b']
---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
<ipython-input-44-33332c7e7227> in <module>()
----> 1 df['a','b']

......    
pandas\hashtable.pyx in pandas.hashtable.PyObjectHashTable.get_item (pandas\hashtable.c:12349)()

pandas\hashtable.pyx in pandas.hashtable.PyObjectHashTable.get_item (pandas\hashtable.c:12300)()

KeyError: ('a', 'b')

但这行得通：

In [45]:

df[['a','b']]
Out[45]:
Empty DataFrame
Columns: [a, b]
Index: []

使用 scikit 学习 DictVectorizer 对特定列进行矢量化时出现问题？

Problems vectorizing specific columns with scikit learn DictVectorizer?

python

machine-learning

python-2.7

pandas

scikit-learn