我正在通过本教程工作:http://ahmedbesbes.com/how-to-score-08134-in-titanic-kaggle-kaggle-challenge-challenge.html
,直到我到达中间部分的最后一部分之前,它没有任何问题:
,如您所见,功能以不同的间隔范围。让我们在单位间隔中对所有这些都进行标准化。除了我们需要提交需要的旅客
我们所需要的所有这些In [48]:
>>> def scale_all_features():
>>> global combined
>>> features = list(combined.columns)
>>> features.remove('PassengerId')
>>> combined[features] = combined[features].apply(lambda x: x/x.max(), axis=0)
>>> print 'Features scaled successfully !'
In [49]:
>>> scale_all_features()
成功缩放的功能!
,尽管在我的python脚本中为单词键入单词:
#Cell 48
GreatDivide.split()
def scale_all_features():
global combined
features = list(combined.columns)
features.remove('PassengerId')
combined[features] = combined[features].apply(lambda x: x/x.max(), axis=0)
print 'Features scaled successfully !'
#Cell 49
GreatDivide.split()
scale_all_features()
它一直给我一个错误:
--------------------------------------------------48--------------------------------------------------
--------------------------------------------------49--------------------------------------------------
Traceback (most recent call last):
File "KaggleTitanic[2-FE]--[01].py", line 350, in <module>
scale_all_features()
File "KaggleTitanic[2-FE]--[01].py", line 332, in scale_all_features
combined[features] = combined[features].apply(lambda x: x/x.max(), axis=0)
File "/usr/local/lib/python2.7/dist-packages/pandas/core/frame.py", line 4061, in apply
return self._apply_standard(f, axis, reduce=reduce)
File "/usr/local/lib/python2.7/dist-packages/pandas/core/frame.py", line 4157, in _apply_standard
results[i] = func(v)
File "KaggleTitanic[2-FE]--[01].py", line 332, in <lambda>
combined[features] = combined[features].apply(lambda x: x/x.max(), axis=0)
File "/usr/local/lib/python2.7/dist-packages/pandas/core/ops.py", line 651, in wrapper
return left._constructor(wrap_results(na_op(lvalues, rvalues)),
File "/usr/local/lib/python2.7/dist-packages/pandas/core/ops.py", line 592, in na_op
result[mask] = op(x[mask], y)
TypeError: ("unsupported operand type(s) for /: 'str' and 'str'", u'occurred at index Ticket')
这里有什么问题?所有前49个部分都没有任何问题,因此,如果我遇到了一个错误,那么现在就会显示出来吧?
您可以帮助确保数学转换仅发生在数字列上。
numeric_cols = combined.columns[combined.dtypes != 'object']
combined.loc[:, numeric_cols] = combined[numeric_cols] / combined[numeric_cols].max()
不需要该应用功能。