pandas 熊猫数据帧操作中不支持的操作数
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unsupported operand in pandas dataframe operation
提问by tomasz74
I have pandas DataFrame. I would like to get single value from a column based on a condition involving two another column. I am looking for the value from the column3 for which is the biggest distance in the column1 and 2.
我有Pandas数据框。我想根据涉及另外两列的条件从一列中获取单个值。我正在寻找 column3 中的值，该值是 column1 和 2 中的最大距离。
I build the simple example which works:
我构建了一个简单的例子：
d = pd.DataFrame({'c1':[.1,3,11.3],'c2':[3,6,.6],'c3':[8,.8,10.9]})
print'data d=\n%s\n' % d
x = float(d.c3[abs(d.c1-d.c2)==max(abs(d.c1-d.c2))].values)
print 'the value of x= \n%s\n' % x
The output from this example is as I expect:
这个例子的输出正如我所期望的：
c1 c2 c3
0 0.1 3.0 8.0
1 3.0 6.0 0.8
2 11.3 0.6 10.9
the value of x=
10.9
I try to apply exactly the same logic to my original problem with large dataframe inside a class. The code is:
我尝试将完全相同的逻辑应用于我在类中使用大数据框的原始问题。代码是：
yInit = float(self.DenFrame.Depth[abs(self.DenFrame.Hper-self.DenFrame.Vper)==max(abs(self.DenFrame.Hper-self.DenFrame.Vper))].values)
but this code produce an error:
但此代码产生错误：
...
File "C:\Python27\lib\site-packages\pandas-0.9.0-py2.7-win32.egg\pandas\core\series.py", line 73, in wrapper
return Series(na_op(self.values, other.values),
File "C:\Python27\lib\site-packages\pandas-0.9.0-py2.7-win32.egg\pandas\core\series.py", line 59, in na_op
result[mask] = op(x[mask], y[mask])
TypeError: unsupported operand type(s) for -: 'str' and 'str'
I found in herethat there could be a problem with type of the columns but Depth is type numpy.float64Hper is type floatVper is type floatso I understand how it can apply to my problem.
我在这里发现列的类型可能有问题，但深度是numpy.float64Hper 类型，floatVper 是类型，float所以我了解它如何适用于我的问题。
I don't know from this point what to do as I understand the same code works in one case but not in another and I cannot spot the problem.
从这一点上我不知道该怎么做，因为我知道相同的代码在一种情况下有效，但在另一种情况下无效，而且我无法发现问题。
回答by Andy Hayden
You have some strings in your DenFrame.Hperand DenFrame.Vper.
您的DenFrame.Hperand 中有一些字符串DenFrame.Vper。
You can see this by checking the dtypeor type of each element:
您可以通过检查dtype每个元素的or 类型来查看这一点：
In [11]: df.Hper.dtype
Out[11]: dtype('object')
Means that the numpy array could contain various types, we can see what these types are:
意味着 numpy 数组可以包含各种类型，我们可以看到这些类型是什么：
In [12]: DenFrame.Hper.map(type).unique()
Out[12]: [<type 'float'> <type 'str'>]
And you could inspect which entries are strings:
您可以检查哪些条目是字符串：
DenFrame[DenFrame.Hper.map(type) == str]
Perhaps it makes sense to only include those which are floats:
也许只包括那些浮动的东西是有意义的：
DenFrame_floats = DenFrame[(DenFrame.Hper.map(type) == float) &
(DenFrame.Vper.map(type) == float)]
or you could (if it's possible) convert them to floats:
或者您可以（如果可能）将它们转换为浮点数：
DenFrame.Hper = DenFrame.Hper.apply(float)
