pandas Python 熊猫相关 corr() TypeError：无法将 ['pearson'] 与块值进行比较
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Python pandas correlation corr() TypeError: Could not compare ['pearson'] with block values
提问by MJS
one = pd.DataFrame(data=[1,2,3,4,5], index=[1,2,3,4,5])
two = pd.DataFrame(data=[5,4,3,2,1], index=[1,2,3,4,5])
one.corr(two)
I think it should return a float = -1.00 but instead it's generating the following error:
我认为它应该返回一个 float = -1.00 但它产生了以下错误：
TypeError: Could not compare ['pearson'] with block values
类型错误：无法将 ['pearson'] 与块值进行比较
Thanks in advance for your help.
在此先感谢您的帮助。
回答by zero323
pandas.DataFrame.corrcomputes pairwise correlation between the columns of a single data frame. What you need here is pandas.DataFrame.corrwith:
pandas.DataFrame.corr计算单个数据帧的列之间的成对相关性。你需要的是pandas.DataFrame.corrwith：
>>> one.corrwith(two)
0 -1
dtype: float64
回答by Brian
You are operating on a DataFramewhen you should be operating on a Series.
您在操作DataFrame时，你应该对进行操作Series。
In [1]: import pandas as pd
In [2]: one = pd.DataFrame(data=[1,2,3,4,5], index=[1,2,3,4,5])
In [3]: two = pd.DataFrame(data=[5,4,3,2,1], index=[1,2,3,4,5])
In [4]: one
Out[4]:
0
1 1
2 2
3 3
4 4
5 5
In [5]: two
Out[5]:
0
1 5
2 4
3 3
4 2
5 1
In [6]: one[0].corr(two[0])
Out[6]: -1.0
Why subscript with [0]? Because that is the name of the column in the DataFrame, since you didn't give it one. When you reference a column in a DataFrame, it will return a Series, which is 1-dimensional. The documentation for this function is here.
为什么用 下标[0]？因为那是 中列的名称DataFrame，因为你没有给它一个。当您引用 a 中的列时DataFrame，它将返回 a Series，它是一维的。此功能的文档在此处。
