尽管数据已填充数据，pandas df.corr() 仍返回 NaN
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pandas df.corr() returns NaN despite data fed having populated data
提问by jason m
My data looks like the following:
我的数据如下所示：
print data
print data
A B
2014-04-04 163.24 191.77
2014-06-11 165.43 182.25
2014-12-22 194.44 161.44
2014-03-25 163.25 195.04
2014-11-03 190.83 164.36
2014-06-16 165.85 182.35
2014-11-24 190.07 162.15
2014-05-21 159.35 186.39
2015-01-21 177.15 152.09
2014-08-28 177.65 192.00
2014-02-19 163.26 182.95
2014-05-12 159.55 192.57
2014-07-09 164.67 188.42
2015-02-26 192.20 160.87
2014-10-14 178.70 183.80
2014-07-16 170.47 192.36
2014-01-21 173.20 188.43
2014-06-03 161.80 184.37
2014-03-17 166.84 185.81
2014-08-11 172.46 187.47
2015-01-07 187.28 155.05
2014-05-29 160.74 183.76
2015-02-11 187.65 158.20
2014-02-27 165.38 185.27
2015-01-05 188.34 159.51
2014-07-01 166.81 186.35
2015-02-18 188.67 162.19
2014-04-03 166.09 192.69
2014-10-06 187.48 189.04
2014-12-29 196.19 160.51
When I try to call data.corr()I receive back all NaN. I tested this in excel, and the correlation is indeed able to be calculated.
当我尝试打电话时，data.corr()我收到了所有NaN. 我在excel中测试了这个，确实可以计算出相关性。
Any idea why this might be the case?
知道为什么会这样吗？
I am happy to post more but i am unsure what would help.
我很高兴发布更多信息，但我不确定什么会有所帮助。
print data.info()
<class 'pandas.core.frame.DataFrame'>
Index: 298 entries, 2014-04-04 to 2014-01-29
Data columns (total 2 columns):
A 298 non-null float64
B 298 non-null float64
dtypes: float64(2)None
print data.describe()
A B
count 298.000000 298.000000
mean 175.152886 178.596242
std 11.490668 13.709316
min 152.720000 151.410000
25% 165.502500 162.655000
50% 175.480000 184.330000
75% 185.085000 189.692500
max 196.890000 197.770000
print pd.version
0.14.1
回答by EngineeredE
Jason, Using the sample data it works fine for me.
Jason，使用示例数据对我来说效果很好。
data.corr()
A B
A 1.000000 -0.779864
B -0.779864 1.000000
I noticed in your data.info() there is a 'None' tacked on to dtypes. When I load your sample data I get
我注意到在你的 data.info() 中有一个“无”附加到 dtypes。当我加载您的示例数据时，我得到
data.info()
<class 'pandas.core.frame.DataFrame'>
Index: 30 entries, 2014-04-04 to 2014-12-29
Data columns (total 2 columns):
A 30 non-null float64
B 30 non-null float64
dtypes: float64(2)
I imagine what's causing that 'None' is causing your problem.
我想是什么导致“无”导致您的问题。
Hope this helps [wish I could leave as a comment but don't have the reputation yet!]
希望这会有所帮助 [希望我可以留下评论但还没有声誉！]
