Warning: file_get_contents(/data/phpspider/zhask/data//catemap/2/python/299.json): failed to open stream: No such file or directory in /data/phpspider/zhask/libs/function.php on line 167

Warning: Invalid argument supplied for foreach() in /data/phpspider/zhask/libs/tag.function.php on line 1116

Notice: Undefined index: in /data/phpspider/zhask/libs/function.php on line 180

Warning: array_chunk() expects parameter 1 to be array, null given in /data/phpspider/zhask/libs/function.php on line 181
Python 值之间的相关性_Python_Pandas - Fatal编程技术网

Python 值之间的相关性

Python 值之间的相关性,python,pandas,Python,Pandas,我想在这个数据帧中进行关联,但不是以显示的方式,而是对值进行排序​​从最低到最大 import pandas as pd import numpy as np rs = np.random.RandomState(1) df = pd.DataFrame(rs.rand(9, 8)) corr = df.corr() corr.style.background_gradient().set_precision(2) 0 1 2 3 4 5 6 7 0 1

我想在这个数据帧中进行关联,但不是以显示的方式,而是对值进行排序​​从最低到最大

import pandas as pd
import numpy as np

rs = np.random.RandomState(1)
df = pd.DataFrame(rs.rand(9, 8))
corr = df.corr()
corr.style.background_gradient().set_precision(2)

0   1   2   3   4   5   6   7
0   1   0.42    0.031   -0.16   -0.35   0.23    -0.22   0.4
1   0.42    1   -0.24   -0.55   0.011   0.3     -0.26   0.23
2   0.031   -0.24   1   0.29    0.44    0.29    0.23    0.25
3   -0.16   -0.55   0.29    1   -0.33   -0.42   0.58    -0.37
4   -0.35   0.011   0.44    -0.33   1   0.46    0.074   0.19
5   0.23    0.3     0.29    -0.42   0.46    1   -0.41   0.71
6   -0.22   -0.26   0.23    0.58    0.074   -0.41   1   -0.66
7   0.4     0.23    0.25    -0.37   0.19    0.71    -0.66   1
您可以使用:

结果:

          0         1         2         3         4         5         6         7
0  1.000000  0.418246  0.030692 -0.160001 -0.352993  0.230069 -0.216804  0.395662
1  0.418246  1.000000 -0.244115 -0.549013  0.010745  0.299203 -0.262351  0.232681
2  0.030692 -0.244115  1.000000  0.288011  0.435907  0.285408  0.225205  0.253840
3 -0.160001 -0.549013  0.288011  1.000000 -0.326950 -0.415688  0.578549 -0.366539
4 -0.352993  0.010745  0.435907 -0.326950  1.000000  0.455738  0.074293  0.193905
5  0.230069  0.299203  0.285408 -0.415688  0.455738  1.000000 -0.413383  0.708467
6 -0.216804 -0.262351  0.225205  0.578549  0.074293 -0.413383  1.000000 -0.664207
7  0.395662  0.232681  0.253840 -0.366539  0.193905  0.708467 -0.664207  1.000000
          0         1         7         5         2         3         6         4
0  1.000000  0.418246  0.395662  0.230069  0.030692 -0.160001 -0.216804 -0.352993
1  0.418246  1.000000  0.232681  0.299203 -0.244115 -0.549013 -0.262351  0.010745
2  0.030692 -0.244115  0.253840  0.285408  1.000000  0.288011  0.225205  0.435907
3 -0.160001 -0.549013 -0.366539 -0.415688  0.288011  1.000000  0.578549 -0.326950
4 -0.352993  0.010745  0.193905  0.455738  0.435907 -0.326950  0.074293  1.000000
5  0.230069  0.299203  0.708467  1.000000  0.285408 -0.415688 -0.413383  0.455738
6 -0.216804 -0.262351 -0.664207 -0.413383  0.225205  0.578549  1.000000  0.074293
7  0.395662  0.232681  1.000000  0.708467  0.253840 -0.366539 -0.664207  0.193905

请再详细说明一下或举个例子。很抱歉,可能我不清楚。例如,我希望第一行是这样的:10.42 0.4 0.23 0.031-0.16-0.22-0.35我们可以这样排序:10.42 0.4 0.23 0.031-0.16-0.22-0.35是的,使用sort\u值:
corr.sort\u值(by=0,axis=1,inplace=True)。style.background\u gradient().set\u精度(2)
Yes,所有数据帧都包含sort\u值方法corr.sort\u值(by=[1,2],axis=0,inplace=True)仅按第1列而不是第2列给我排序_值。问题出在哪里。
          0         1         2         3         4         5         6         7
0  1.000000  0.418246  0.030692 -0.160001 -0.352993  0.230069 -0.216804  0.395662
1  0.418246  1.000000 -0.244115 -0.549013  0.010745  0.299203 -0.262351  0.232681
2  0.030692 -0.244115  1.000000  0.288011  0.435907  0.285408  0.225205  0.253840
3 -0.160001 -0.549013  0.288011  1.000000 -0.326950 -0.415688  0.578549 -0.366539
4 -0.352993  0.010745  0.435907 -0.326950  1.000000  0.455738  0.074293  0.193905
5  0.230069  0.299203  0.285408 -0.415688  0.455738  1.000000 -0.413383  0.708467
6 -0.216804 -0.262351  0.225205  0.578549  0.074293 -0.413383  1.000000 -0.664207
7  0.395662  0.232681  0.253840 -0.366539  0.193905  0.708467 -0.664207  1.000000
          0         1         7         5         2         3         6         4
0  1.000000  0.418246  0.395662  0.230069  0.030692 -0.160001 -0.216804 -0.352993
1  0.418246  1.000000  0.232681  0.299203 -0.244115 -0.549013 -0.262351  0.010745
2  0.030692 -0.244115  0.253840  0.285408  1.000000  0.288011  0.225205  0.435907
3 -0.160001 -0.549013 -0.366539 -0.415688  0.288011  1.000000  0.578549 -0.326950
4 -0.352993  0.010745  0.193905  0.455738  0.435907 -0.326950  0.074293  1.000000
5  0.230069  0.299203  0.708467  1.000000  0.285408 -0.415688 -0.413383  0.455738
6 -0.216804 -0.262351 -0.664207 -0.413383  0.225205  0.578549  1.000000  0.074293
7  0.395662  0.232681  1.000000  0.708467  0.253840 -0.366539 -0.664207  0.193905