我有一个pandas数据帧
>>> ris
Pr Err Tr Err Pr Err Tr Err Pr Err Tr Err
Data nodes
boston 10 0.456532 0.458170 0.868836 0.810764 0.826163 0.775337
30 0.512490 0.460417 0.623531 0.511936 0.600965 0.511689
50 0.547000 0.447586 0.529250 0.377296 0.528913 0.398829
100 0.781039 0.585664 0.452310 0.295945 0.480067 0.297470
500 1.635246 1.084544 0.490629 0.188229 0.488209 0.174449
1000 2.347967 1.325350 0.482844 0.153391 0.497174 0.139749
5000 6.112860 3.248268 0.469981 0.141781 0.465061 0.055253
crime 10 0.713751 0.534806 0.959765 0.909708 0.964622 0.932691
30 0.897192 0.648438 0.957707 0.814946 0.924469 0.835406
50 1.259947 0.835315 0.958826 0.763053 0.935411 0.752043
100 1.788571 1.188414 0.893760 0.675943 0.878403 0.638281
500 3.705343 1.925542 0.875850 0.442439 0.917819 0.210832
1000 5.364042 2.730365 0.877851 0.401714 0.834504 0.095997
5000 11.592207 5.696515 0.924210 0.128621 0.757942 0.008422
diabetes 10 0.724064 0.708919 0.896751 0.884411 0.876967 0.871300
30 0.776270 0.697421 0.748575 0.718090 0.770397 0.722314
50 0.831268 0.738589 0.744160 0.670036 0.732472 0.681045
100 0.944318 0.746765 0.725481 0.644612 0.739595 0.646943
500 2.049824 1.295420 0.744597 0.638818 0.848764 0.342133
1000 3.023125 1.945415 0.726805 0.632582 0.841408 0.202868
5000 8.248108 4.950347 0.729375 0.614312 0.849506 0.049566
j2m 10 0.262522 0.220741 0.704471 0.707829 0.975908 0.971793
30 0.329172 0.249799 0.612609 0.595846 0.937233 0.913272
50 0.540852 0.392339 0.569175 0.550119 0.905082 0.870621
100 0.837123 0.648585 0.537721 0.499987 0.846324 0.802037
500 1.939758 1.398511 0.472884 0.354905 0.683411 0.496362
1000 2.981468 2.151604 0.431983 0.307520 0.663899 0.339811
5000 6.577426 4.737849 0.408002 0.290080 0.452132 0.022331
wine 10 0.821250 0.806193 0.940909 0.934531 0.940558 0.933438
30 0.838295 0.817293 0.887308 0.862306 0.889729 0.876763
50 0.897821 0.847260 0.872193 0.837761 0.872479 0.835796
100 1.009768 0.909182 0.857645 0.814801 0.862258 0.809452
500 1.675544 1.310232 0.855094 0.783809 0.940632 0.618788
1000 2.094566 1.548781 0.863529 0.765906 0.973830 0.432291
5000 5.004573 3.293214 0.861923 0.698045 0.920401 0.115565
>>>
我希望在乳胶文档中使用此表。我想完全按原样打印，但是采用乳胶格式。
我尝试用
打印它 print(ris.to_latex(float_format= lambda x: str(np.round(x, 3))))
我得到的结果不是我原来的数据帧。
>>> \begin{tabular}{llrrrrrr}
\toprule
& & Pr Err & Tr Err & Pr Err & Tr Err & Pr Err & Tr Err \\
\midrule
boston & 10 & & & & & & \\
crime & 30 & 0.457 & 0.458 & 0.869 & 0.811 & 0.826 & 0.775 \\
diabetes & 50 & 0.512 & 0.46 & 0.624 & 0.512 & 0.601 & 0.512 \\
j2m & 100 & 0.547 & 0.448 & 0.529 & 0.377 & 0.529 & 0.399 \\
wine & 500 & 0.781 & 0.586 & 0.452 & 0.296 & 0.48 & 0.297 \\
\bottomrule
\end{tabular}
>>>
我该如何解决？
编辑：
使用命令print(ris.reset_index().to_latex(index=False))我得到：
\begin{tabular}{lrrrrrrr}
\toprule
Data & nodes & Pr Err & Tr Err & Pr Err & Tr Err & Pr Err & Tr Err \\
\midrule
boston & 10 & 0.456532 & 0.458170 & 0.868836 & 0.810764 & 0.826163 & 0.775337 \\
boston & 30 & 0.512490 & 0.460417 & 0.623531 & 0.511936 & 0.600965 & 0.511689 \\
boston & 50 & 0.547000 & 0.447586 & 0.529250 & 0.377296 & 0.528913 & 0.398829 \\
boston & 100 & 0.781039 & 0.585664 & 0.452310 & 0.295945 & 0.480067 & 0.297470 \\
boston & 500 & 1.635246 & 1.084544 & 0.490629 & 0.188229 & 0.488209 & 0.174449 \\
boston & 1000 & 2.347967 & 1.325350 & 0.482844 & 0.153391 & 0.497174 & 0.139749 \\
boston & 5000 & 6.112860 & 3.248268 & 0.469981 & 0.141781 & 0.465061 & 0.055253 \\
crime & 10 & 0.713751 & 0.534806 & 0.959765 & 0.909708 & 0.964622 & 0.932691 \\
crime & 30 & 0.897192 & 0.648438 & 0.957707 & 0.814946 & 0.924469 & 0.835406 \\
crime & 50 & 1.259947 & 0.835315 & 0.958826 & 0.763053 & 0.935411 & 0.752043 \\
crime & 100 & 1.788571 & 1.188414 & 0.893760 & 0.675943 & 0.878403 & 0.638281 \\
crime & 500 & 3.705343 & 1.925542 & 0.875850 & 0.442439 & 0.917819 & 0.210832 \\
crime & 1000 & 5.364042 & 2.730365 & 0.877851 & 0.401714 & 0.834504 & 0.095997 \\
crime & 5000 & 11.592207 & 5.696515 & 0.924210 & 0.128621 & 0.757942 & 0.008422 \\
diabetes & 10 & 0.724064 & 0.708919 & 0.896751 & 0.884411 & 0.876967 & 0.871300 \\
diabetes & 30 & 0.776270 & 0.697421 & 0.748575 & 0.718090 & 0.770397 & 0.722314 \\
diabetes & 50 & 0.831268 & 0.738589 & 0.744160 & 0.670036 & 0.732472 & 0.681045 \\
diabetes & 100 & 0.944318 & 0.746765 & 0.725481 & 0.644612 & 0.739595 & 0.646943 \\
diabetes & 500 & 2.049824 & 1.295420 & 0.744597 & 0.638818 & 0.848764 & 0.342133 \\
diabetes & 1000 & 3.023125 & 1.945415 & 0.726805 & 0.632582 & 0.841408 & 0.202868 \\
diabetes & 5000 & 8.248108 & 4.950347 & 0.729375 & 0.614312 & 0.849506 & 0.049566 \\
j2m & 10 & 0.262522 & 0.220741 & 0.704471 & 0.707829 & 0.975908 & 0.971793 \\
j2m & 30 & 0.329172 & 0.249799 & 0.612609 & 0.595846 & 0.937233 & 0.913272 \\
j2m & 50 & 0.540852 & 0.392339 & 0.569175 & 0.550119 & 0.905082 & 0.870621 \\
j2m & 100 & 0.837123 & 0.648585 & 0.537721 & 0.499987 & 0.846324 & 0.802037 \\
j2m & 500 & 1.939758 & 1.398511 & 0.472884 & 0.354905 & 0.683411 & 0.496362 \\
j2m & 1000 & 2.981468 & 2.151604 & 0.431983 & 0.307520 & 0.663899 & 0.339811 \\
j2m & 5000 & 6.577426 & 4.737849 & 0.408002 & 0.290080 & 0.452132 & 0.022331 \\
wine & 10 & 0.821250 & 0.806193 & 0.940909 & 0.934531 & 0.940558 & 0.933438 \\
wine & 30 & 0.838295 & 0.817293 & 0.887308 & 0.862306 & 0.889729 & 0.876763 \\
wine & 50 & 0.897821 & 0.847260 & 0.872193 & 0.837761 & 0.872479 & 0.835796 \\
wine & 100 & 1.009768 & 0.909182 & 0.857645 & 0.814801 & 0.862258 & 0.809452 \\
wine & 500 & 1.675544 & 1.310232 & 0.855094 & 0.783809 & 0.940632 & 0.618788 \\
wine & 1000 & 2.094566 & 1.548781 & 0.863529 & 0.765906 & 0.973830 & 0.432291 \\
wine & 5000 & 5.004573 & 3.293214 & 0.861923 & 0.698045 & 0.920401 & 0.115565 \\
\bottomrule
\end{tabular}