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      1. statsmodels汇总到乳胶

        statsmodels summary to latex(statsmodels汇总到乳胶)
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                • 本文介绍了statsmodels汇总到乳胶的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着跟版网的小编来一起学习吧!

                  问题描述

                  我是 latex 新手,我想将 statsmodels(python-package) 摘要导入到我的乳胶报告.我发现可以使用以下方法将摘要转换为乳胶表格:latex_as_tabular.到目前为止,一切正常.现在我必须存储表格,但我不太明白它是如何工作的.

                  I'm a newbie to latex and I want to import a statsmodels(python-package) summary to my report in latex. I found that it's possible to transform a summary into a latex tabular with the following method: latex_as_tabular. Until now everything is working. Now I have to store the tabular, but I don't really understand how this works.

                  我想我必须使用以下命令:

                  I suppose I have to use the following commands:

                  x_values=sm.add_constant(x_values)
                  model=sm.OLS(y_values, x_values)
                  results=model.fit()
                  tbl=results.summary(xname=['b,'a'],yname='y')
                  with open('c:/temp/temp.tex','w') as fh:
                      fh.write( tbl.as_latex_tabular() )
                  

                  此代码直到现在才起作用.大多数情况下,控制台都会给出错误:tex-file does not exist or not allowed in this map.我真的不明白我必须在这里做什么.有人可以帮我吗?

                  this code doesn't work until now. most of the times the console gives the error: tex-file doesn't exists or not permitted in this map. I don't really understand what I have to do here. Could someone please help me with this ?

                  推荐答案

                  这好像是个误会.您可以通过 summary.as_latex() 或通过调用 table.as_latex_tabular().

                  That seems to be a misunderstanding. You can either convert a whole summary into latex via summary.as_latex() or convert its tables one by one by calling table.as_latex_tabular() for each table.

                  以下示例代码取自 statsmodels 文档.请注意,您不能在 summary 对象上调用 as_latex_tabular.

                  The following example code is taken from statsmodels documentation. Note that you cannot call as_latex_tabular on a summary object.

                  import numpy as np
                  import statsmodels.api as sm
                  
                  nsample = 100
                  x = np.linspace(0, 10, 100)
                  X = np.column_stack((x, x**2))
                  beta = np.array([1, 0.1, 10])
                  e = np.random.normal(size=nsample)
                  
                  X = sm.add_constant(X)
                  y = np.dot(X, beta) + e
                  
                  model = sm.OLS(y, X)
                  results = model.fit()
                  
                  # do either
                  print(results.summary().as_latex())
                  
                  # alternatively
                  for table in results.summary().tables:
                      print(table.as_latex_tabular())
                  

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