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Accepted
Giampaolo Levorato
Asked: 2024-08-25 17:11:18 +0800 CST

将 statsmodels summary() 导出为 .png

  • 772

我已经训练了glm如下内容：

    fitGlm = smf.glm( listOfInModelFeatures,
          family=sm.families.Binomial(),data=train, freq_weights = train['sampleWeight']).fit()

结果看起来不错：

print(fitGlm.summary())

                 Generalized Linear Model Regression Results                  
==============================================================================
Dep. Variable:                 Target   No. Observations:              1065046
Model:                            GLM   Df Residuals:               4361437.81
Model Family:                Binomial   Df Model:                            7
Link Function:                  Logit   Scale:                          1.0000
Method:                          IRLS   Log-Likelihood:            -6.0368e+05
Date:                Sun, 25 Aug 2024   Deviance:                   1.2074e+06
Time:                        09:03:54   Pearson chi2:                 4.12e+06
No. Iterations:                     8   Pseudo R-squ. (CS):             0.1716
Covariance Type:            nonrobust                                         
===========================================================================================
                              coef    std err          z      P>|z|      [0.025      0.975]
-------------------------------------------------------------------------------------------
Intercept                   3.2530      0.003   1074.036      0.000       3.247       3.259
feat1                       0.6477      0.004    176.500      0.000       0.641       0.655
feat2                       0.3939      0.006     71.224      0.000       0.383       0.405
feat3                       0.1990      0.007     28.294      0.000       0.185       0.213
feat4                       0.4932      0.009     54.614      0.000       0.476       0.511
feat5                       0.4477      0.005     90.323      0.000       0.438       0.457
feat6                       0.3031      0.005     57.572      0.000       0.293       0.313
feat7                       0.3711      0.004     87.419      0.000       0.363       0.379
===========================================================================================

然后我尝试按照这里的建议将其summary()导出.png：

Python：如何将 statsmodels 结果保存为图像文件？

因此，我写了这样的代码：

    fig, ax = plt.subplots(figsize=(16, 8))
    summary = []
    fitGlm.summary(print_fn=lambda x: summary.append(x))
    summary = '\n'.join(summary)
    ax.text(0.01, 0.05, summary, fontfamily='monospace', fontsize=12)
    ax.axis('off')
    plt.tight_layout()
    plt.savefig('output.png', dpi=300, bbox_inches='tight')

但是我收到此错误：

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Cell In[57], line 57
     55 fig, ax = plt.subplots(figsize=(16, 8))
     56 summary = []
---> 57 fitGlm.summary(print_fn=lambda x: summary.append(x))
     58 summary = '\n'.join(summary)
     59 ax.text(0.01, 0.05, summary, fontfamily='monospace', fontsize=12)

TypeError: GLMResults.summary() got an unexpected keyword argument 'print_fn'

看起来好像print_fn没有被 statsmodels 识别？

有人能帮帮我吗？

python

1 个回答

  1. Best Answer

    我设置了一个测试来查看 print_fn 可以在何处使用。我也查看了上一个问题发布的解决方案，但在文档中找不到 print_fn。

    我尝试将其转换为制表格式以便将摘要保存为 png：

    import matplotlib.pyplot as plt
import pandas as pd

# Convert the summary table to a pandas DataFrame
# change tables [0] to [1] to get the second table
summary_df = pd.read_html(model.summary().tables[0].as_html(), header=0, index_col=0)[0]

# Get the headers
headers = summary_df.columns.tolist()

# Convert the DataFrame to a list of lists and add the headers
summary_list = [headers] + summary_df.values.tolist()

# Create a new figure
fig, ax = plt.subplots()

# Remove the axes
ax.axis('off')

# Add a table to the figure
table = plt.table(cellText=summary_list, loc='center')

# Auto scale the table
table.auto_set_font_size(False)
table.set_fontsize(10)
table.scale(1, 1.5)

# Save the figure as a PNG file
plt.savefig('summary2.png', dpi=300, bbox_inches='tight')

    在我看来，将数据保存为 png 是一种非常不寻常的情况。它阻止用户共享信息。有选项可以将摘要导出到 csv 和 latex。如果您手动执行此操作，我建议导出到 csv 并复制粘贴为图像。或者保存为 txt 甚至截图。

    供参考：

    model.summary().as_csv()
# save as csv
with open('summary.csv', 'w') as file:
    file.write(model.summary().as_csv())

    或者

    text = model.summary().as_text()

# save to txt
with open('summary.txt', 'w') as file:
    file.write(text)
    • 1

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