| import numpy as np | |
| import statsmodels.api as sm | |
| df = sm.datasets.ccard.load_pandas().data | |
| df['intercept'] = 1.0 | |
| model = sm.Logit(df.OWNRENT, df[['intercept', 'AGE', 'INCOME']]) | |
| result = model.fit() | |
| result.summary() | |
| # the odds | |
| np.exp(result.params) |
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