How to get odds-ratios and other related features with scikit-learn

You can get the odds ratios by taking the exponent of the coeffecients:

import numpy as np
X = df.female.values.reshape(200,1)
clf.fit(X,y)
np.exp(clf.coef_)

# array([[ 1.80891307]])

As for the other statistics, these are not easy to get from scikit-learn (where model evaluation is mostly done using cross-validation), if you need them you're better off using a different library such as statsmodels.

In addition to @maxymoo's answer, to get other statistics, statsmodel can be used. Assuming that you have your data in a DataFrame called df, the code below should show a good summary:

import pandas as pd
from patsy import dmatrices
import statsmodels.api as sm 

y, X = dmatrices( 'label ~ age + gender', data=df, return_type='dataframe')
mod = sm.Logit(y, X)
res = mod.fit()
print res.summary()