bootstrap.py

import pandas as pd
from numpy.random import randint
from numpy import median, percentile

my_data = pd.read_csv('dataset.csv')
n = len(my_data)

num_bootstrap_samples = 1000
bootstrap_results = []
for b in xrange(num_bootstrap_samples):
  sampled_data = my_data.iloc[randint(0, n, size=n)]
  med = median(sampled_data['income'])
  bootstrap_results.append(med)

ci_lower = percentile(bootstrap_results, 2.5)
ci_upper = percentile(bootstrap_results, 97.5)