bootstrap.py

def bootstrap(data, col, st_dev=False, rep=1000):
    
    if not st_dev:
        means = []
        n = len(data)

        for i in range(rep):
            sample = data.sample(n=n, replace=True)
            mean = sample[col].mean()
            means.append(mean)

        return pd.DataFrame(means, columns=['means'])
    
    else:
        st_devs = []
        n = len(data)

        for i in range(rep):
            sample = data.sample(n=n, replace=True)
            st_dev = sample[col].std()
            st_devs.append(st_dev)

        return pd.DataFrame(stds, columns=['st_dev'])