Add rows in array with nested loop

I am new to coding and trying to write a program to calculate sample size, n, in A/B testing.

I am stuck in the nested loop in main function below. I want to create an array, n_dist_all, with 3 different rows containing values of n depending upon different values of beta using nested loop. However, the function just adds the values for three different betas in the same row. I am trying to use numpy.hstack. I have also tried concatenate and append but they are all giving me the same result.

import numpy as np
import math
import scipy.stats as st

def N(alpha, beta, delta):
    Z_alpha = st.norm.ppf(1-alpha)
    Z_beta = st.norm.ppf(1-alpha)
    pA = 0.01
    pB = pA + delta
    qA = 1.0 - pA
    qB = 1.0 - qA

    n = (((Z_alpha*math.sqrt((pA+pB)*(qA+qB)/float(2)))+(Z_beta*math.sqrt((pA*qA)*(pB*qB))))/(pA-pB))**float(2)
    return int(n)


def float_range(start, stop, step):
    i = start
    while i < (stop + step):
        yield i
        i += step


def main():
    n_dist_all = np.array([])

    beta_1 = 0.2
    beta_2 = 0.1
    beta_3 = 0.05
    beta_group = [beta_1, beta_2, beta_3]

    alpha = 0.05

    for beta in beta_group:
        n_dist = np.array([])
        for delta in float_range(0.001,0.03,0.0005):
            n_dist = np.append(n_dist, N(alpha, beta, delta))
        n_dist_all = np.hstack((n_dist_all, n_dist))
        n_dist = []
    print n_dist_all

if __name__ == "__main__":
        main()