import numpy as np

bins = ["  0-9: ","10-19: ","20-29: ","30-39: ","40-49: ","50-59: ","60-69: ","70-79: ","80-89: ","90-99: "]

def get_distribution():
    # Generate normal distribution (mean_value, standard_deviation, size)
    exam_points = np.random.normal(60, 20, 67)
    # round to integer datatype
    exam_points = np.rint(exam_points).astype(int)
    # clip values between 15 and 95
    exam_points = np.clip(exam_points, 15, 95)

    for points in exam_points:
        pass

    return exam_points

def generate_arr():
    arr = np.ndarray((10,10), dtype=object)

    for pos in range (10):
        arr[(pos,0)] = bins[pos]

    print(arr)

def main():
    generate_arr()

main()