z_table.py

# copy and paste the script on a Jupyter Notebook to have the 
# table printed on screen

import numpy as np
import pandas as pd
from scipy.integrate import quad

def normal_probability_density(x):
    constant = 1.0 / np.sqrt(2 * np.pi)
    return(constant * np.exp((-x**2) / 2))

standard_normal_table = pd.DataFrame(data=[],
                                     index = np.round(np.arange(0, 3.5, .1), 2),
                                     columns=np.round(np.arange(0.00, 0.1, 0.01), 2))

for index in standard_normal_table.index:
  for column in standard_normal_table.columns:
    z = np.round(index + column, 2)
    value, _ = quad(normal_probability_density, np.NINF, z)
    standard_normal_table.loc[index, column] = value

standard_normal_table.index = standard_normal_table.index.astype(str)
standard_normal_table.columns = (str(column).ljust(4, '0') for column in standard_normal_table.columns)

standard_normal_table