import pandas as pd
import numpy as np
#import scipy.stats as stats 
from scipy.stats import norm

r = 50

z_00 = np.empty(r)

for j in range(r):
  z_00[j] = norm.cdf(j/100, loc=0, scale=1)-0.5
  j=j+1

#print(z_00)

i_1 = np.arange(0,10)
i_2 = np.arange(10,20)
i_3 = np.arange(20,30)
i_4 = np.arange(30,40)
i_5 = np.arange(40,50)

z_0 = z_00[i_1] 
z_1 = z_00[i_2]
z_2 = z_00[i_3] 
z_3 = z_00[i_4]
z_4 = z_00[i_5] 

z_0_0 = pd.Series(z_0)
z_1_0 = pd.Series(z_1)
z_2_0 = pd.Series(z_2)
z_3_0 = pd.Series(z_3)
z_4_0 = pd.Series(z_4)

z = pd.DataFrame({'0.0':z_0_0, '0.1':z_1_0,'0.2':z_2_0,'0.3':z_3_0,'0.4':z_4_0})
z=z.T
z = z.rename(columns={z.columns[0]: '0.00'})
z = z.rename(columns={z.columns[1]: '0.01'})
z = z.rename(columns={z.columns[2]: '0.02'})
z = z.rename(columns={z.columns[3]: '0.03'})
z = z.rename(columns={z.columns[4]: '0.04'})
z = z.rename(columns={z.columns[5]: '0.05'})
z = z.rename(columns={z.columns[6]: '0.06'})
z = z.rename(columns={z.columns[7]: '0.07'})
z = z.rename(columns={z.columns[8]: '0.08'})
z = z.rename(columns={z.columns[9]: '0.09'})

#print(z)
round(z,4)
print("Standard Normal Distribution Table : ", f'\n{round(z,4)}\n')