How to convert Matlab code to python? Request for make correction.

[rasheed2063]

I want to add 2 columns in the original exel datasheet which has 19 columns and 132 rows

First, I need to add one additional column by the name of i_demand in which the values are saved as per the condition below.` if censored column==0

if the censored column (column-18) is equal to 0, then add rows for which all values remain the same except the i_demand value is put equal to 0.01 upto the point up to 0.15 with increment of 0.01

Similarly, the second additional column (FailSur), should be filled such that if i_demand<= drift, than put 1 else 0. if censored column==1

if the censored column (column-18) is equal to 0, then add rows for which all values remain the same except the i_demand value is put equal to 0.01 upto the point where the i_demand is less than drift (column_19)

Similarly, the second additional column (FailSur), should be filled such that if i_demand<= drift, than put 1 else 0. I am unable to append the rows, i have develped the matlab code and it works fine, i want to get the results as per the matlab code attached

`_

___________Python_CODE_____________________
  import pandas as pd
  import numpy as np 
   # Adding new column Failur and store the value 1 or 0 based on the condition if i_demand<= drift col
 df["FailSur"]= df['Dc', 'H', 'Ag', 'Igr', 'Ieff', 'fy', 'db', "fiu_mono", 'fiy', "f'c",  'P', "gross_dia, Dg", 'Disp', 'Vu', "ft", 'rhow', 'rhho_long',
   'censored', 'drift']

new_rows_list = []
for  i_demand in np.arange(0.01, 0.16, 0.01):
   for _, current_row in df.iterrows():
       if current_row['censored'] == 0:               # For censored=0, the failure column should have values for i_demand<= drift
           if i_demand <= current_row["drift"]:
               print( "FailSur",1)
           else:
               print("FailSur",0)
            
               new_row=pd.DataFrame(Templine_Pre, i_demand, )
               append_row= df.append(new_rows_list, new_row)
       
    
        else:                                          # For censored=1, the failure column should have values for from 0.01 till 0.15
            if i_demand <= current_row["drift"]:
                print(1)
               new_row=pd.DataFrame(Templine_Pre, i_demand, )
               append_row= df.append(new_rows_list, new_row)
            
           else:
                 print(0)`

<img width="417


" alt="Matlab_code" src="https://user-images.githubusercontent.com/83563415/204904975-91612f79-f2de-4acb-8dbe-4bc4e253d284.PNG">

[rasheed2063]

`

The matlab code of above question
incr=0.01; 
for i_demand=0.01:+incr:0.15
for i = 1:size(A_Mat,1)
    Templine_Pre = A_Mat(i,:);% 19 column
    if A_Mat(i,18) == 0  % failure data
        if i_demand<= A_Mat(i,19)
           FailSur= 1;
        else
           FailSur= 0;   
        end
        Templine = [Templine_Pre, i_demand, FailSur] ;% 0 failure and 1 survive 
        Append_Mat = [Append_Mat; Templine]; % append temporary line with colun 21
    elseif A_Mat(i,18) == 1
        if i_demand<= A_Mat(i,19)
           FailSur= 1;
           Templine = [Templine_Pre, i_demand, FailSur]; % 0 failure and 1 survive 
           Append_Mat = [Append_Mat; Templine]; % append temporary line with colun 21
        else
           FailSur= 0;   % Do nothing
        end
    else 
        
    end

    end
end 

XY_ALL= Append_Mat;
save XY_ALL;`