Double 'for' loop and writing in a new columns dataframe

[marco_ita]

Hi there,
the below code work as long as i remove the lines number 8 and 26.
But i need to create another loop using j as I need the multiplier in row 26 to change dynamically between 0 and 5.
Now once it is achieved, i will need to print a new 5 new columns for j=0, j=1, j=2, etc till j=5.
Under each column i want to display the 'Profit/Loss' but according to that specific value of j at each interaction.
I am getting crazy and can't find the way.
Appreciate your help,
Thanks a lot.
Marco.

# assign to variable n the total number of rows
n = df_dj30.shape[0]-1
new_df = pd.DataFrame()


#loop cycle and add new values to the new dataframe new_df

for j in range(0, 5):
    
for i in range(0, n):
    new_df.loc[i, 'Date[i]'] = (df_dj30['Date'][i])
    new_df.loc[i, 'Delta[i]'] = (df_dj30['Delta'][i])
    if (df_dj30['Delta'][i])>0:
        new_df.loc[i, 'Action[i+1]'] = 'buy',
    else:
        new_df.loc[i, 'Action[i+1]'] = 'sell'
    new_df.loc[i, 'Open[i+1]'] = (df_dj30['Open'][i+1])
    new_df.loc[i, 'Close[i+1]'] = (df_dj30['Close'][i+1])
    new_df.loc[i, 'High[i]'] = (df_dj30['High'][i])
    new_df.loc[i, 'Low[i]'] = (df_dj30['Low'][i])
    new_df.loc[i, 'High[i+1]'] = (df_dj30['High'][i+1])
    new_df.loc[i, 'Low[i+1]'] = (df_dj30['Low'][i+1])
    
    if new_df.loc[i, 'Action[i+1]'] == 'sell':
#        new_df.loc[i, 'SL[i+1]'] = (max(new_df.loc[i, 'High[i]'], new_df.loc[i, 'Open[i+1]']))-0 ,
            new_df.loc[i, 'SL[i+1]'] = (new_df.loc[i, 'Open[i+1]'])*(1+j/1000) ,
            new_df.loc[i, 'TP[i+1]'] = new_df.loc[i, 'Close[i+1]'] ,
            if new_df.loc[i, 'High[i+1]'] >= new_df.loc[i, 'SL[i+1]']:
                new_df.loc[i, 'Profit/Loss'] = new_df.loc[i, 'Open[i+1]'] - new_df.loc[i, 'SL[i+1]'],
                new_df.loc[i, 'Profit/Loss-2'] = new_df.loc[i, 'Close[i+1]'] - new_df.loc[i, 'SL[i+1]'],


            else:
                new_df.loc[i, 'Profit/Loss'] = new_df.loc[i, 'Open[i+1]'] - new_df.loc[i, 'Close[i+1]'],    
    else:
#        new_df.loc[i, 'SL[i+1]'] = (min(new_df.loc[i, 'Low[i]'], new_df.loc[i, 'Open[i+1]']))+0,
        new_df.loc[i, 'SL[i+1]'] = (new_df.loc[i, 'Open[i+1]'])*0.99,
        new_df.loc[i, 'TP[i+1]'] = new_df.loc[i, 'Close[i+1]'],
        if new_df.loc[i, 'Low[i+1]'] <= new_df.loc[i, 'SL[i+1]']:
            new_df.loc[i, 'Profit/Loss'] = new_df.loc[i, 'SL[i+1]'] - new_df.loc[i, 'Open[i+1]'],
            new_df.loc[i, 'Profit/Loss-2'] = new_df.loc[i, 'SL[i+1]'] - new_df.loc[i, 'Close[i+1]'],
        else:
            new_df.loc[i, 'Profit/Loss'] = new_df.loc[i, 'Close[i+1]'] - new_df.loc[i, 'Open[i+1]']
    
    new_df.loc[i, 'Delta[i+1]'] = (df_dj30['Delta'][i+1])    

#temporary as it might changes according to the SL triggering
    if (df_dj30['Delta'][i])>0 and new_df.loc[i, 'Delta[i+1]']>0:
        new_df.loc[i, 'Outcome[i+1]'] = 'profit',
    elif (df_dj30['Delta'][i])<0 and new_df.loc[i, 'Delta[i+1]']<0:
        new_df.loc[i, 'Outcome[i+1]'] = 'profit',
    else:
        new_df.loc[i, 'Outcome[i+1]'] = 'loss'

Output:
 	Date[i] 	Delta[i] 	Action[i+1] 	Open[i+1] 	Close[i+1] 	High[i] 	Low[i] 	High[i+1] 	Low[i+1] 	SL[i+1] 	TP[i+1] 	Profit/Loss 	Delta[i+1] 	Outcome[i+1] 	Profit/Loss-2
0 	2002-04-08 	-11.0 	sell 	10290.0 	10222.0 	10280.0 	10105.0 	10312.0 	10204.0 	10392.90 	10222.0 	68.00 	-68.0 	profit 	NaN
1 	2002-04-09 	-68.0 	sell 	10229.0 	10387.0 	10312.0 	10204.0 	10399.0 	10215.0 	10331.29 	10387.0 	-102.29 	158.0 	loss 	55.71
2 	2002-04-10 	158.0 	buy 	10378.0 	10170.0 	10399.0 	10215.0 	10378.0 	10158.0 	10274.22 	10170.0 	-103.78 	-208.0 	loss 	104.22
3 	2002-04-11 	-208.0 	sell 	10210.0 	10194.0 	10378.0 	10158.0 	10240.0 	10140.0 	10312.10 	10194.0 	16.00 	-16.0 	profit 	NaN
4 	2002-04-12 	-16.0 	sell 	10196.0 	10093.0 	10240.0 	10140.0 	10230.0 	10068.0 	10297.96 	10093.0 	103.00 	-103.0 	profit 	NaN