Help in pandas-gurobipy

any help please 

Hello, the problem in my model is how to convert the database  S1 and S2 of week zero into   S1[1,0].ub and S1[2,0].lb , the same for S2 , I sent the excel files by email 

S1 and S2 are variables for weeks 1 , 2,3 , and 4 but for week 0 is a data 

import gurobipy as gp
import pandas as pd
import numpy as np
from gurobipy import GRB
#Read Purchase Order from Excel
df=pd.read_excel("purchase order.xlsx")
products=df.Article.values.tolist()
print(products)
m=df.drop(columns='Article',axis=1)
#print(m)
a=m.values.tolist()
print (a)
#a=[[0,0,10,0,0],[0,20,0,0,0],]

#Read Consommation from Excel
df=pd.read_excel("Consommation.xlsx")
b=df.drop(columns='Article',axis=1)
l=b.values.tolist()
print(l)
#l=[[0,2,3,1,2],[0,9,5,1,2],]



m=gp.Model("Log")

weeks = [0,1,2,3,4]

#products=[1,2]
L=10
k=2

S=m.addVars(products,weeks,name='S')
S1=m.addVars(products,weeks,name='S1')
S2=m.addVars(products,weeks,obj=k,name='S2')

#Read initial Local stock from Excel
df=pd.read_excel("S1.xlsx")
b=df.drop(columns='Article',axis=1)
S3=b.values.tolist()
#print(S3)
for i in range(len(products)):
     S1[i,0].ub=S3[i]
     S1[i, 0].ub +=1
     S1[i,0].lb=S3[i]
     S1[i,0].lb+=1
#print(S1)

#Read initial Logis stock from Excel
df=pd.read_excel("S2.xlsx")
b=df.drop(columns='Article',axis=1)
S4=b.values.tolist()
#print(S4)
for i in range(len(products)):
     S2[i,0].ub=S4[i]
     S2[i, 0].ub +=1
     S2[i,0].lb=S4[i]
     S2[i,0].lb+=1
print(S2)
#S1[1,0].lb=1
#S1[1,0].ub=1
#S1[2,0].lb=2
#S1[2,0].ub=2

#S2[1,0].lb=3
#S2[1,0].ub=3
#S2[2,0].lb=4
#S2[2,0].ub=4



l1=m.addVars(products,weeks,name='l1')
l2=m.addVars(products,weeks,obj=k,name='l2')
l3=m.addVars(products,weeks,obj=k,name='l3')

a1=m.addVars(products,weeks,name='a1')
a2=m.addVars(products,weeks,obj=k,name='a2')


m.addConstrs(S[p,t-1]+a[p-1][t] == l[p-1][t]+S[p,t] for p in products  for t in weeks if t>0)
#m.addConstrs(S1[p,t-1]+a1[p,t] == l1[p,t]+S1[p,t]-l3[p,t] for p in products  for t in weeks if t>1)
m.addConstrs(S1[p][t-1]+a1[p,t] == l1[p,t]+S1[p][t]-l3[p,t] for p in products  for t in weeks if t>1)
m.addConstrs(S2[p,t-1]+a2[p,t] == l2[p,t]+S2[p,t]+l3[p,t] for p in products  for t in weeks if t>0)
m.addConstrs((S[p,t] == S1[p,t]+S2[p,t] for p in products for t in weeks ))
m.addConstrs((a[p-1][t] == a1[p,t]+a2[p,t] for p in products for t in weeks ))
m.addConstrs((l[p-1][t] == l1[p,t]+l2[p,t] for p in products for t in weeks ))
m.addConstrs(gp.quicksum(S1[p,t] for p in products) <= L for t in weeks)
m.addConstrs(gp.quicksum(S[p,t] for p in products) <= L + gp.quicksum(S2[p,t] for p in products) for t in weeks)

m.optimize()
m.write("myLP.lp")
print(m)

Purchase order

consommation 

S1 

S2