Python sort_values (inplace=True) but not really?

So I am trying to write a loop in python as I have to compare rows to each other in a table. I have to sort the data, which I do by 'sort_values', the dataframe seems to sort, yet when I step through it with a 'for loop' it is still unsorted? So I'm clearly not understanding how pandas memory allocation works. I have tried sorting to another dataframe and I get the same problem

import pandas as pd

data = {'state': ['Ohio', 'Ohio', 'Ohio', 'Nevada', 'Nevada', 'Nevada'],
        'date1': ['2000-04-18', '2000-04-16', '2000-04-15', '2000-04-25', '2000-04-16', '2000-04-17'],
        'stat1': [1.5, 1.7, 3.6, 2.4, 2.9, 3.2]}

frame = pd.DataFrame(data) 
 
frame

output original unsorted:
 state  date1   stat1
0   Ohio    2000-04-18  1.5
1   Ohio    2000-04-16  1.7
2   Ohio    2000-04-15  3.6
3   Nevada  2000-04-25  2.4
4   Nevada  2000-04-16  2.9
5   Nevada  2000-04-17  3.2 

frame.sort_values(by=['state','date1'], inplace=True)

frame

sorted output:
    state   date1   stat1
4   Nevada  2000-04-16  2.9
5   Nevada  2000-04-17  3.2
3   Nevada  2000-04-25  2.4
2   Ohio    2000-04-15  3.6
1   Ohio    2000-04-16  1.7
0   Ohio    2000-04-18  1.5

for i1 in range(0, len(frame)):
    state1=frame['state'][i1]
    print(frame['state'][i1],' ', frame['date1'][i1])

output unsorted:
Ohio   2000-04-18
Ohio   2000-04-16
Ohio   2000-04-15
Nevada   2000-04-25
Nevada   2000-04-16
Nevada   2000-04-17

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