Table:
Season
Team
G
Rushing
Receiving
Kickoff Return
Passing

Att
Yds
Avg
Long
TD
Rec
Yds
Avg
Long
TD
KR
Yds
Long
TD
Comp
Att
Yards
TD

2015
Penn State

11
182
1,076
5.9
56
7
20
161
8.1
32
0
1
12
12
0
0
0
0
0

2016
Penn State

14
272
1,496
5.5
81T
18
28
402
14.4
44T
5
4
84
33
0
0
0
0
0

2017
Penn State

13
217
1,271
5.9
92T
18
54
632
11.7
85T
3
14
423
98T
2
2
2
36
1

Career
38
672
3,843
5.7
92T
43
102
1,195
11.7
85T
8
19
519
98T
2
2
2
36
1

Source[31]

Your is as follows:
Examine the table image and determine the locations of the mentioned cells. You need to express a cell's position with the JSON {'value': '<cell value>', 'location': (row number, column number)}, with row and column number both commencing from 1. Some cell values may not be contained in this table. If so, represent their locations as 'DOES NOT EXIST'.
Cells to locate:
1. '5'
2. '2016'
3. '3,843'
4. 'Winnipeg, Manitoba'
5. '33'
6. '1,496'
7. '7'
8. 'Toronto, Ontario'
9. '1,271'
10. '182'
11. 'receiving'

The target cell locations are as follows:
1. {'value': '5', 'location': (4, 13)}
2. {'value': '2016', 'location': (4, 1)}
3. {'value': '3,843', 'location': (6, 5)}
4. {'value': 'Winnipeg, Manitoba', 'location': 'DOES NOT EXIST'}
5. {'value': '33', 'location': (4, 16)}
6. {'value': '1,496', 'location': (4, 5)}
7. {'value': '7', 'location': (3, 8)}
8. {'value': 'Toronto, Ontario', 'location': 'DOES NOT EXIST'}
9. {'value': '1,271', 'location': (5, 5)}
10. {'value': '182', 'location': (3, 4)}
11. {'value': 'receiving', 'location': (1, 9)}