Table:
Club

Season

Division

League

FA Cup

Other

Total

Apps
Goals
Apps
Goals
Apps
Goals
Apps
Goals

Swansea City (loan)

1995–96

Second Division

6
0
0
0
0
0
6
0

Oldham Athletic

1993–94

Premier League

1
0
0
0
0
0
1
0

1994–95

First Division

2
0
0
0
0
0
2
0

1995–96

First Division

28
2
0
0
5
0
33
2

1996–97

First Division

33
0
1
0
4
0
38
0

Total

64
2
1
0
10
0
75
2

Preston North End (loan)

1999–2000

Second Division

4
0
1
0
1
0
6
0

Port Vale (loan)

2000–01

Second Division

4
0
0
0
0
0
4
0

Huddersfield Town

1996–97

First Division

6
1
0
0
0
0
6
1

1997–98

First Division

8
0
0
0
1
0
9
0

1998–99

First Division

19
2
2
0
2
0
33
2

1999–2000

First Division

0
0
0
0
1
0
1
0

2000–01

First Division

2
0
0
0
1
0
3
0

Total

35
3
2
0
5
0
42
3

Hull City

2001–02

Third Division

41
1
1
0
5
0
47
1

Macclesfield Town (loan)

2003–04

Third Division

5
0
0
0
1
0
6
0

Plymouth Argyle

2002–03

Second Division

16
0
0
0
2
0
18
0

2003–04

Second Division

1
0
0
0
0
0
1
0

Total

17
0
0
0
2
0
19
0

Tranmere Rovers

2003–04

Second Division

25
1
6
0
0
0
31
1

2004–05

League One

19
2
0
0
5
1
24
3

Total

44
3
6
0
5
1
55
4

Macclesfield Town

2005–06

League Two

16
0
2
0
4
1
22
1

Career Total

236
9
13
0
32
2
281
11

To complete your task, analyze the table image and identify the positions of the specified cells. Ensure that you represent a cell's location using the JSON format {'value': '<cell value>', 'location': (row number, column number)}, with both row and column number starting from 1. Denote the location as 'DOES NOT EXIST' if a cell does not exist in the table.
Target cells:
1. '31'
2. '64'
3. 'swansea city'
4. '32'
5. '1997-98'
6. 'oldham athletic'

The coordinates of target cells are listed below.
1. {'value': '31', 'location': (22, 10)}
2. {'value': '64', 'location': (8, 4)}
3. {'value': 'swansea city', 'location': (3, 1)}
4. {'value': '32', 'location': (26, 8)}
5. {'value': '1997-98', 'location': (12, 2)}
6. {'value': 'oldham athletic', 'location': (4, 1)}