Table:
Year

Team

Games

Passing

Rushing

Att

Comp

Pct

Yards

TD

Int

Rating

Att

Yards

Avg

Long

TD

2000
NE

8
9
3
33.3
80
1
1
64.4
7
-1
-0.1
2
0

2001
FRA

10
153
76
49.7
1,090
11
7
78.1
35
244
7.0
22
1

2002
TOR

14
148
63
42.6
1,053
7
10
54.8
45
225
5.0
24
2

2003
TOR

18
20
8
40.0
215
1
2
55.2
3
33
11.0
14
0

2004
TOR

18
217
104
47.9
1,508
6
15
51.4
60
408
6.8
38
5

2005
TOR

18
61
31
50.8
416
3
4
61.9
13
102
7.8
21
0

2006
TOR

11
12
5
41.7
75
2
1
83.7
21
31
1.5
3
1

2007
TOR

13
355
185
52.1
2,920
22
11
87.5
38
260
6.8
20
0

2008
SSK

10
232
141
60.8
2,224
7
12
81.2
41
202
4.9
20
4

2008
TOR

8
42
19
45.2
326
3
1
86.0
5
42
8.4
--
0

2009
WPG

14
405
204
50.4
3,035
15
20
67.1
19
84
4.4
--
0

NFL totals

8
9
3
33.3
80
1
1
64.4
7
-1
-0.1
2
0

NFLE totals

10
153
76
49.7
1,090
11
7
78.1
35
244
7.0
22
1

CFL totals

125
1,492
760
50.9
11,772
66
77
70.7
275
1,387
5.0
38
12

Examine the given table and locate the cells that contain the following values:
1. '2001'
2. '50.4'
3. '326'
Return the cell locations using the JSON format {'value': '<cell value>', 'location': (row index, column index)}, where both row and column indices commence from 1. Use 'DOES NOT EXIST' as the location for a non-existing cell in the table.

The coordinates of target cells are listed below.
1. {'value': '2001', 'location': (4, 1)}
2. {'value': '50.4', 'location': (13, 6)}
3. {'value': '326', 'location': (12, 7)}