Table:
Club	Season	League	Cup	League Cup	Continental	Other	Total

Division	Apps	Goals	Apps	Goals	Apps	Goals	Apps	Goals	Apps	Goals	Apps	Goals

Rennes	1992–93	Division 2	2	0	–	2	0

1993–94	26	8	–	26	8

1994–95	Division 1	26	5	–	26	5

1995–96	37	15	1	0	2	3	–	40	18

1996–97 (loan)	35	3	2	0	3	0	–	40	3

Total	126	31	3	0	5	3	0	0	134	34

Bordeaux	1997–98	Division 1	34	11	2	4	5	1	2	0	–	43	16

1998–99	33	22	0	0	1	0	8	5	–	42	27

1999–00	32	13	4	0	2	0	12	4	–	50	17

Total	99	46	6	4	8	1	22	9	0	0	135	60

Arsenal	2000–01	Premier League	27	8	6	6	1	0	13	1	–	47	15

2001–02	33	10	7	2	3	4	11	1	–	54	17

2002–03	34	10	7	2	0	0	12	1	1	0	54	13

2003–04	12	3	0	0	3	1	4	0	1	0	20	4

Total	106	31	20	10	7	5	40	3	2	0	175	49

Lyon	2004–05	Ligue 1	25	3	2	2	0	0	8	6	–	35	11

2005–06	35	12	3	0	0	0	10	2	–	48	14

2006–07	22	5	1	0	2	2	6	0	–	31	7

Total	82	20	6	2	2	2	24	8	0	0	114	32

Rennes	2007–08	Ligue 1	25	6	2	1	1	0	4	0	–	32	7

2008–09	6	0	0	0	1	1	2	0	–	9	1

Total	31	6	2	1	2	1	6	0	0	0	41	8

Marseille	2008–09	Ligue 1	13	1	1	0	0	0	0	0	–	14	1

Metz	2009–10	Ligue 2	15	3	0	0	0	0	0	0	–	15	3

Nantes	2011–12	Ligue 2	33	8	0	0	1	0	0	0	–	34	8

Total	505	146	38	17	25	12	92	20	2	0	662	195

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. '1933-34';
2. '2005-06';
3. '1932-33';
4. '24';
5. '322';
6. 'torquay united';

The coordinates of target cells are listed below.
1. {'value': '1933-34', 'location': 'DOES NOT EXIST'}
2. {'value': '2005-06', 'location': (19, 2)}
3. {'value': '1932-33', 'location': 'DOES NOT EXIST'}
4. {'value': '24', 'location': (21, 10)}
5. {'value': '322', 'location': 'DOES NOT EXIST'}
6. {'value': 'torquay united', 'location': 'DOES NOT EXIST'}