Table:
Club	Season	League	Cup	Continental	Other	Total

Division	Apps	Goals	Apps	Goals	Apps	Goals	Apps	Goals	Apps	Goals

Regatas	2013–14	Torneo Argentino B	4	0	0	0	—	0	0	4	0

Unión Aconquija	2015	Torneo Federal A	2	0	0	0	—	0	0	2	0

Villa Mitre	2015	Torneo Federal B	24	4	0	0	—	0	0	24	4

2016	Torneo Federal A	11	0	2	0	—	0	0	13	0

Total	35	4	2	0	—	0	0	37	4

Estudiantes	2016–17	Primera B Metropolitana	1	0	0	0	—	0	0	1	0

Tigre	2017–18	Primera División	0	0	0	0	—	0	0	0	0

Acassuso (loan)	2017–18	Primera B Metropolitana	2	0	0	0	—	0	0	2	0

San Carlos	2018–19	Liga FPD	9	0	—	0	0	9	0

Egersunds IK	2019	2. divisjon	1	0	0	0	—	0	0	1	0

Career total	54	4	2	0	—	0	0	56	4

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_id, column_id)}, with both row and column id starting from 1. Represent the location as 'DOES NOT EXIST' if a cell is not present in the table.
Target cells:
(1) '2016-17';
(2) 'league';
(3) '56';
(4) 'liga fpd';
(5) '2018-19';
(6) 'acassuso';
(7) 'career total';
(8) 'tigre';
(9) '35';

The coordinates of target cells are listed below.
(1) {'value': '2016-17', 'location': (8, 2)}
(2) {'value': 'league', 'location': (1, 3)}
(3) {'value': '56', 'location': (13, 12)}
(4) {'value': 'liga fpd', 'location': (11, 3)}
(5) {'value': '2018-19', 'location': (11, 2)}
(6) {'value': 'acassuso', 'location': (10, 1)}
(7) {'value': 'career total', 'location': (13, 1)}
(8) {'value': 'tigre', 'location': (9, 1)}
(9) {'value': '35', 'location': (7, 4)}