Table:
male
female

total number
1,242,600
1,352,000

mean age
38.6
39.4

% distribution

age group

0 to 24
22.5
19.8

25 to 44
41.7
44.4

45 to 64
29.0
27.2

65 or older
6.8
8.6

immigration category

economic class

principal applicant
26.2
12.2

dependant
23.5
33.7

family class
28.9
37.4

refugee class
16.4
12.7

other
5.0
4.0

landing year

1980 to 1989
23.2
22.3

1990 to 1999
44.1
44.9

2000 to 2006
32.7
32.8

source world region

united states
2.1
2.6

caribbean/central and south america
10.1
11.0

western europe
8.1
7.3

eastern europe
12.6
12.6

sub-saharan africa
4.8
4.6

north africa/middle east/west asia
9.4
7.7

south asia
19.3
17.6

south east asia
11.9
14.1

east asia
20.7
21.8

oceania
0.7
0.7

Given a task involving a table image, your goal is to pinpoint the positions of specified cells. Format each cell's location as JSON in the format {'value': '<cell value>', 'location': (row_id, column_id)}, with both row and column id starting from 1. Denote the location as 'DOES NOT EXIST' if a cell does not exist in the table.
Refer to the cell values provided below:
(1) '65 or older'
(2) '2.1'
(3) '27.2'
(4) 'female'
(5) 'total number'
(6) 'economic class'
(7) '45 to 64'
(8) 'east asia'
(9) '6.8'

The coordinates of target cells are listed below.
(1) {'value': '65 or older', 'location': (9, 1)}
(2) {'value': '2.1', 'location': (22, 2)}
(3) {'value': '27.2', 'location': (8, 3)}
(4) {'value': 'female', 'location': (1, 3)}
(5) {'value': 'total number', 'location': (2, 1)}
(6) {'value': 'economic class', 'location': (11, 1)}
(7) {'value': '45 to 64', 'location': (8, 1)}
(8) {'value': 'east asia', 'location': (30, 1)}
(9) {'value': '6.8', 'location': (9, 2)}