Table:
municipalities
as a percent of visible minority females in each cma
as a percent of total female population in each cma/municipality
largest visible minority group in each cma/municipality
largest visible minority group as a percent of total female population in each cma/municipality

toronto cma
100.0
47.6
south asian
14.7

toronto
49.3
49.8
south asian
11.8

mississauga
14.5
54.1
south asian
21.4

brampton
13.0
66.5
south asian
37.7

markham
8.2
72.5
chinese
38.5

richmond hill
3.7
53.4
chinese
23.6

vancouver cma
100.0
46.1
chinese
18.6

vancouver
30.2
53.7
chinese
28.6

surrey
22.9
52.7
south asian
30.3

richmond
13.1
71.3
chinese
47.7

burnaby
12.7
60.9
chinese
31.6

coquitlam
5.3
44.6
chinese
17.5

montreal cma
100.0
20.2
black
5.9

montreal
66.8
31.3
black
9.4

laval
10.6
20.5
black
6.2

longueuil
4.2
14.0
black
4.8

brossard
4.0
38.0
chinese
12.3

dollard-des ormeaux
2.4
36.4
south asian
9.9

calgary cma
100.0
28.4
south asian
6.9

calgary
96.5
30.3
south asian
7.3

chestermere
1.3
29.3
south asian
9.5

airdrie
1.1
8.6
filipino
2.1

rocky view county
1.0
9.3
south asian
3.7

cochrane
0.2
3.4
filipino
1.3

For the specified cells listed below, determine their locations in the given table. Express the cell locations as JSON {'value': '<cell value>', 'location': (row number, column number)}, starting from 1 for both row and column number. Some cell values may not be contained in this table. If so, represent their locations as 'DOES NOT EXIST'.
(1) 'Apps',
(2) '53.4',
(3) '2.4',
(4) 'longueuil',
(5) '44.6',
(6) 'Continental',
(7) '6.2',
(8) '38.0',

The target cell locations are as follows:
(1) {'value': 'Apps', 'location': 'DOES NOT EXIST'}
(2) {'value': '53.4', 'location': (7, 3)}
(3) {'value': '2.4', 'location': (19, 2)}
(4) {'value': 'longueuil', 'location': (17, 1)}
(5) {'value': '44.6', 'location': (13, 3)}
(6) {'value': 'Continental', 'location': 'DOES NOT EXIST'}
(7) {'value': '6.2', 'location': (16, 5)}
(8) {'value': '38.0', 'location': (18, 3)}