Table:
year
n.l
p.e.i
n.s
n.b
que
ont
man
sask
alta
b.c
y.t
n.w.t
nvt
unknown
canada

number

1981
98
25
139
114
807
1,073
191
203
452
424
8
28
.
0
3,562

1986
s
13
104
81
604
969
157
157
393
355
12
28
.
0
2,938

1991
56
13
69
58
578
953
111
126
285
298
6
20
.
0
2,573

1996
38
8
59
40
396
802
104
112
236
237
0
19
.
0
2,051

2001
23
10
50
31
349
713
98
68
210
168
3
3
12
1
1,739

2002
21
2
36
27
346
681
98
67
283
183
3
7
8
0
1,762

2003
23
7
49
29
322
692
111
76
265
170
2
4
15
0
1,765

2004
23
6
40
30
342
735
97
74
236
175
4
0
12
1
1,775

2005
28
3
34
28
353
745
94
99
286
183
0
3
7
0
1,863

2006
24
3
34
28
415
674
88
75
238
171
3
7
10
1
1,771

2007
34
7
29
31
379
723
111
77
296
176
3
3
12
0
1,881

2008
25
3
32
24
379
753
101
85
317
166
2
7
13
4
1,911

2009
31
5
31
43
389
705
100
96
284
161
3
11
13
0
1,872

2010
26
5
41
25
440
695
106
84
299
166
2
1
12
0
1,902

2011
28
6
43
25
399
664
120
97
267
171
0
5
24
0
1,849

2012
25
5
40
40
441
684
92
80
223
166
1
3
18
0
1,818

2013
29
3
29
33
438
681
93
111
285
161
1
5
15
0
1,884

rate per 1,000

1981
10.8
13.2
11.5
10.9
8.5
8.8
11.9
11.8
10.6
10.2
14.9
21.5
.
..
9.6

1986
8.5
6.7
8.4
8.3
7.1
7.2
9.2
9.0
9.0
8.5
24.8
18.6
.
..
7.9

1991
7.8
6.9
5.7
6.1
5.9
6.3
6.4
8.2
6.7
6.5
10.6
12.2
.
..
6.4

1996
6.6
4.7
5.6
4.9
4.6
5.7
6.7
8.4
6.2
5.1
0.0
12.2
.
..
5.6

2001
4.9
7.3
5.6
4.3
4.7
5.4
7.0
5.5
5.6
4.1
8.7
4.9
16.9
..
5.2

2002
4.5
1.5
4.2
3.8
4.8
5.3
7.1
5.7
7.3
4.6
8.8
11.0
11.0
..
5.4

2003
5.0
4.9
5.7
4.1
4.4
5.3
8.0
6.3
6.6
4.2
6.0
5.7
19.8
..
5.3

2004
5.1
4.3
4.6
4.3
4.6
5.5
7.0
6.2
5.8
4.3
11.0
0.0
16.1
..
5.3

2005
6.2
2.2
4.0
4.1
4.6
5.6
6.6
8.3
6.8
4.5
0.0
4.2
10.0
..
5.4

2006
5.3
2.1
4.0
4.0
5.1
5.0
6.0
6.1
5.3
4.1
8.2
10.2
13.4
..
5.0

2007
7.5
5.0
3.3
4.3
4.5
5.2
7.3
5.8
6.0
4.0
8.5
4.1
15.1
..
5.1

2008
5.1
2.0
3.5
3.2
4.3
5.4
6.5
6.2
6.2
3.8
5.4
9.7
16.2
..
5.1

2009
6.3
3.4
3.4
5.8
4.4
5.0
6.3
6.7
5.5
3.6
7.8
15.5
14.8
..
4.9

2010
5.3
3.6
4.6
3.4
5.0
5.0
6.7
5.9
5.9
3.8
5.2
1.4
14.5
..
5.0

2011
6.3
4.2
4.9
3.5
4.5
4.7
7.7
6.8
5.2
3.9
0.0
7.2
28.7
..
4.9

2012
5.7
3.8
4.6
5.7
5.0
4.8
5.6
5.4
4.2
3.8
2.3
4.4
21.4
..
4.8

2013
6.4
2.1
3.4
4.7
4.9
4.9
5.6
7.5
5.3
3.7
2.5
7.5
16.4
..
5.0

Based on the table image, extract the cell contents located in the 5th column. Output the cell values in a column as JSON in the format {"column_id":"<column index>", "cell_list":"<a list of cells in this column>"}, e.g., {"column_id":"3", "cell_list": ["123.89", "News gathering", "selected tools"]}.

The cells in the 5th column: {"column_id": "5", "cell_list": ['n.b', '', '114', '81', '58', '40', '31', '27', '29', '30', '28', '28', '31', '24', '43', '25', '25', '40', '33', '', '10.9', '8.3', '6.1', '4.9', '4.3', '3.8', '4.1', '4.3', '4.1', '4.0', '4.3', '3.2', '5.8', '3.4', '3.5', '5.7', '4.7']}