Table:
type of offence
2018r
2019
change in rate 2018 to 2019
change in rate 2009 to 2019

number
rate
number
rate
percent

total criminal code (excluding traffic) - "crime rate"
2,043,328
5,514
2,208,076
5,874
7
-9

total violent crime
426,839
1,152
480,004
1,277
11
-3

homicide
658
1.78
678
1.80
2
-1

other violations causing death
133
0
108
0
-20
-4

attempted murder
821
2.22
865
2.30
4
-3

sexual assault - level 3 - aggravated
158
0
125
0
-22
-6

sexual assault - level 2 - weapon or bodily harm
490
1
525
1
6
33

sexual assault - level 1
27,909
75
30,285
81
7
32

sexual offence occurring prior to january 4, 1983
574
2
534
1
-8
..

sexual violations against children
9,075
24
10,038
27
9
..

assault - level 3 - aggravated
3,584
10
3,924
10
8
-3

assault - level 2 - weapon or bodily harm
54,218
146
59,416
158
8
0

assault - level 1
170,138
459
187,826
500
9
-7

assault against a peace officer
11,751
32
12,132
32
2
-8

other assaults
2,124
6
2,226
6
3
-42

firearms - use of, discharge, pointing
2,861
8
3,503
9
21
81

robbery
22,550
61
23,296
62
2
-36

forcible confinement or kidnapping
3,490
9
3,695
10
4
-31

trafficking in persons
238
1
341
1
41
..

extortion
4,724
13
4,174
11
-13
117

criminal harassment
19,691
53
23,325
62
17
5

uttering threats
66,806
180
81,361
216
20
-7

indecent or harassing communications
17,772
48
23,289
62
29
-10

non-consensual distribution of intimate images
1,483
4
1,972
5
31
..

offences in relation to sexual services
1,044
3
1,163
3
10
..

other violent criminal code violations
4,547
12
5,203
14
13
13

total property crime
1,241,083
3,349
1,319,562
3,510
5
-15

breaking and entering
160,329
433
161,291
429
-1
-30

possess stolen property
24,358
66
25,752
69
4
..

theft of motor vehicle
86,192
233
87,066
232
0
-28

theft over $5,000
20,104
54
21,357
57
5
21

shoplifting under $5,000
124,896
337
140,286
373
11
35

theft of $5,000 or under
407,567
1,100
424,439
1,129
3
-19

fraud
130,008
351
142,140
378
8
64

identity theft
3,815
10
4,683
12
21
..

identity fraud
15,848
43
19,664
52
22
..

mischief
259,917
701
284,694
757
8
-30

arson
8,049
22
8,190
22
0
-45

total other criminal code offences
375,406
1,013
408,510
1,087
7
7

weapons violations
16,589
45
18,622
50
11
11

child pornography
5,934
16
8,815
23
46
449

prostitution
115
0
135
0
16
..

terrorism
108
0
85
0
-22
..

disturb the peace
94,379
255
110,444
294
15
-16

administration of justice violations
229,250
619
237,346
631
2
24

other violations
29,031
78
33,063
88
12
-9

total criminal code traffic violations
125,890
340
136,706
364
7
-16

alcohol-impaired driving
66,008
178
72,818
194
9
-25

drug-impaired driving
4,444
12
6,453
17
43
297

alcohol- and drug-impaired driving
267
1
4,618
12
..
..

impaired driving
113
0
1,784
5
..
..

other criminal code traffic violations
55,058
149
51,033
136
-9
-21

total drug offences
84,927
229
70,140
187
-19
-36

total other federal statute violations
26,183
71
23,596
63
-11
-33

human trafficking under the immigration and refugee protection act
117
0
170
0
43
..

youth criminal justice act
4,765
13
3,815
10
-21
-73

other federal statutes
21,301
57
19,611
52
-9
-9

total - all violations
2,280,328
6,153
2,438,518
6,487
5
-11

The task is as follows:
Analyze the table in this image to find every merged cell. Return the regions of these merged cells in the JSON {'top-left':(X1, Y1), 'bottom-right':(X2, Y2)}, where '(X1, Y1)' and '(X2, Y2)' show the (row_id, column_id) of the top-left and bottom-right cells in these regions, respectively. The row and column IDs start from 1.

The merged cell areas are as follows:
{'top-left':(1, 1), 'bottom-right':(2, 1)}
{'top-left':(1, 2), 'bottom-right':(1, 3)}
{'top-left':(1, 4), 'bottom-right':(1, 5)}
{'top-left':(2, 6), 'bottom-right':(2, 7)}.