Table:
Month	Jan	Feb	Mar	Apr	May	Jun	Jul	Aug	Sep	Oct	Nov	Dec	Year

Average high °F (°C)	37.1

(2.8)	39.7

(4.3)	47.2

(8.4)	57.6

(14.2)	67.6

(19.8)	77.0

(25)	82.1

(27.8)	80.8

(27.1)	74.0

(23.3)	63.2

(17.3)	53.1

(11.7)	42.3

(5.7)	60.1

(15.6)

Average low °F (°C)	23.1

(−4.9)	25.2

(−3.8)	31.4

(−0.3)	41.0

(5)	50.5

(10.3)	60.2

(15.7)	66.3

(19.1)	65.6

(18.7)	58.0

(14.4)	46.4

(8)	37.9

(3.3)	28.4

(−2)	44.5

(6.9)

Precipitation inches (mm)	3.10

(78.7)	2.79

(70.9)	4.04

(102.6)	4.13

(104.9)	3.80

(96.5)	3.64

(92.5)	3.46

(87.9)	3.96

(100.6)	3.48

(88.4)	3.64

(92.5)	3.39

(86.1)	3.33

(84.6)	42.75

(1,085.9)

Snowfall inches (cm)	6.8

(17.3)	5.7

(14.5)	3.2

(8.1)	.8

(2)	0

(0)	0

(0)	0

(0)	0

(0)	0

(0)	0

(0)	.2

(0.5)	4.8

(12.2)	21.4

(54.4)

Avg. precipitation days (≥ 0.01 inch)	10.9	9.7	11.3	11.0	11.8	11.1	8.9	8.9	8.2	8.8	10.0	11.1	121.7

Avg. snowy days (≥ 0.1 inch)	5.0	3.6	2.4	.3	0	0	0	0	0	0	.5	3.1	15.0

Based on the table image, your task is to extract the cells' values in row 7. Output the cell values in a row as JSON in the format {"row_id":"<row index>", "cell_list":"<a list of cells in this row>"}, e.g., {"row_id":"3", "cell_list": ["123.89", "News gathering", "selected tools"]}.

The target cell values of row 7: {"row_id": "7", "cell_list": ['Avg. snowy days (≥ 0.1 inch)', '5.0', '3.6', '2.4', '.3', '0', '0', '0', '0', '0', '0', '.5', '3.1', '15.0']}