Table:
Pos

No

Nat

Driver

Constructor

Laps

Time/Retired

Grid

Points

1

9

Kimi Räikkönen

McLaren-Mercedes

66

1:27:16.830

1

10

2

5

Fernando Alonso

Renault

66

+27.652

3

8

3

16

Jarno Trulli

Toyota

66

+45.947

5

6

4

17

Ralf Schumacher

Toyota

66

+46.719

4

5

5

6

Giancarlo Fisichella

Renault

66

+57.936

6

4

6

7

Mark Webber

Williams-BMW

66

+1:08.542

2

3

7

10

Juan Pablo Montoya

McLaren-Mercedes

65

+1 lap

7

2

8

14

David Coulthard

Red Bull-Cosworth

65

+1 lap

9

1

9

2

Rubens Barrichello

Ferrari

65

+1 lap

16

10

8

Nick Heidfeld

Williams-BMW

65

+1 lap

17

11

12

Felipe Massa

Sauber-Petronas

63

Wheel rim

10

12

18

Tiago Monteiro

Jordan-Toyota

63

+3 laps

18

13

19

Narain Karthikeyan

Jordan-Toyota

63

+3 laps

13

Ret

11

Jacques Villeneuve

Sauber-Petronas

51

Engine

12

Ret

1

Michael Schumacher

Ferrari

46

Puncture

8

Ret

21

Christijan Albers

Minardi-Cosworth

19

Gearbox

14

Ret

20

Patrick Friesacher

Minardi-Cosworth

11

Spun off

15

Ret

15

Vitantonio Liuzzi

Red Bull-Cosworth

9

Spun off

11

Examine the given table and extract the contents of in the specific rows or columns, denoted by row or column indices. Provide the cells in each row or column in the JSON structure, using the format {"row_id/column_id":"<row or column index>", "cell_list":"<a list of cells in this row/column>"}.
Specified rows or columns:
row 1,
column 6,

The cell values of target rows or columns are as follows:
For row 1: {"row_id": "1", "cell_list": ['Pos', 'No', 'Driver', 'Constructor', 'Laps', 'Time/Retired', 'Grid', 'Points']}
For column 6: {"column_id": "6", "cell_list": ['Time/Retired', '1:27:16.830', '+27.652', '+45.947', '+46.719', '+57.936', '+1:08.542', '+1 lap', '+1 lap', '+1 lap', '+1 lap', 'Wheel rim', '+3 laps', '+3 laps', 'Engine', 'Puncture', 'Gearbox', 'Spun off', 'Spun off']}