Table:
Nation
Men
Women
Total

Men's
individual
Men's
team
Women's
individual
Women's
team
Athletes

Australia
1

1

2

Bangladesh
1

1

Belarus

1

1

Bhutan

1

1

Brazil
1

1

Bulgaria
1

1

Canada
1

1

2

Chile

1

1

China
3
X
3
X
6

Colombia
1

1

2

Ivory Coast
1

1

Cuba
1

1

Denmark

3
X
3

Egypt
1

1

2

Estonia

1

1

Fiji
1

1

France
3
X
1

4

Georgia

1

1

Germany
1

1

2

Great Britain
3
X
3
X
6

Greece

1

1

Hong Kong
1

1

Iran
1

1

2

Iraq

1

1

India
3
X
3
X
6

Indonesia

1

1

Italy
3
X
3
X
6

Japan
3
X
3
X
6

Kazakhstan
1

1

2

Luxembourg
1

1

Malaysia
3
X
1

4

Mexico
3
X
3
X
6

Moldova
1

1

Mongolia
1

1

2

Myanmar
1

1

Netherlands
1

1

Norway
1

1

North Korea

1

1

Philippines
1

1

2

Poland
1

1

2

Russia

3
X
3

Samoa

1

1

San Marino
1

1

South Africa

1

1

South Korea
3
X
3
X
6

Spain
1

1

2

Slovenia
1

1

Sweden

1

1

Switzerland
1

1

2

Chinese Taipei
3
X
3
X
6

Thailand
1

1

Turkey

1

1

Ukraine
3
X
3
X
6

United States
3
X
3
X
6

Venezuela
1

1

2

Total: 55 NOCs
64
12
64
12
128

Analyze the provided table and extract the contents of specified rows, identified by row indices. 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"]}.
Target rows:
row 51
row 17
row 27
row 33
row 42

The extracted row contents are listed below.
For row 51: {"row_id": "51", "cell_list": ['switzerland', '1', 'none', '1', 'none', '2']}
For row 17: {"row_id": "17", "cell_list": ['estonia', 'none', 'none', '1', 'none', '1']}
For row 27: {"row_id": "27", "cell_list": ['india', '3', 'x', '3', 'x', '6']}
For row 33: {"row_id": "33", "cell_list": ['malaysia', '3', 'x', '1', 'none', '4']}
For row 42: {"row_id": "42", "cell_list": ['poland', '1', 'none', '1', 'none', '2']}