Table:
As of December 31,	2019	2018	2017	2016	2015

Working capital (1)	$207,599	$237,416	$306,296	$226,367	$219,219

Total assets	$545,118	$628,027	$669,094	$667,235	$632,904

Total debt (2)	$24,600	$25,600	$26,700	$27,800	$28,900

Stockholders’ equity	$380,426	$446,279	$497,911	$479,517	$480,160

Analyze the provided table and extract the contents of specified rows or columns, identified by row or column indices. The cells of every row or column should be presented in the JSON format of {"row_id/column_id":"<row or column index>", "cell_list":"<a list of cells in this row/column>"}, e.g., {"row_id":"3", "cell_list": ["xxx", "yyy", "zzz"]}.
Target rows or columns:
the 3rd row,
the 4th row,
the 6th column,
the 4th column,
the 3rd column,
the 1st column,

The extracted row or column contents are listed below.
For the 3rd row: {"row_id": "3", "cell_list": ['Total assets', '$545,118', '$628,027', '$669,094', '$667,235', '$632,904']}
For the 4th row: {"row_id": "4", "cell_list": ['Total debt (2)', '$24,600', '$25,600', '$26,700', '$27,800', '$28,900']}
For the 6th column: {"column_id": "6", "cell_list": ['2015', '$219,219', '$632,904', '$28,900', '$480,160']}
For the 4th column: {"column_id": "4", "cell_list": ['2017', '$306,296', '$669,094', '$26,700', '$497,911']}
For the 3rd column: {"column_id": "3", "cell_list": ['2018', '$237,416', '$628,027', '$25,600', '$446,279']}
For the 1st column: {"column_id": "1", "cell_list": ['As of December 31,', 'Working capital (1)', 'Total assets', 'Total debt (2)', 'Stockholders’ equity']}