list of how it 's made episodes
of the how it 's made episodes , the episode where segment a was metal detectors was one episode before the episode where segment a was riding mowers .
{'row_1': '8', 'row_2': '9', 'col': '2', 'col_other': '4', 'relation': 'diff', 'record_mentioned': 'yes', 'diff_result': {'diff_value': '1', 'bigger': 'row2'}}
{'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'segment a', 'metal detectors'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose segment a record fuzzily matches to metal detectors .', 'tostr': 'filter_eq { all_rows ; segment a ; metal detectors }'}, 'episode'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; segment a ; metal detectors } ; episode }', 'tointer': 'select the rows whose segment a record fuzzily matches to metal detectors . take the episode record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'segment a', 'riding mowers'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose segment a record fuzzily matches to riding mowers .', 'tostr': 'filter_eq { all_rows ; segment a ; riding mowers }'}, 'episode'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; segment a ; riding mowers } ; episode }', 'tointer': 'select the rows whose segment a record fuzzily matches to riding mowers . take the episode record of this row .'}], 'result': '-1', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; segment a ; metal detectors } ; episode } ; hop { filter_eq { all_rows ; segment a ; riding mowers } ; episode } }'}, '-1'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; segment a ; metal detectors } ; episode } ; hop { filter_eq { all_rows ; segment a ; riding mowers } ; episode } } ; -1 }', 'tointer': 'select the rows whose segment a record fuzzily matches to metal detectors . take the episode record of this row . select the rows whose segment a record fuzzily matches to riding mowers . take the episode record of this row . the second record is 1 larger than the first record .'}, {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'segment a', 'metal detectors'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose segment a record fuzzily matches to metal detectors .', 'tostr': 'filter_eq { all_rows ; segment a ; metal detectors }'}, 'episode'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; segment a ; metal detectors } ; episode }', 'tointer': 'select the rows whose segment a record fuzzily matches to metal detectors . take the episode record of this row .'}, '151'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; segment a ; metal detectors } ; episode } ; 151 }', 'tointer': 'the episode record of the first row is 151 .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'segment a', 'riding mowers'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose segment a record fuzzily matches to riding mowers .', 'tostr': 'filter_eq { all_rows ; segment a ; riding mowers }'}, 'episode'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; segment a ; riding mowers } ; episode }', 'tointer': 'select the rows whose segment a record fuzzily matches to riding mowers . take the episode record of this row .'}, '152'], 'result': True, 'ind': 7, 'tostr': 'eq { hop { filter_eq { all_rows ; segment a ; riding mowers } ; episode } ; 152 }', 'tointer': 'the episode record of the second row is 152 .'}], 'result': True, 'ind': 8, 'tostr': 'and { eq { hop { filter_eq { all_rows ; segment a ; metal detectors } ; episode } ; 151 } ; eq { hop { filter_eq { all_rows ; segment a ; riding mowers } ; episode } ; 152 } }', 'tointer': 'the episode record of the first row is 151 . the episode record of the second row is 152 .'}], 'result': True, 'ind': 9, 'tostr': 'and { eq { diff { hop { filter_eq { all_rows ; segment a ; metal detectors } ; episode } ; hop { filter_eq { all_rows ; segment a ; riding mowers } ; episode } } ; -1 } ; and { eq { hop { filter_eq { all_rows ; segment a ; metal detectors } ; episode } ; 151 } ; eq { hop { filter_eq { all_rows ; segment a ; riding mowers } ; episode } ; 152 } } } = true', 'tointer': 'select the rows whose segment a record fuzzily matches to metal detectors . take the episode record of this row . select the rows whose segment a record fuzzily matches to riding mowers . take the episode record of this row . the second record is 1 larger than the first record . the episode record of the first row is 151 . the episode record of the second row is 152 .'}
and { eq { diff { hop { filter_eq { all_rows ; segment a ; metal detectors } ; episode } ; hop { filter_eq { all_rows ; segment a ; riding mowers } ; episode } } ; -1 } ; and { eq { hop { filter_eq { all_rows ; segment a ; metal detectors } ; episode } ; 151 } ; eq { hop { filter_eq { all_rows ; segment a ; riding mowers } ; episode } ; 152 } } } = true
select the rows whose segment a record fuzzily matches to metal detectors . take the episode record of this row . select the rows whose segment a record fuzzily matches to riding mowers . take the episode record of this row . the second record is 1 larger than the first record . the episode record of the first row is 151 . the episode record of the second row is 152 .
{'and_9': 'and', 'result_10': 'true', 'eq_5': 'eq', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_11': 'all_rows', 'segment a_12': 'segment a', 'metal detectors_13': 'metal detectors', 'episode_14': 'episode', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_15': 'all_rows', 'segment a_16': 'segment a', 'riding mowers_17': 'riding mowers', 'episode_18': 'episode', '-1_19': '-1', 'and_8': 'and', 'eq_6': 'eq', '151_20': '151', 'eq_7': 'eq', '152_21': '152'}
['series ep', 'episode', 'netflix', 'segment a', 'segment b', 'segment c', 'segment d']
[['12 - 01', '144', 's06e14', 'pneumatic impact wrenches', 'cultured marble sinks', 'plantain chips', 'nascar stock cars'], ['12 - 02', '145', 's06e15', 'jaws of life', 'artificial christmas trees', 'soda crackers', 'ratchets'], ['12 - 03', '146', 's06e16', 's thermometer', 'produce scales', 'aircraft painting', 'luxury s chocolate'], ['12 - 04', '147', 's06e17', 'carburetors', 'air conditioners', 'sugar ( part 1 )', 'sugar ( part 2 )'], ['12 - 05', '148', 's06e18', 'combination wrenches', 'deli meats', 'golf cars', 'airships'], ['12 - 06', '149', 's06e19', 'carbon fibre car parts', 'hand dryers', 'recycled polyester yarn', 'fleece'], ['12 - 07', '150', 's06e20', 'police badges', 'muffins', 'car washes', 'pressure gauges'], ['12 - 08', '151', 's06e21', 'metal detectors', 'rum', 'tiffany reproductions', 'aircraft engines'], ['12 - 09', '152', 's06e22', 'riding mowers', 'popcorn', 'adjustable beds', 'cultured diamonds'], ['12 - 10', '153', 's06e23', 'airstream trailers', 'horseradish', 'industrial steam s boiler', 'deodorant'], ['12 - 11', '154', 's06e24', 's screwdriver', 'compact track loaders', 'physician scales', 'carbon fibre bats'], ['12 - 12', '155', 's06e25', 's escalator', 'kevlar s canoe', 'goat cheese', 'disc music boxes']]