swimming at the 2007 world aquatics championships - women 's 200 metre individual medley
in swimming at the 2007 world aquatics championships , in the women 's 200 metre individual medley , of the athletes with a 50 m split under 29.0 , the only one from zimbabwe is kirsty coventry .
{'scope': 'subset', 'row': '2', 'col': '4', 'col_other': '3', 'criterion': 'equal', 'value': 'zimbabwe', 'subset': {'col': '5', 'criterion': 'less_than', 'value': '29.0'}}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_less', 'args': ['all_rows', '50 m split', '29.0'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; 50 m split ; 29.0 }', 'tointer': 'select the rows whose 50 m split record is less than 29.0 .'}, 'nationality', 'zimbabwe'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose 50 m split record is less than 29.0 . among these rows , select the rows whose nationality record fuzzily matches to zimbabwe .', 'tostr': 'filter_eq { filter_less { all_rows ; 50 m split ; 29.0 } ; nationality ; zimbabwe }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_less { all_rows ; 50 m split ; 29.0 } ; nationality ; zimbabwe } }', 'tointer': 'select the rows whose 50 m split record is less than 29.0 . among these rows , select the rows whose nationality record fuzzily matches to zimbabwe . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_less', 'args': ['all_rows', '50 m split', '29.0'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; 50 m split ; 29.0 }', 'tointer': 'select the rows whose 50 m split record is less than 29.0 .'}, 'nationality', 'zimbabwe'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose 50 m split record is less than 29.0 . among these rows , select the rows whose nationality record fuzzily matches to zimbabwe .', 'tostr': 'filter_eq { filter_less { all_rows ; 50 m split ; 29.0 } ; nationality ; zimbabwe }'}, 'name'], 'result': 'kirsty coventry', 'ind': 3, 'tostr': 'hop { filter_eq { filter_less { all_rows ; 50 m split ; 29.0 } ; nationality ; zimbabwe } ; name }'}, 'kirsty coventry'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_less { all_rows ; 50 m split ; 29.0 } ; nationality ; zimbabwe } ; name } ; kirsty coventry }', 'tointer': 'the name record of this unqiue row is kirsty coventry .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_less { all_rows ; 50 m split ; 29.0 } ; nationality ; zimbabwe } } ; eq { hop { filter_eq { filter_less { all_rows ; 50 m split ; 29.0 } ; nationality ; zimbabwe } ; name } ; kirsty coventry } } = true', 'tointer': 'select the rows whose 50 m split record is less than 29.0 . among these rows , select the rows whose nationality record fuzzily matches to zimbabwe . there is only one such row in the table . the name record of this unqiue row is kirsty coventry .'}
and { only { filter_eq { filter_less { all_rows ; 50 m split ; 29.0 } ; nationality ; zimbabwe } } ; eq { hop { filter_eq { filter_less { all_rows ; 50 m split ; 29.0 } ; nationality ; zimbabwe } ; name } ; kirsty coventry } } = true
select the rows whose 50 m split record is less than 29.0 . among these rows , select the rows whose nationality record fuzzily matches to zimbabwe . there is only one such row in the table . the name record of this unqiue row is kirsty coventry .
{'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_str_eq_1': 'filter_str_eq', 'filter_less_0': 'filter_less', 'all_rows_7': 'all_rows', '50 m split_8': '50 m split', '29.0_9': '29.0', 'nationality_10': 'nationality', 'zimbabwe_11': 'zimbabwe', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'name_12': 'name', 'kirsty coventry_13': 'kirsty coventry'}
['place', 'lane', 'name', 'nationality', '50 m split', '100 m split', '150 m split', 'time']
[['1', '4', 'katie hoff', 'usa', '28.35', '1:01.96', '1:39.06', '2:10.13'], ['2', '5', 'kirsty coventry', 'zimbabwe', '28.73', '1:01.92', '1:40.00', '2:10.76'], ['3', '3', 'stephanie rice', 'australia', '28.45', '1:02.03', '1:40.39', '2:11.42'], ['4', '2', 'whitney myers', 'usa', '28.59', '1:01.72', '1:41.79', '2:13.73'], ['5', '6', 'julie hjorth - hansen', 'denmark', '28.96', '1:03.59', '1:42.09', '2:14.05'], ['6', '7', 'shayne reese', 'australia', '28.33', '1:03.03', '1:42.24', '2:14.89'], ['7', '8', 'georgina bardach', 'argentina', '29.76', '1:05.21', '1:43.83', '2:15.26'], ['8', '1', 'julia wilkinson', 'canada', '29.51', '1:03.82', '1:43.87', '2:15.28']]