locomotives of the great western railway
beyer peacock & co has a total of 3 types of locomotives .
{'scope': 'subset', 'criterion': 'equal', 'value': 'beyer , peacock & co', 'result': '3', 'col': '1', 'subset': {'col': '1', 'criterion': 'equal', 'value': 'beyer , peacock & co'}}
{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'manufacturer', 'beyer , peacock & co'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; manufacturer ; beyer , peacock & co }', 'tointer': 'select the rows whose manufacturer record fuzzily matches to beyer , peacock & co .'}, 'manufacturer', 'beyer , peacock & co'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose manufacturer record fuzzily matches to beyer , peacock & co . among these rows , select the rows whose manufacturer record fuzzily matches to beyer , peacock & co .', 'tostr': 'filter_eq { filter_eq { all_rows ; manufacturer ; beyer , peacock & co } ; manufacturer ; beyer , peacock & co }'}], 'result': '3', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; manufacturer ; beyer , peacock & co } ; manufacturer ; beyer , peacock & co } }', 'tointer': 'select the rows whose manufacturer record fuzzily matches to beyer , peacock & co . among these rows , select the rows whose manufacturer record fuzzily matches to beyer , peacock & co . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; manufacturer ; beyer , peacock & co } ; manufacturer ; beyer , peacock & co } } ; 3 } = true', 'tointer': 'select the rows whose manufacturer record fuzzily matches to beyer , peacock & co . among these rows , select the rows whose manufacturer record fuzzily matches to beyer , peacock & co . the number of such rows is 3 .'}
eq { count { filter_eq { filter_eq { all_rows ; manufacturer ; beyer , peacock & co } ; manufacturer ; beyer , peacock & co } } ; 3 } = true
select the rows whose manufacturer record fuzzily matches to beyer , peacock & co . among these rows , select the rows whose manufacturer record fuzzily matches to beyer , peacock & co . the number of such rows is 3 .
{'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'manufacturer_6': 'manufacturer', 'beyer , peacock & co_7': 'beyer , peacock & co', 'manufacturer_8': 'manufacturer', 'beyer, peacock & co_9': 'beyer , peacock & co', '3_10': '3'}
['manufacturer', 'type', 'quantity', 'm & swj nos', 'gwr nos']
[['beyer , peacock & co', '0 - 4 - 4t', '1', '15', '23'], ['beyer , peacock & co', '2 - 6 - 0', '1', '16', '24'], ['sharp , stewart & co', '4 - 4 - 4t', '2', '17 - 18', '25 , 27'], ['dübs & co', '0 - 6 - 0t', '2', '13 - 14', '825 , 843'], ['beyer , peacock & co', '0 - 6 - 0', '10', '19 - 28', '1003 - 1011 , 1013'], ['north british locomotive co', '4 - 4 - 0', '9', '1 - 8 , 31', '1119 - 1126 , 1128'], ['dübs & co', '4 - 4 - 0', '1', '9', '1127'], ['dübs & co', '2 - 4 - 0', '3', '10 - 12', '1334 - 1336']]