remittance
in terms of remittances , of the countries who had remittances over 10 in 2011 , the only time the remittance was over 50 in 2010 was when the country was india .
{'scope': 'subset', 'row': '1', 'col': '4', 'col_other': '1', 'criterion': 'greater_than', 'value': '50', 'subset': {'col': '5', 'criterion': 'greater_than', 'value': '10'}}
{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'remittances 2011', '10'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; remittances 2011 ; 10 }', 'tointer': 'select the rows whose remittances 2011 record is greater than 10 .'}, 'remittances 2010', '50'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose remittances 2011 record is greater than 10 . among these rows , select the rows whose remittances 2010 record is greater than 50 .', 'tostr': 'filter_greater { filter_greater { all_rows ; remittances 2011 ; 10 } ; remittances 2010 ; 50 }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_greater { filter_greater { all_rows ; remittances 2011 ; 10 } ; remittances 2010 ; 50 } }', 'tointer': 'select the rows whose remittances 2011 record is greater than 10 . among these rows , select the rows whose remittances 2010 record is greater than 50 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'remittances 2011', '10'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; remittances 2011 ; 10 }', 'tointer': 'select the rows whose remittances 2011 record is greater than 10 .'}, 'remittances 2010', '50'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose remittances 2011 record is greater than 10 . among these rows , select the rows whose remittances 2010 record is greater than 50 .', 'tostr': 'filter_greater { filter_greater { all_rows ; remittances 2011 ; 10 } ; remittances 2010 ; 50 }'}, 'country'], 'result': 'india', 'ind': 3, 'tostr': 'hop { filter_greater { filter_greater { all_rows ; remittances 2011 ; 10 } ; remittances 2010 ; 50 } ; country }'}, 'india'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_greater { filter_greater { all_rows ; remittances 2011 ; 10 } ; remittances 2010 ; 50 } ; country } ; india }', 'tointer': 'the country record of this unqiue row is india .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_greater { filter_greater { all_rows ; remittances 2011 ; 10 } ; remittances 2010 ; 50 } } ; eq { hop { filter_greater { filter_greater { all_rows ; remittances 2011 ; 10 } ; remittances 2010 ; 50 } ; country } ; india } } = true', 'tointer': 'select the rows whose remittances 2011 record is greater than 10 . among these rows , select the rows whose remittances 2010 record is greater than 50 . there is only one such row in the table . the country record of this unqiue row is india .'}
and { only { filter_greater { filter_greater { all_rows ; remittances 2011 ; 10 } ; remittances 2010 ; 50 } } ; eq { hop { filter_greater { filter_greater { all_rows ; remittances 2011 ; 10 } ; remittances 2010 ; 50 } ; country } ; india } } = true
select the rows whose remittances 2011 record is greater than 10 . among these rows , select the rows whose remittances 2010 record is greater than 50 . there is only one such row in the table . the country record of this unqiue row is india .
{'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_greater_1': 'filter_greater', 'filter_greater_0': 'filter_greater', 'all_rows_7': 'all_rows', 'remittances 2011_8': 'remittances 2011', '10_9': '10', 'remittances 2010_10': 'remittances 2010', '50_11': '50', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'country_12': 'country', 'india_13': 'india'}
['country', 'remittances 2008', 'remittances 2009', 'remittances 2010', 'remittances 2011']
[['india', '49.98', '49.20', '53.48', '63.82'], ['china', '22.69', '22.90', '33.44', '40.48'], ['mexico', '26.04', '22.08', '22.08', '23.59'], ['philippines', '18.63', '19.73', '21.37', '22.97'], ['nigeria', '19.21', '18.37', '19.82', '20.62'], ['france', '16.28', '16.06', '16.71', '19.31'], ['egypt', '8.69', '7.15', '12.45', '14.32'], ['germany', '10.97', '11.30', '11.73', '13.16'], ['pakistan', '7.04', '8.72', '9.69', '12.26'], ['bangladesh', '8.93', '10.52', '10.85', '12.07'], ['belgium', '10.42', '10.44', '10.30', '10.91'], ['spain', '10.15', '8.95', '9.11', '9.91'], ['vietnam', '6.81', '6.02', '8.26', '8.60'], ['south korea', '9.07', '7.28', '7.06', '8.49']]