### Sample Dataset to simulate query result
import random
headers = ['col1', 'col2', 'col3', 'col4', 'col5', 'col6', 'col7', 'col8', 'col9', 'col10', 't_stamp', 'color', 'area']
data = []
t_stamp = system.date.now()
for i in range(10):
newRow = [random.randrange(100) for j in range(10)]
t_stamp = system.date.addMinutes(t_stamp, 1)
newRow.extend([t_stamp, 'blue', 'zoneX'])
data.append(newRow)
dataIn = system.dataset.toPyDataSet(system.dataset.toDataSet(headers, data))
#util.printDataSet(dataIn)
print '---'
### Sorting
# List of exluded columns
excluded_cols = ['t_stamp', 'color', 'area']
# Get columns to use in sorting
filteredHeaders = [colName for colName in dataIn.getColumnNames() if colName not in excluded_cols]
for row in dataIn:
data = [row[colName] for colName in filteredHeaders]
#Sorting a zip sorts all lists by the first one.
pareto = [[x, y] for y, x in reversed(sorted(zip(data, filteredHeaders)))][:5]
print row['t_stamp'], pareto
row | col1 | col2 | col3 | col4 | col5 | col6 | col7 | col8 | col9 | col10 | t_stamp | color | area
-------------------------------------------------------------------------------------------------------------------------
0 | 99 | 40 | 49 | 0 | 70 | 32 | 76 | 69 | 70 | 33 | Mon May 02 12:39:36 EDT 2022 | blue | zoneX
1 | 75 | 81 | 77 | 51 | 49 | 93 | 62 | 15 | 59 | 53 | Mon May 02 12:40:36 EDT 2022 | blue | zoneX
2 | 45 | 7 | 39 | 63 | 74 | 31 | 29 | 8 | 82 | 44 | Mon May 02 12:41:36 EDT 2022 | blue | zoneX
3 | 31 | 39 | 57 | 72 | 79 | 16 | 17 | 57 | 48 | 9 | Mon May 02 12:42:36 EDT 2022 | blue | zoneX
4 | 1 | 24 | 68 | 57 | 66 | 92 | 54 | 72 | 46 | 67 | Mon May 02 12:43:36 EDT 2022 | blue | zoneX
5 | 53 | 64 | 5 | 60 | 55 | 93 | 64 | 96 | 66 | 63 | Mon May 02 12:44:36 EDT 2022 | blue | zoneX
6 | 41 | 24 | 23 | 82 | 50 | 89 | 77 | 74 | 99 | 27 | Mon May 02 12:45:36 EDT 2022 | blue | zoneX
7 | 4 | 40 | 24 | 56 | 3 | 17 | 85 | 74 | 68 | 53 | Mon May 02 12:46:36 EDT 2022 | blue | zoneX
8 | 33 | 16 | 64 | 55 | 76 | 64 | 21 | 44 | 13 | 14 | Mon May 02 12:47:36 EDT 2022 | blue | zoneX
9 | 79 | 31 | 46 | 53 | 1 | 8 | 35 | 63 | 69 | 14 | Mon May 02 12:48:36 EDT 2022 | blue | zoneX
---
Mon May 02 12:39:36 EDT 2022 [[u'col1', 99], [u'col7', 76], [u'col9', 70], [u'col5', 70], [u'col8', 69]]
Mon May 02 12:40:36 EDT 2022 [[u'col6', 93], [u'col2', 81], [u'col3', 77], [u'col1', 75], [u'col7', 62]]
Mon May 02 12:41:36 EDT 2022 [[u'col9', 82], [u'col5', 74], [u'col4', 63], [u'col1', 45], [u'col10', 44]]
Mon May 02 12:42:36 EDT 2022 [[u'col5', 79], [u'col4', 72], [u'col8', 57], [u'col3', 57], [u'col9', 48]]
Mon May 02 12:43:36 EDT 2022 [[u'col6', 92], [u'col8', 72], [u'col3', 68], [u'col10', 67], [u'col5', 66]]
Mon May 02 12:44:36 EDT 2022 [[u'col8', 96], [u'col6', 93], [u'col9', 66], [u'col7', 64], [u'col2', 64]]
Mon May 02 12:45:36 EDT 2022 [[u'col9', 99], [u'col6', 89], [u'col4', 82], [u'col7', 77], [u'col8', 74]]
Mon May 02 12:46:36 EDT 2022 [[u'col7', 85], [u'col8', 74], [u'col9', 68], [u'col4', 56], [u'col10', 53]]
Mon May 02 12:47:36 EDT 2022 [[u'col5', 76], [u'col6', 64], [u'col3', 64], [u'col4', 55], [u'col8', 44]]
Mon May 02 12:48:36 EDT 2022 [[u'col1', 79], [u'col9', 69], [u'col8', 63], [u'col4', 53], [u'col3', 46]]