from __future__ import absolute_import, print_function, division


# rowreduce()
#############

import petl as etl
table1 = [['foo', 'bar'],
          ['a', 3],
          ['a', 7],
          ['b', 2],
          ['b', 1],
          ['b', 9],
          ['c', 4]]
def sumbar(key, rows):
    return [key, sum(row[1] for row in rows)]

table2 = etl.rowreduce(table1, key='foo', reducer=sumbar,
                       fields=['foo', 'barsum'])
table2


# aggregate()
#############

import petl as etl

table1 = [['foo', 'bar', 'baz'],
          ['a', 3, True],
          ['a', 7, False],
          ['b', 2, True],
          ['b', 2, False],
          ['b', 9, False],
          ['c', 4, True]]
# aggregate whole rows
table2 = etl.aggregate(table1, 'foo', len)
table2
# aggregate single field
table3 = etl.aggregate(table1, 'foo', sum, 'bar')
table3
# alternative signature using keyword args
table4 = etl.aggregate(table1, key=('foo', 'bar'),
                       aggregation=list, value=('bar', 'baz'))
table4
# aggregate multiple fields
from collections import OrderedDict
import petl as etl

aggregation = OrderedDict()
aggregation['count'] = len
aggregation['minbar'] = 'bar', min
aggregation['maxbar'] = 'bar', max
aggregation['sumbar'] = 'bar', sum
# default aggregation function is list
aggregation['listbar'] = 'bar'
aggregation['listbarbaz'] = ('bar', 'baz'), list
aggregation['bars'] = 'bar', etl.strjoin(', ')
table5 = etl.aggregate(table1, 'foo', aggregation)
table5


# mergeduplicates()
###################

import petl as etl
table1 = [['foo', 'bar', 'baz'],
          ['A', 1, 2.7],
          ['B', 2, None],
          ['D', 3, 9.4],
          ['B', None, 7.8],
          ['E', None, 42.],
          ['D', 3, 12.3],
          ['A', 2, None]]
table2 = etl.mergeduplicates(table1, 'foo')
table2


# merge()
#########

import petl as etl
table1 = [['foo', 'bar', 'baz'],
          [1, 'A', True],
          [2, 'B', None],
          [4, 'C', True]]
table2 = [['bar', 'baz', 'quux'],
          ['A', True, 42.0],
          ['B', False, 79.3],
          ['C', False, 12.4]]
table3 = etl.merge(table1, table2, key='bar')
table3


# fold()
########

import petl as etl
table1 = [['id', 'count'], 
          [1, 3], 
          [1, 5],
          [2, 4], 
          [2, 8]]        
import operator
table2 = etl.fold(table1, 'id', operator.add, 'count',
                  presorted=True)
table2