text: # -*- coding: utf-8 -*-
  from __future__ import print_function
  
  import numpy as np
  import pytest
  
  from pandas.compat import product as cart_product, range
  
  from pandas import DataFrame, MultiIndex, Period, Series, Timedelta, Timestamp
  from pandas.util.testing import assert_frame_equal, assert_series_equal
  
  
  class TestCounting(object):
  
      def test_cumcount(self):
          df = DataFrame([['a'], ['a'], ['a'], ['b'], ['a']], columns=['A'])
          g = df.groupby('A')
          sg = g.A
  
          expected = Series([0, 1, 2, 0, 3])
  
          assert_series_equal(expected, g.cumcount())
          assert_series_equal(expected, sg.cumcount())
  
      def test_cumcount_empty(self):
          ge = DataFrame().groupby(level=0)
          se = Series().groupby(level=0)
  
          # edge case, as this is usually considered float
          e = Series(dtype='int64')
  
          assert_series_equal(e, ge.cumcount())
          assert_series_equal(e, se.cumcount())
  
      def test_cumcount_dupe_index(self):
          df = DataFrame([['a'], ['a'], ['a'], ['b'], ['a']], columns=['A'],
                         index=[0] * 5)
          g = df.groupby('A')
          sg = g.A
  
          expected = Series([0, 1, 2, 0, 3], index=[0] * 5)
  
          assert_series_equal(expected, g.cumcount())
          assert_series_equal(expected, sg.cumcount())
  
      def test_cumcount_mi(self):
          mi = MultiIndex.from_tuples([[0, 1], [1, 2], [2, 2], [2, 2], [1, 0]])
          df = DataFrame([['a'], ['a'], ['a'], ['b'], ['a']], columns=['A'],
                         index=mi)
          g = df.groupby('A')
          sg = g.A
  
          expected = Series([0, 1, 2, 0, 3], index=mi)
  
          assert_series_equal(expected, g.cumcount())
          assert_series_equal(expected, sg.cumcount())
  
      def test_cumcount_groupby_not_col(self):
          df = DataFrame([['a'], ['a'], ['a'], ['b'], ['a']], columns=['A'],
                         index=[0] * 5)
          g = df.groupby([0, 0, 0, 1, 0])
          sg = g.A
  
          expected = Series([0, 1, 2, 0, 3], index=[0] * 5)
  
          assert_series_equal(expected, g.cumcount())
          assert_series_equal(expected, sg.cumcount())
  
      def test_ngroup(self):
          df = DataFrame({'A': list('aaaba')})
          g = df.groupby('A')
          sg = g.A
  
          expected = Series([0, 0, 0, 1, 0])
  
          assert_series_equal(expected, g.ngroup())
          assert_series_equal(expected, sg.ngroup())
  
      def test_ngroup_distinct(self):
          df = DataFrame({'A': list('abcde')})
          g = df.groupby('A')
          sg = g.A
  
          expected = Series(range(5), dtype='int64')
  
          assert_series_equal(expected, g.ngroup())
          assert_series_equal(expected, sg.ngroup())
  
      def test_ngroup_one_group(self):
          df = DataFrame({'A': [0] * 5})
          g = df.groupby('A')
          sg = g.A
  
          expected = Series([0] * 5)
  
          assert_series_equal(expected, g.ngroup())
          assert_series_equal(expected, sg.ngroup())
  
      def test_ngroup_empty(self):
          ge = DataFrame().groupby(level=0)
          se = Series().groupby(level=0)
  
          # edge case, as this is usually considered float
          e = Series(dtype='int64')
  
          assert_series_equal(e, ge.ngroup())
          assert_series_equal(e, se.ngroup())
  
      def test_ngroup_series_matches_frame(self):
          df = DataFrame({'A': list('aaaba')})
          s = Series(list('aaaba'))
  
          assert_series_equal(df.groupby(s).ngroup(),
                              s.groupby(s).ngroup())
  
      def test_ngroup_dupe_index(self):
          df = DataFrame({'A': list('aaaba')}, index=[0] * 5)
          g = df.groupby('A')
          sg = g.A
  
          expected = Series([0, 0, 0, 1, 0], index=[0] * 5)
  
          assert_series_equal(expected, g.ngroup())
          assert_series_equal(expected, sg.ngroup())
  
      def test_ngroup_mi(self):
          mi = MultiIndex.from_tuples([[0, 1], [1, 2], [2, 2], [2, 2], [1, 0]])
          df = DataFrame({'A': list('aaaba')}, index=mi)
          g = df.groupby('A')
          sg = g.A
          expected = Series([0, 0, 0, 1, 0], index=mi)
  
          assert_series_equal(expected, g.ngroup())
          assert_series_equal(expected, sg.ngroup())
  
      def test_ngroup_groupby_not_col(self):
          df = DataFrame({'A': list('aaaba')}, index=[0] * 5)
          g = df.groupby([0, 0, 0, 1, 0])
          sg = g.A
  
          expected = Series([0, 0, 0, 1, 0], index=[0] * 5)
  
          assert_series_equal(expected, g.ngroup())
          assert_series_equal(expected, sg.ngroup())
  
      def test_ngroup_descending(self):
          df = DataFrame(['a', 'a', 'b', 'a', 'b'], columns=['A'])
          g = df.groupby(['A'])
  
          ascending = Series([0, 0, 1, 0, 1])
          descending = Series([1, 1, 0, 1, 0])
  
          assert_series_equal(descending, (g.ngroups - 1) - ascending)
          assert_series_equal(ascending, g.ngroup(ascending=True))
          assert_series_equal(descending, g.ngroup(ascending=False))
  
      def test_ngroup_matches_cumcount(self):
          # verify one manually-worked out case works
          df = DataFrame([['a', 'x'], ['a', 'y'], ['b', 'x'],
                          ['a', 'x'], ['b', 'y']], columns=['A', 'X'])
          g = df.groupby(['A', 'X'])
          g_ngroup = g.ngroup()
          g_cumcount = g.cumcount()
          expected_ngroup = Series([0, 1, 2, 0, 3])
          expected_cumcount = Series([0, 0, 0, 1, 0])
  
          assert_series_equal(g_ngroup, expected_ngroup)
          assert_series_equal(g_cumcount, expected_cumcount)
  
      def test_ngroup_cumcount_pair(self):
          # brute force comparison for all small series
          for p in cart_product(range(3), repeat=4):
              df = DataFrame({'a': p})
              g = df.groupby(['a'])
  
              order = sorted(set(p))
              ngroupd = [order.index(val) for val in p]
              cumcounted = [p[:i].count(val) for i, val in enumerate(p)]
  
              assert_series_equal(g.ngroup(), Series(ngroupd))
              assert_series_equal(g.cumcount(), Series(cumcounted))
  
      def test_ngroup_respects_groupby_order(self):
          np.random.seed(0)
          df = DataFrame({'a': np.random.choice(list('abcdef'), 100)})
          for sort_flag in (False, True):
              g = df.groupby(['a'], sort=sort_flag)
              df['group_id'] = -1
              df['group_index'] = -1
  
              for i, (_, group) in enumerate(g):
                  df.loc[group.index, 'group_id'] = i
                  for j, ind in enumerate(group.index):
                      df.loc[ind, 'group_index'] = j
  
              assert_series_equal(Series(df['group_id'].values),
                                  g.ngroup())
              assert_series_equal(Series(df['group_index'].values),
                                  g.cumcount())
  
      @pytest.mark.parametrize('datetimelike', [
          [Timestamp('2016-05-%02d 20:09:25+00:00' % i) for i in range(1, 4)],
          [Timestamp('2016-05-%02d 20:09:25' % i) for i in range(1, 4)],
          [Timedelta(x, unit="h") for x in range(1, 4)],
          [Period(freq="2W", year=2017, month=x) for x in range(1, 4)]])
      def test_count_with_datetimelike(self, datetimelike):
          # test for #13393, where DataframeGroupBy.count() fails
          # when counting a datetimelike column.
  
          df = DataFrame({'x': ['a', 'a', 'b'], 'y': datetimelike})
          res = df.groupby('x').count()
          expected = DataFrame({'y': [2, 1]}, index=['a', 'b'])
          expected.index.name = "x"
          assert_frame_equal(expected, res)
  
      def test_count_with_only_nans_in_first_group(self):
          # GH21956
          df = DataFrame({'A': [np.nan, np.nan], 'B': ['a', 'b'], 'C': [1, 2]})
          result = df.groupby(['A', 'B']).C.count()
          mi = MultiIndex(levels=[[], ['a', 'b']],
                          codes=[[], []],
                          names=['A', 'B'])
          expected = Series([], index=mi, dtype=np.int64, name='C')
          assert_series_equal(result, expected, check_index_type=False)
  