def test_add_match_single_occurence(self):
"""Should add the match if there are no exact duplicates"""
test_series_1 = pd.Series(['foooo', 'no match', 'baz', 'foooo'])
test_series_2 = pd.Series(['foooo', 'bar', 'baz', 'foooob'])
sg = StringGrouper(test_series_1).fit()
sg.add_match('no match', 'baz')
matches = sg.get_matches()
matches = matches[(matches.left_side == 'no match') & (matches.right_side == 'baz')]
self.assertEqual(1, matches.shape[0])
sg2 = StringGrouper(test_series_1, test_series_2).fit()
sg2.add_match('no match', 'bar')
matches = sg2.get_matches()
matches = matches[(matches.left_side == 'no match') & (matches.right_side == 'bar')]
self.assertEqual(1, matches.shape[0])
def test_get_matches_2_series_2_id_series(self):
test_series_1 = pd.Series(['foo', 'bar', 'baz'])
test_series_id_1 = pd.Series(['A0', 'A1', 'A2'])
test_series_2 = pd.Series(['foo', 'bar', 'bop'])
test_series_id_2 = pd.Series(['B0', 'B1', 'B2'])
sg = StringGrouper(test_series_1,
test_series_2,
duplicates_id=test_series_id_2,
master_id=test_series_id_1).fit()
left_side = ['foo', 'bar']
left_side_id = ['A0', 'A1']
left_index = [0, 1]
right_side = ['foo', 'bar']
right_side_id = ['B0', 'B1']
right_index = [0, 1]
similarity = [1.0, 1.0]
expected_df = pd.DataFrame({
'left_index': left_index,
'left_side': left_side,
'left_id': left_side_id,
'similarity': similarity,
'right_id': right_side_id,
'right_side': right_side,
'right_index': right_index
})
expected_df.loc[:,
'similarity'] = expected_df.loc[:,
'similarity'].astype(
sg._config.
tfidf_matrix_dtype)
pd.testing.assert_frame_equal(expected_df, sg.get_matches())
def test_get_matches_two_dataframes(self):
test_series_1 = pd.Series(['foo', 'bar', 'baz'])
test_series_2 = pd.Series(['foo', 'bar', 'bop'])
sg = StringGrouper(test_series_1, test_series_2).fit()
left_side = ['foo', 'bar']
right_side = ['foo', 'bar']
similarity = [1.0, 1.0]
expected_df = pd.DataFrame({'left_side': left_side, 'right_side': right_side, 'similarity': similarity})
pd.testing.assert_frame_equal(expected_df, sg.get_matches())
def test_remove_match(self):
"""Should remove a match"""
test_series_1 = pd.Series(['foooo', 'no match', 'baz', 'foooob'])
test_series_2 = pd.Series(['foooo', 'bar', 'baz', 'foooob'])
sg = StringGrouper(test_series_1).fit()
sg.remove_match('foooo', 'foooob')
matches = sg.get_matches()
matches_1 = matches[(matches.left_side == 'foooo') & (matches.right_side == 'foooob')]
# In the case of only a master series, the matches are recursive, so both variants are to be removed
matches_2 = matches[(matches.left_side == 'foooob') & (matches.right_side == 'foooo')]
self.assertEqual(0, matches_1.shape[0])
self.assertEqual(0, matches_2.shape[0])
sg2 = StringGrouper(test_series_1, test_series_2).fit()
sg2.remove_match('foooo', 'foooob')
matches = sg2.get_matches()
matches = matches[(matches.left_side == 'foooo') & (matches.right_side == 'foooob')]
self.assertEqual(0, matches.shape[0])
def test_add_match_single_group_matches_symmetric(self):
"""New matches that are added to a SG with only a master series should be symmetric"""
test_series_1 = pd.Series(['foooo', 'no match', 'baz', 'foooo'])
sg = StringGrouper(test_series_1).fit()
sg.add_match('no match', 'baz')
matches = sg.get_matches()
matches_1 = matches[(matches.left_side == 'no match') & (matches.right_side == 'baz')]
self.assertEqual(1, matches_1.shape[0])
matches_2 = matches[(matches.left_side == 'baz') & (matches.right_side == 'no match')]
self.assertEqual(1, matches_2.shape[0])
def test_get_matches_1_series_1_id_series(self):
test_series_1 = pd.Series(['foo', 'bar', 'baz', 'foo'])
test_series_id_1 = pd.Series(['A0', 'A1', 'A2', 'A3'])
sg = StringGrouper(test_series_1, master_id=test_series_id_1)
sg = sg.fit()
left_side = ['foo', 'foo', 'bar', 'baz', 'foo', 'foo']
left_side_id = ['A0', 'A0', 'A1', 'A2', 'A3', 'A3']
right_side = ['foo', 'foo', 'bar', 'baz', 'foo', 'foo']
right_side_id = ['A3', 'A0', 'A1', 'A2', 'A3', 'A0']
similarity = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
expected_df = pd.DataFrame({'left_side_id': left_side_id, 'left_side': left_side,
'right_side_id': right_side_id, 'right_side': right_side, 'similarity': similarity})
pd.testing.assert_frame_equal(expected_df, sg.get_matches())
def test_get_matches_single(self):
test_series_1 = pd.Series(['foo', 'bar', 'baz', 'foo'])
sg = StringGrouper(test_series_1)
sg = sg.fit()
left_side = ['foo', 'foo', 'bar', 'baz', 'foo', 'foo']
right_side = ['foo', 'foo', 'bar', 'baz', 'foo', 'foo']
left_index = [0, 0, 1, 2, 3, 3]
right_index = [0, 3, 1, 2, 0, 3]
similarity = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
expected_df = pd.DataFrame({
'left_index': left_index,
'left_side': left_side,
'similarity': similarity,
'right_side': right_side,
'right_index': right_index
})
pd.testing.assert_frame_equal(expected_df, sg.get_matches())
def test_get_matches_two_dataframes(self):
test_series_1 = pd.Series(['foo', 'bar', 'baz'])
test_series_2 = pd.Series(['foo', 'bar', 'bop'])
sg = StringGrouper(test_series_1, test_series_2).fit()
left_side = ['foo', 'bar']
left_index = [0, 1]
right_side = ['foo', 'bar']
right_index = [0, 1]
similarity = [1.0, 1.0]
expected_df = pd.DataFrame({
'left_index': left_index,
'left_side': left_side,
'similarity': similarity,
'right_side': right_side,
'right_index': right_index
})
expected_df.loc[:,
'similarity'] = expected_df.loc[:,
'similarity'].astype(
sg._config.
tfidf_matrix_dtype)
pd.testing.assert_frame_equal(expected_df, sg.get_matches())
