def test_cast_int_to_float(self):
result = render(P(type=_join_type_map.index('inner'),
colnames=(['A'], [])),
pd.DataFrame({'A': [1, 2, 3]}),
PR('', {'A': [1.0, 2.0, 4.0]}))
expected = pd.DataFrame({'A': [1.0, 2.0]})
assert_frame_equal(result.dataframe, expected)
def test_join(self):
# Nothing too technical, do not need to test pandas functions
set_string(self.url_pval, self.valid_workflow_URL)
set_string(self.colnames_pval, 'key')
set_integer(self.type_pval, _join_type_map.index("inner"))
result = JoinURL.render(self.wfm, self.table)
assert_frame_equal(self.ref_left_join, result.dataframe)
def test_type_mismatch(self):
# Joining on column with different dtypes should fail
set_string(self.url_pval, self.valid_workflow_URL)
set_string(self.colnames_pval, 'key')
set_integer(self.type_pval, _join_type_map.index("inner"))
result = JoinURL.render(self.wfm, self.table_with_types)
self.assertEqual(("Types do not match for key column 'key' (number and text). " \
'Please use a type conversion module to make these column types consistent.'), result.error)
def test_type_num_cast(self):
# Joining on column that is both int and float, module should convert to float
version = self.wfm.store_fetched_table(self.ext_workflow_with_types)
self.wfm.set_fetched_data_version(version)
set_string(self.url_pval, self.valid_workflow_URL)
set_string(self.colnames_pval, 'key')
set_integer(self.type_pval, _join_type_map.index("inner"))
result = JoinURL.render(self.wfm, self.table_with_types)
assert_frame_equal(self.ref_left_join_with_types, result.dataframe)
def test_type_mismatch(self):
result = render(P(type=_join_type_map.index('inner'),
colnames=(['A'], [])),
pd.DataFrame({'A': [1, 2, 3]}),
PR('', {'A': ['1', '2', '3']}))
self.assertEqual(result, ProcessResult(error=(
'Types do not match for key column "A" (number and text). '
'Please use a type conversion module '
'to make these column types consistent.'
)))
def test_importcols(self):
result = render(P(type=_join_type_map.index('inner'),
colnames=(['key'], []), select_columns=True,
importcols=(['col2'], [])),
pd.DataFrame({'col1': ['a', 'a'], 'key': ['b', 'c']}),
PR('', {
'key': ['b', 'd'],
'col2': ['c', 'a'],
'col3': ['d', 'b'],
}))
self.assertEqual(['col1', 'key', 'col2'],
list(result.dataframe.columns))
def test_importcols(self):
# Should only import 1 column
set_string(self.url_pval, self.valid_workflow_URL)
set_string(self.colnames_pval, 'key')
set_string(self.importcols_pval, 'col2')
set_checkbox(self.select_columns_pval, True)
set_integer(self.type_pval, _join_type_map.index("inner"))
result = JoinURL.render(self.wfm, self.table.copy())
assert_frame_equal(self.ref_left_join[['col1', 'key', 'col2']],
result.dataframe)
# When select_column false, should import all columns
set_checkbox(self.select_columns_pval, False)
result = JoinURL.render(self.wfm, self.table.copy())
assert_frame_equal(self.ref_left_join, result.dataframe)
def test_join(self):
# Nothing too technical, do not need to test pandas functions
result = render(P(type=_join_type_map.index('inner'),
colnames=(['key'], [])),
pd.DataFrame({'col1': ['a', 'a'], 'key': ['b', 'c']}),
PR('', {
'key': ['b', 'd'],
'col2': ['c', 'a'],
'col3': ['d', 'b'],
}))
assert_frame_equal(result.dataframe, pd.DataFrame({
'col1': ['a'],
'key': ['b'],
'col2': ['c'],
'col3': ['d'],
}))
