def test_create_col_names_numeric(data_raw):
expander = DataFrameETL(cols_to_expand=['pid', 'fruits'],
cols_to_drop=['djinn_type', 'animal'],
dummy_na=True)
expander._is_numeric = {'pid': 0, 'djinn_type': 0, 'fruits': 0}
expander._nan_numeric = NAN_NUMERIC
expander._nan_string = NAN_STRING
expander._cols_to_drop = expander.cols_to_drop
expander._cols_to_expand = expander.cols_to_expand
expander.levels_ = expander._create_levels(data_raw)
(cnames, unexpanded) = expander._create_col_names(data_raw)
cols_numeric = ['pid_a', 'pid_b', 'pid_c', 'pid_NaN', 'fruits_1.0',
'fruits_3.0', 'fruits_NaN', 'age']
assert cnames == cols_numeric
assert unexpanded == ['pid', 'fruits', 'age']
def test_create_col_names_no_dummy(data_raw):
expander = DataFrameETL(cols_to_expand=['pid', 'djinn_type', 'animal'],
cols_to_drop=['fruits'],
dummy_na=False)
expander._nan_sentinel = NAN_STRING
expander._cols_to_drop = expander.cols_to_drop
expander._cols_to_expand = expander.cols_to_expand
expander.levels_ = expander._create_levels(data_raw)
(cnames, unexpanded) = expander._create_col_names(data_raw)
cols_expected = [
'pid_a', 'pid_b', 'pid_c', 'djinn_type_effrit', 'djinn_type_marid',
'djinn_type_sila', 'age', 'animal_cat', 'animal_dog'
]
assert cnames == cols_expected
assert unexpanded == ['pid', 'djinn_type', 'age', 'animal']
def test_create_col_names_numeric(data_raw):
expander = DataFrameETL(cols_to_expand=['pid', 'fruits'],
cols_to_drop=['djinn_type', 'animal'],
dummy_na='expanded')
expander._nan_sentinel = NAN_STRING
expander._cols_to_drop = expander.cols_to_drop
expander._cols_to_expand = expander.cols_to_expand
expander._dummy_na = 'expanded'
expander.levels_ = expander._create_levels(data_raw)
expander._unexpanded_nans = expander._flag_unexpanded_nans(data_raw)
(cnames, unexpanded) = expander._create_col_names(data_raw)
cols_numeric = [
'pid_a', 'pid_b', 'pid_c', 'pid_NaN', 'fruits_1.0', 'fruits_3.0',
'fruits_NaN', 'age'
]
assert cnames == cols_numeric
assert unexpanded == ['pid', 'fruits', 'age']
def test_create_col_names(data_raw):
expander = DataFrameETL(cols_to_expand=['pid', 'djinn_type', 'animal'],
cols_to_drop=['fruits'],
dummy_na=True)
expander._is_numeric = {'pid': 0, 'djinn_type': 0, 'animal': 0}
expander._nan_numeric = NAN_NUMERIC
expander._nan_string = NAN_STRING
expander._cols_to_drop = expander.cols_to_drop
expander._cols_to_expand = expander.cols_to_expand
expander.levels_ = expander._create_levels(data_raw)
(cnames, unexpanded) = expander._create_col_names(data_raw)
cols_expected = ['pid_a', 'pid_b', 'pid_c', 'pid_NaN',
'djinn_type_effrit', 'djinn_type_marid',
'djinn_type_sila', 'djinn_type_NaN', 'age',
'animal_cat', 'animal_dog', 'animal_NaN']
assert cnames == cols_expected
assert unexpanded == ['pid', 'djinn_type', 'age', 'animal']
