def test_check_sentinels(data_raw):
expander = DataFrameETL(cols_to_expand=['pid', 'djinn_type',
'animal', 'fruits'])
# fill in necessary parameters
expander._nan_string = 'effrit'
expander._nan_numeric = 1.0
expander._is_numeric = {}
expander.levels_ = {}
expander._cols_to_drop = expander.cols_to_drop
expander._cols_to_expand = expander.cols_to_expand
for col in expander.cols_to_expand:
expander._is_numeric[col] = expander._flag_numeric(
pd.unique(data_raw[col]))
expander._check_sentinels(data_raw)
assert expander._nan_string is not 'effrit'
assert expander._nan_numeric is not 1.0
assert not (data_raw[['pid', 'djinn_type', 'animal']] ==
expander._nan_string).any().any()
assert not (data_raw['fruits'] == expander._nan_numeric).any().any()
def test_flag_numeric():
test1 = [1, 'a', 'b']
test2 = [5.55, 0, np.nan]
expander = DataFrameETL()
assert expander._flag_numeric(test1) is False
assert expander._flag_numeric(test2) is True
