def test_load_data():
variables = [ordinal('education', ['high school', 'college', 'PhD']), ratio('age', drange=[0,99])]
file_path = './datasets/mini_test.csv'
ds = load_data(file_path, variables, 'participant_id')
assert ds.dfile == file_path
assert ds.variables == variables
def test_make_ordinal():
o = ordinal('education', ['high school', 'college', 'Master\'s', 'PhD'])
assert o.name == 'education'
assert o.categories == OrderedDict([
('high school', 1),
('college', 2),
('Master\'s', 3),
('PhD', 4)
])
assert o.drange == [1,4]
def test_load_data():
variables = [
ordinal('education', ['high school', 'college', 'PhD']),
ratio('age', drange=[0, 99])
]
file_path = './datasets/mini_test.csv'
ds = load_data(file_path, variables, 'participant_id')
assert ds.dfile == file_path
assert ds.variables == variables
categories = ['high school', 'college', 'PhD']
# variables = [ordinal('education', categories)]
edu = ordinal('education', ['high school', 'college', 'PhD'])
age = ratio('age', drange=[0, 99])
variables = [edu, age]
file_path = './datasets/mini_test.csv'
ds = load_data(file_path, variables, 'participant_id')
def test_index_in_dataset():
for v in variables:
assert (ds[v.name].equals(ds.data[v.name]))
# def test_select_equals():
# for v in variables:
# all_unique = ds.data[v.name].unique()