def test_clean_df():
path = path1 + POLLUTANT.pm10.name + path2
df = get_stations_data(path)
assert df is not None
assert len(df.columns) == 8
clean_df(df)
assert len(df.columns) == 2
def test_get_best_no2_stations():
path = path1 + POLLUTANT.no2.name + path2
df = get_stations_data(path)
size = len(df)
df = get_best_stations(path, POLLUTANT.no2)
assert df is not None
assert len(df) < size
# number of best station/city for 'no2'
assert len(df) == 557
def get_worst_stations_helper(pollutant: POLLUTANT, cities: int):
path = path1 + pollutant.name + path2
df = get_stations_data(path)
size = len(df)
df = get_worst_stations(path, pollutant)
assert df is not None
assert len(df) < size
# number of worst station/city for a pollutant
assert len(df) == cities
def test_get_mean_per_city():
path = path1 + POLLUTANT.pm10.name + path2
df = get_stations_data(path)
size = len(df)
df = get_mean_per_city(path, POLLUTANT.pm10)
assert df is not None
assert len(df) < size
# number of best station/city for 'no2'
assert len(df) == 525
assert len(df.columns) == 3
def test_filter_main_cities():
path = path1 + POLLUTANT.pm10.name + path2
df = filter_main_cities(get_stations_data(path))
assert df is not None
assert len(df) == 121
def test_get_stations_data():
path = path1 + POLLUTANT.pm10.name + path2
df = get_stations_data(path)
assert df is not None