def test_cube_to_df_people_dimensions_bookings_table(
self, people, bookings, cube_003_people_dimensions_bookings_table):
cube = bookings.cube([people[var] for var in ("Source", "Occupation")])
df = cube.to_df(unclassified=True, totals=True)
assert_cube_dataframes_match(
df, cube_003_people_dimensions_bookings_table)
def test_cube_to_df_people_various_dimensions(
self, people, cube_001_people_various_dimensions):
cube = people.cube(
[people[var] for var in ("Income", "Occupation", "Source")])
df = cube.to_df(unclassified=True, totals=True)
assert_cube_dataframes_match(df, cube_001_people_various_dimensions)
def test_cube_to_df_bookings_single_dimension_default_count_measure_table(
self,
holidays,
bookings,
cube_007_bookings_single_dimension_default_count_measure,
):
cube = bookings.cube([bookings["Destination"]])
df = cube.to_df(unclassified=True, totals=True)
assert_cube_dataframes_match(
df, cube_007_bookings_single_dimension_default_count_measure,
False)
def test_cube_to_df_mixed_households_people_dimensions_households_table(
self,
households,
people,
cube_005_mixed_households_people_dimensions_households_table,
):
cube = households.cube([people[var] for var in ("Income", "Gender")] +
[households["Region"]])
df = cube.to_df(unclassified=True, totals=True)
assert_cube_dataframes_match(
df, cube_005_mixed_households_people_dimensions_households_table)
def test_cube_to_df_bookings_before_2020_cost_less_than_500(
self, bookings, cube_002_bookings_before_2020_cost_less_than_500):
before_2020_cost_less_than_500 = (bookings["Cost"] < 500) & (
bookings["boDate"] <= datetime(2019, 12, 31))
cube = before_2020_cost_less_than_500.cube([
bookings[var]
for var in ("Destination", "Product", "Response Code")
])
df = cube.to_df(unclassified=True, totals=True)
assert_cube_dataframes_match(
df, cube_002_bookings_before_2020_cost_less_than_500)
def test_cube_to_df_bookings_dimensions_households_selection_people_table(
self,
households,
people,
bookings,
cube_004_bookings_dimensions_households_selection_people_table,
):
north_west_or_f_car = (households["Region"] == ("02", "13")) | (
households["HHCarmak"] == ("FER", "FIA", "FOR"))
cube = north_west_or_f_car.cube(
[bookings[var] for var in ("Product", "Continent")], table=people)
df = cube.to_df(unclassified=True, totals=True)
assert_cube_dataframes_match(
df, cube_004_bookings_dimensions_households_selection_people_table)
def test_cube_to_df_mixed_hhds_jnys_ppl_dimensions_people_selection_journeys_table(
self,
households,
people,
bookings,
journeys,
cube_006_mixed_hhds_jnys_ppl_dimensions_people_selection_journeys_table,
):
cube = journeys.cube(
[households["Region"], journeys["Pool"], people["Gender"]],
selection=((people["Surname"].contains(["int", "str", "bool"],
match_case=False))
| (bookings["Continent"] == ("AM", "AU"))),
)
df = cube.to_df(unclassified=True, totals=True)
assert_cube_dataframes_match(
df,
cube_006_mixed_hhds_jnys_ppl_dimensions_people_selection_journeys_table
)
