def test_interestingness_1_2_0(): from lux.vis.Vis import Vis from lux.vis.Vis import Clause from lux.interestingness.interestingness import interestingness df = pd.read_csv("lux/data/car.csv") y_clause = Clause(attribute = "Name", channel = "y") color_clause = Clause(attribute = 'Cylinders', channel = "color") new_vis = Vis([y_clause, color_clause]) new_vis.refresh_source(df) new_vis #assert(len(new_vis.data)==color_cardinality*group_by_cardinality) assert(interestingness(new_vis, df)<0.01)
def test_interestingness_1_2_0(global_var): from lux.vis.Vis import Vis from lux.vis.Vis import Clause from lux.interestingness.interestingness import interestingness df = pytest.car_df y_clause = Clause(attribute="Name", channel="y") color_clause = Clause(attribute="Cylinders", channel="color") new_vis = Vis([y_clause, color_clause]) new_vis.refresh_source(df) new_vis # assert(len(new_vis.data)==color_cardinality*group_by_cardinality) assert interestingness(new_vis, df) < 0.01
def test_colored_bar_chart(): from lux.vis.Vis import Vis from lux.vis.Vis import Clause df = pd.read_csv("lux/data/car.csv") x_clause = Clause(attribute="MilesPerGal", channel="x") y_clause = Clause(attribute="Origin", channel="y") color_clause = Clause(attribute='Cylinders', channel="color") new_vis = Vis([x_clause, y_clause, color_clause], df) #make sure dimention of the data is correct color_cardinality = len(df.unique_values['Cylinders']) group_by_cardinality = len(df.unique_values['Origin']) assert (len(new_vis.data.columns) == 3) assert ( len(new_vis.data) == 15 > group_by_cardinality < color_cardinality * group_by_cardinality ) # Not color_cardinality*group_by_cardinality since some combinations have 0 values
def test_colored_bar_chart(): from lux.vis.Vis import Vis from lux.vis.Vis import Clause tbl = lux.LuxSQLTable() tbl.set_SQL_table("cars") x_clause = Clause(attribute="milespergal", channel="x") y_clause = Clause(attribute="origin", channel="y") color_clause = Clause(attribute="cylinders", channel="color") new_vis = Vis([x_clause, y_clause, color_clause], tbl) # make sure dimention of the data is correct color_carsdinality = len(tbl.unique_values["cylinders"]) group_by_carsdinality = len(tbl.unique_values["origin"]) assert len(new_vis.data.columns) == 3 assert ( len(new_vis.data) == 15 > group_by_carsdinality < color_carsdinality * group_by_carsdinality ) # Not color_carsdinality*group_by_carsdinality since some combinations have 0 values
def test_colored_bar_chart(global_var): from lux.vis.Vis import Vis from lux.vis.Vis import Clause df = pytest.car_df x_clause = Clause(attribute="MilesPerGal", channel="x") y_clause = Clause(attribute="Origin", channel="y") color_clause = Clause(attribute="Cylinders", channel="color") new_vis = Vis([x_clause, y_clause, color_clause], df) # make sure dimention of the data is correct color_cardinality = len(df.unique_values["Cylinders"]) group_by_cardinality = len(df.unique_values["Origin"]) assert len(new_vis.data.columns) == 3 # Not color_cardinality*group_by_cardinality since some combinations have 0 values assert len( new_vis.data ) == 15 > group_by_cardinality < color_cardinality * group_by_cardinality
def test_colored_line_chart(): from lux.vis.Vis import Vis from lux.vis.Vis import Clause df = pd.read_csv("lux/data/car.csv") df["Year"] = pd.to_datetime( df["Year"], format='%Y') # change pandas dtype for the column "Year" to datetype x_clause = Clause(attribute="Year", channel="x") y_clause = Clause(attribute="MilesPerGal", channel="y") color_clause = Clause(attribute='Cylinders', channel="color") new_vis = Vis([x_clause, y_clause, color_clause]) new_vis.refresh_source(df) #make sure dimention of the data is correct color_cardinality = len(df.unique_values['Cylinders']) group_by_cardinality = len(df.unique_values['Year']) assert (len(new_vis.data.columns) == 3) assert ( len(new_vis.data) == 60 > group_by_cardinality < color_cardinality * group_by_cardinality ) # Not color_cardinality*group_by_cardinality since some combinations have 0 values
def test_colored_line_chart(global_var): from lux.vis.Vis import Vis from lux.vis.Vis import Clause df = pytest.car_df # change pandas dtype for the column "Year" to datetype df["Year"] = pd.to_datetime(df["Year"], format="%Y") x_clause = Clause(attribute="Year", channel="x") y_clause = Clause(attribute="MilesPerGal", channel="y") color_clause = Clause(attribute="Cylinders", channel="color") new_vis = Vis([x_clause, y_clause, color_clause], df) # make sure dimention of the data is correct color_cardinality = len(df.unique_values["Cylinders"]) group_by_cardinality = len(df.unique_values["Year"]) assert len(new_vis.data.columns) == 3 # Not color_cardinality*group_by_cardinality since some combinations have 0 values assert len( new_vis.data ) == 60 > group_by_cardinality < color_cardinality * group_by_cardinality
def test_colored_bar_chart(): from lux.vis.Vis import Vis from lux.vis.Vis import Clause connection = psycopg2.connect( "host=localhost dbname=postgres user=postgres password=lux") sql_df = lux.LuxSQLTable() lux.config.set_SQL_connection(connection) sql_df.set_SQL_table("car") x_clause = Clause(attribute="MilesPerGal", channel="x") y_clause = Clause(attribute="Origin", channel="y") color_clause = Clause(attribute="Cylinders", channel="color") new_vis = Vis([x_clause, y_clause, color_clause], sql_df) # make sure dimention of the data is correct color_cardinality = len(sql_df.unique_values["Cylinders"]) group_by_cardinality = len(sql_df.unique_values["Origin"]) assert len(new_vis.data.columns) == 3 assert ( len(new_vis.data) == 15 > group_by_cardinality < color_cardinality * group_by_cardinality ) # Not color_cardinality*group_by_cardinality since some combinations have 0 values