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
