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%matplotlib inline


    

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from yellowbrick.datasets import load_occupancy
from yellowbrick.features import RadViz

# Load the classification dataset
X, y = load_occupancy()
features = X.columns

# Specify the target classes
classes = ["unoccupied", "occupied"]

# Instantiate the visualizer
visualizer = RadViz(
    classes=classes, features=features, 
    color=["orangered","orange"],
    size = (600,600)
)

visualizer.fit(X, y)           # Fit the data to the visualizer
visualizer.transform(X)        # Transform the data
visualizer.poof()              # Draw/show/poof the data


    

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from yellowbrick.datasets import load_credit
from yellowbrick.features import RadViz

# Load the classification dataset
X, y = load_credit()
features = X.columns

# Specify the target classes
classes = ['account in default', 'current with bills']

# Instantiate the visualizer
visualizer = RadViz(
    classes=classes, features=features, 
    color=["orangered","orange"],
    size = (600,600)
)

visualizer.fit(X, y)           # Fit the data to the visualizer
visualizer.transform(X)        # Transform the data
visualizer.poof()              # Draw/show/poof the data


    

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