if __name__ == "__main__":
// Load the credit data set
data = pd.read_csv("../../../examples/data/credit/credit.csv")
// Specify the features of interest
features = [
"limit", "sex", "edu", "married", "age", "apr_delay", "may_delay",
"jun_delay", "jul_delay", "aug_delay", "sep_delay", "apr_bill", "may_bill",
"jun_bill", "jul_bill", "aug_bill", "sep_bill", "apr_pay", "may_pay", "jun_pay",
"jul_pay", "aug_pay", "sep_pay",
]
// Extract the numpy arrays from the data frame
X = data[features].as_matrix()
y = data.default.as_matrix()
// Instantiate the visualizer
pca(X, y, "images/pca_projection_2d.png", scale=True, center=False, col=y)
After Change
if __name__ == "__main__":
// Draw PCA with credit data set
X, y = load_credit()
colors = np.array(["r" if yi else "b" for yi in y])
pca(X, y, "images/pca_projection_2d.png", scale=True, color=colors)
pca(X, y, "images/pca_projection_3d.png", scale=True, color=colors, proj_dim=3)
