import matplotlib.pyplot as plt
from sklearn.cluster import DBSCAN

def perform_dbscan_clustering(data, data_name, eps, min_samples):
    x = data[data_name].to_numpy()
    dbscan = DBSCAN(eps=eps, min_samples=min_samples)
    y_dbscan = dbscan.fit_predict(x)

    fig = plt.figure()
    if len(data_name) == 2:
        ax = fig.add_subplot(projection='rectilinear')
        plt.scatter(x[:, 0], x[:, 1], c=y_dbscan, s=50, cmap="viridis")
    else:
        ax = fig.add_subplot(projection='3d')
        ax.scatter(x[:, 0], x[:, 1], x[:, 2], c=y_dbscan, s=50, cmap="viridis")
    return fig