db = DBSCAN(eps=0.0375, min_samples=50).fit(X_principal)
labels1 = db.labels_

colours1 = {}
colours1[0] = 'r'
colours1[1] = 'g'
colours1[2] = 'b'
colours1[3] = 'c'
colours1[4] = 'y'
colours1[5] = 'm'
colours1[-1] = 'k'

cvec = [colours1[label] for label in labels1]
colors1 = ['r', 'g', 'b', 'c', 'y', 'm', 'k']

r = plt.scatter(
    X_principal['P1'], X_principal['P2'], marker='o', color=colors1[0])
g = plt.scatter(
    X_principal['P1'], X_principal['P2'], marker='o', color=colors1[1])
b = plt.scatter(
    X_principal['P1'], X_principal['P2'], marker='o', color=colors1[2])
c = plt.scatter(
    X_principal['P1'], X_principal['P2'], marker='o', color=colors1[3])
y = plt.scatter(
    X_principal['P1'], X_principal['P2'], marker='o', color=colors1[4])
m = plt.scatter(
    X_principal['P1'], X_principal['P2'], marker='o', color=colors1[5])
k = plt.scatter(
    X_principal['P1'], X_principal['P2'], marker='o', color=colors1[6])

plt.figure(figsize=(9,9))
plt.scatter(X_principal['P1'], X_principal['P2'], c=cvec)
plt.legend((r, g, b, c, y, m, k),
          ('Label 0', 'Label 1', 'Label 2', 'Label 3', 'Label 4', 'Label 5', 'Label -1'),
          scatterpoints=1,
          loc='upper left',
          ncol=3,
          fontsize=8)
plt.show()