searching the number of cluster find by DBSCAN algo by moving eps value

looking_best_eps_dbscan.py

from sklearn.cluster import DBSCAN
import pandas as pd
# You already have your feature in X

dbscan_eps = []
for i in [x / 10.0 for x in range(1, 20, 1)]:
    db = DBSCAN(eps=i).fit(X)
    n_clusters_ = len(set(db.labels_)) - (1 if -1 in db.labels_ else 0)
    print "eps = " +" "+ str(i) +" "+ " cluster = " + str(n_clusters_)
    dbscan_eps.append({'eps' : i,
               'n_cluster' : n_clusters_})
df_dbscan_eps = pd.DataFrame(dbscan_eps)
df_dbscan_eps.set_index('eps', inplace=True)
df_dbscan_eps.plot()