text: import matplotlib.pyplot as plt
  plt.style.use('ggplot')
  import plotly.express as px
  from numpy import array, unique, where
  from pandas import DataFrame
  from sklearn.cluster import DBSCAN
  
  # Create data
  x_arr = array([11.10, 11.15,
                 5, 8, 1, 9,])
        
  y_arr =  array([2, 8, 1.8,
                  8, 0.6, 11,])
  
  # Convert array to a DataFrame
  x = DataFrame(x_arr)
  y = DataFrame(y_arr) 
  
  fig = px.scatter(x_arr, y_arr,)
  fig.show()
  
  X=array([[1038,660],
           [1045,680],
           [1038,750],
           [897,750],
           [807,780],
           [805,850],])
           
  # Fitting DBSCAN model to the dataset
  model = DBSCAN(eps=0.20,
                min_samples=2,)
  model.fit(X)
  
  # See the division of data in clusters
  y = model.fit_predict(X)
  y
  
  clusters = unique(y)
  
  for cluster in clusters:
  	row_ix = where(y == cluster)
  	plt.scatter(X[row_ix, 0], 
                X[row_ix, 1],)
  plt.show()
  