title: Plotting 2D Kernel Density Estimation with Python
body: <p>I would like to plot a 2D kernel density estimation. I find the seaborn package very useful here. However, after searching for a long time, I couldn't figure out how to make the y-axis and x-axis non-transparent. Also, how to show the values of the density on the contour? I would be very appreciated if someone could help me out. Below please see my code and graph. <img src="https://i.stack.imgur.com/HdKNY.png" alt="enter image description here"></p>
  
  <pre><code>import numpy as np
  import seaborn as sns
  import matplotlib.pyplot as pl
  
  Y = np.random.multivariate_normal((0, 0), [[0.8, 0.05], [0.05, 0.7]], 100)
  ax = sns.kdeplot(Y, shade = True, cmap = "PuBu")
  ax.patch.set_facecolor('white')
  ax.collections[0].set_alpha(0)
  ax.set_xlabel('$Y_1$', fontsize = 15)
  ax.set_ylabel('$Y_0$', fontsize = 15)
  pl.xlim(-3, 3)
  pl.ylim(-3, 3)
  pl.plot([-3, 3], [-3, 3], color = "black", linewidth = 1)
  pl.show()
  </code></pre>