title: Jensen–Shannon divergence between two 2-D DataFrames
body: <p>I have two dataframes P (real dataset) and Q (fake generated dataset),  with the same number of columns and different number of rows. Each columns X_1, X_2, ... is an aspect of my data lets say X_1 = income, X_2 = age, ... I want to calculate the Jensen-Shannon divergence between the two joint probability distributions JSD(P(X_1, X_2,...,X_10) || Q(X_1, X_2, ...,X_10)). What is the smooth way to do this in python? I know scipy.special.kl_div does this for two 1-D data, but what about 2-D data?</p>