Understanding the diagonal in Pandas' scatter matrix plot

Question

I'm plotting a scatter plot with Pandas. I can understand the plot, except the curves in diagonal plots. Can someone explain to me what they mean?

Image:

Code:

import pylab import numpy as np from pandas.tools.plotting import scatter_matrix import pandas as pd  def make_scatter_plot(X, name):         """     Make scatterplot.      Parameters:     -----------     X:a design matrix where each column is a feature and each row is an observation.     name: the name of the plot.     """     pylab.clf()     df = pd.DataFrame(X)     axs = scatter_matrix(df, alpha=0.2, diagonal='kde')      for ax in axs[:,0]: # the left boundary         ax.grid('off', axis='both')         ax.set_yticks([0, .5])      for ax in axs[-1,:]: # the lower boundary         ax.grid('off', axis='both')         ax.set_xticks([0, .5])      pylab.savefig(name + ".png") 

Answer 1

As you can tell, the scatter matrix is plotting each of the columns specified against each other column.

However, in this format, when you got to a diagonal, you would see a plot of a column against itself. Since this would always be a straight line, Pandas decides it can give you more useful information, and plots the density plot of just that column of data.

See http://pandas.pydata.org/pandas-docs/stable/visualization.html#density-plot.

If you would rather have a histogram, you could change your plotting code to:

axs = scatter_matrix(df, alpha=0.2, diagonal='hist')