## WAY 1
def correlation_matrix(df,title):
import numpy as np
from matplotlib import pyplot as plt
from matplotlib import cm as cm
# get name of variables
lvariables = df.columns.values
# create chart objects
fig = plt.figure()
ax1 = fig.add_subplot(111)
cmap = cm.get_cmap('jet', 30)
# plot
cax = ax1.imshow(df.corr(), interpolation="nearest", cmap=cmap)
# set grid
ax1.grid(True)
# set title
plt.title('MATRIX CORRELATION: %s'%title)
# set axis ticks
plt.xticks(range(0,len(lvariables),1),lvariables,fontsize=10, rotation='vertical')
plt.yticks(range(0,len(lvariables),1),lvariables,fontsize=10)
# build color bar
cbar = fig.colorbar(cax)
# display
plt.show()
## WAY 2
import matplotlib.pyplot as plt
from pandas.plotting import scatter_matrix
scatter_matrix(DF, alpha=0.2, figsize=(6, 6), diagonal='kde')
plt.show()