Financial analytics of SX5E and V2TX

Another nifty function of pandas is the describe function that gives us a summary statistics of every value inside each column of the Pandas DataFrame object:

>>>  print data.describe()
         EUROSTOXX       VSTOXX
count  4072.000000  4048.000000
mean   3254.538183    25.305428
std     793.191950     9.924404
min    1809.980000    11.596600
25%    2662.460000    18.429500
50%    3033.880000    23.168600
75%    3753.542500    28.409550
max    5464.430000    87.512700
[8 rows x 2 columns]

Pandas allows the values in the DataFrame object to be visualized as a graph using the plot function. Let's plot the EURO STOXX 50 and VSTOX to see how they look like over the years:

>>> from pylab import *
>>> data.plot(subplots=True,
...           figsize=(10, 8),          
...           color="blue",
...           grid=True)
>>> show()
Populating the interactive namespace from numpy and matplotlib
array([<matplotlib.axes.AxesSubplot...