Python: Data Analytics and Visualization

Computational tools

Let's start with correlation and covariance computation between two data objects. Both the Series and DataFrame have a cov method. On a DataFrame object, this method will compute the covariance between the Series inside the object:

>>> s1 = pd.Series(np.random.rand(3))
>>> s1
0    0.460324
1    0.993279
2    0.032957
dtype: float64
>>> s2 = pd.Series(np.random.rand(3))
>>> s2
0    0.777509
1    0.573716
2    0.664212
dtype: float64
>>> s1.cov(s2)
-0.024516360159045424

>>> df8 = pd.DataFrame(np.random.rand(12).reshape(4,3),  
                       columns=['a','b','c'])
>>> df8
          a         b         c
0  0.200049  0.070034  0.978615
1  0.293063  0.609812  0.788773
2  0.853431  0.243656  0.978057
0.985584  0.500765  0.481180
>>> df8.cov()
          a         b         c
a  0.155307  0.021273 -0.048449
b 0.021273 0.059925 ...