In [4]:

    

import matplotlib
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
%matplotlib
matplotlib.style.use("ggplot")


    

    




Using matplotlib backend: MacOSX

In [5]:

    

df = pd.DataFrame(np.random.randn(1000, 5), columns=['a', 'b', 'c', 'd', 'e'])
df.corr()


    

    
Out[5]:






  

    

      

      
a
      
b
      
c
      
d
      
e
    
  
  

    

      
a
      
1.000000
      
0.037434
      
-0.026023
      
-0.015054
      
0.002693
    
    

      
b
      
0.037434
      
1.000000
      
-0.030336
      
-0.018162
      
-0.040271
    
    

      
c
      
-0.026023
      
-0.030336
      
1.000000
      
-0.000742
      
0.045151
    
    

      
d
      
-0.015054
      
-0.018162
      
-0.000742
      
1.000000
      
0.004389
    
    

      
e
      
0.002693
      
-0.040271
      
0.045151
      
0.004389
      
1.000000
    
  

In [6]:

    

plt.imshow(df.corr(), cmap=plt.cm.Blues, interpolation="nearest")
plt.colorbar()
tick_marks = [i for i in range(len(df.columns))]
plt.xticks(tick_marks, df.columns, rotation="vertical")
plt.yticks(tick_marks, df.columns)
plt.show()


    

In [ ]: