In [5]:

    

%matplotlib inline
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd


    

In [6]:

    

# Load data from file
data = np.loadtxt('ex2data1.txt',dtype='float',delimiter=',')
X = data[:,:-1]; y = data[:,-1:]
print "Number of data points:", X.shape[0]
print "Number of features:",X.shape[1]
print "Sample data:"
print data[:5]


    

    




Number of data points: 100
Number of features: 2
Sample data:
[[ 34.62365962  78.02469282   0.        ]
 [ 30.28671077  43.89499752   0.        ]
 [ 35.84740877  72.90219803   0.        ]
 [ 60.18259939  86.3085521    1.        ]
 [ 79.03273605  75.34437644   1.        ]]

In [7]:

    

df = pd.DataFrame()
df['Exam1'] = X[:,0]
df['Exam2'] = X[:,1]
df['y'] = y[:,0]
df.head()


    

    
Out[7]:






  

    

      

      
Exam1
      
Exam2
      
y
    
  
  

    

      
0
      
34.623660
      
78.024693
      
0
    
    

      
1
      
30.286711
      
43.894998
      
0
    
    

      
2
      
35.847409
      
72.902198
      
0
    
    

      
3
      
60.182599
      
86.308552
      
1
    
    

      
4
      
79.032736
      
75.344376
      
1
    
  

In [30]:

    

sns.lmplot('Exam1', 'Exam2',
           data=df,
           fit_reg=False,
           #logistic=True,
           hue='y',
           scatter_kws={"marker": "D",
                        "s": 100})
plt.title('Admittance')


    

    
Out[30]:





<matplotlib.text.Text at 0x10a4c9e90>






    

In [32]:

    

sns.pairplot(df,hue='y')


    

    
Out[32]:





<seaborn.axisgrid.PairGrid at 0x106e32dd0>






    

In [ ]: