In [1]:

    

%pylab inline
import matplotlib.pyplot as plt
#use a nicer plotting style
plt.style.use(u'fivethirtyeight')
print(plt.style.available)

#change figure size
pylab.rcParams['figure.figsize'] = (10, 6)


    

    




/usr/local/lib/python2.7/site-packages/matplotlib/__init__.py:872: UserWarning: axes.color_cycle is deprecated and replaced with axes.prop_cycle; please use the latter.
  warnings.warn(self.msg_depr % (key, alt_key))






    




Populating the interactive namespace from numpy and matplotlib
[u'seaborn-darkgrid', u'seaborn-notebook', u'classic', u'seaborn-ticks', u'grayscale', u'bmh', u'seaborn-talk', u'dark_background', u'ggplot', u'fivethirtyeight', u'seaborn-colorblind', u'seaborn-deep', u'seaborn-whitegrid', u'seaborn-bright', u'seaborn-poster', u'seaborn-muted', u'seaborn-paper', u'seaborn-white', u'seaborn-pastel', u'seaborn-dark', u'seaborn-dark-palette']

In [3]:

    

import pandas as pd
aq=pd.read_csv('data/anscombesQuartet.csv')


    

In [5]:

    

aq


    

    
Out[5]:






  

    

      

      
I_x
      
I_y
      
II_x
      
II_y
      
III_x
      
III_y
      
IV_x
      
IV_y
    
  
  

    

      
0
      
10.0
      
8.04
      
10.0
      
9.14
      
10.0
      
7.46
      
8.0
      
6.58
    
    

      
1
      
8.0
      
6.95
      
8.0
      
8.14
      
8.0
      
6.77
      
8.0
      
5.76
    
    

      
2
      
13.0
      
7.58
      
13.0
      
8.74
      
13.0
      
12.74
      
8.0
      
7.71
    
    

      
3
      
9.0
      
8.81
      
9.0
      
8.77
      
9.0
      
7.11
      
8.0
      
8.84
    
    

      
4
      
11.0
      
8.33
      
11.0
      
9.26
      
11.0
      
7.81
      
8.0
      
8.47
    
    

      
5
      
14.0
      
9.96
      
14.0
      
8.10
      
14.0
      
8.84
      
8.0
      
7.04
    
    

      
6
      
6.0
      
7.24
      
6.0
      
6.13
      
6.0
      
6.08
      
8.0
      
5.25
    
    

      
7
      
4.0
      
4.26
      
4.0
      
3.10
      
4.0
      
5.39
      
19.0
      
12.50
    
    

      
8
      
12.0
      
10.84
      
12.0
      
9.13
      
12.0
      
8.15
      
8.0
      
5.56
    
    

      
9
      
7.0
      
4.82
      
7.0
      
7.26
      
7.0
      
6.42
      
8.0
      
7.91
    
    

      
10
      
5.0
      
5.68
      
5.0
      
4.74
      
5.0
      
5.73
      
8.0
      
6.89
    
  

In [ ]:

    

aq.describe()


    

In [ ]:

    

plot(aq['I_x'], aq['I_y'],'o')
figure()
plot(aq['II_x'], aq['II_y'],'o')
figure()
plot(aq['III_x'], aq['III_y'],'o')
figure()
plot(aq['IV_x'], aq['IV_y'],'o')


    

In [ ]:

    




    

In [ ]: