In [1]:

    

import matplotlib.pyplot as plt

import pandas as pd
from pandas import DataFrame
import numpy as np

%matplotlib inline


    

In [2]:

    

#make random dataframe
df = DataFrame(np.random.randn(10, 4).cumsum(0),
                columns=['A', 'B', 'C', 'D'],
                index=np.arange(0, 100, 10)) #0 to 100, at intervals of 10


    

In [9]:

    

# turn a column into a sequence
s = df.ix[:,1] #sequence = dataframe 3rd column. index modifier?
type(s)
print s


    

    




0    -0.087359
10    0.349096
20   -1.042686
30   -1.200931
40   -1.630742
50   -1.690428
60    1.038322
70    0.369046
80   -0.506361
90   -0.494912
Name: B, dtype: float64

In [4]:

    

df


    

    
Out[4]:






  

    

      

      
A
      
B
      
C
      
D
    
  
  

    

      
0
      
-0.306899
      
-0.087359
      
1.100918
      
0.109715
    
    

      
10
      
-0.037300
      
0.349096
      
1.845239
      
1.667171
    
    

      
20
      
2.089129
      
-1.042686
      
1.697987
      
2.545941
    
    

      
30
      
1.160612
      
-1.200931
      
1.061789
      
2.646248
    
    

      
40
      
2.470987
      
-1.630742
      
0.663063
      
2.812492
    
    

      
50
      
2.218397
      
-1.690428
      
1.692802
      
2.781486
    
    

      
60
      
3.525866
      
1.038322
      
-0.459330
      
3.102383
    
    

      
70
      
3.934671
      
0.369046
      
-1.678545
      
1.988175
    
    

      
80
      
3.586243
      
-0.506361
      
-2.305494
      
1.267270
    
    

      
90
      
4.126378
      
-0.494912
      
-1.972927
      
0.703763
    
  

In [13]:

    

plt.figure() #http://matplotlib.org/api/figure_api.html customize the image
df.plot()
x=1
plt.title('Random')
plt.xlabel('Random X')
plt.ylabel('Random Y')
plt.xticks()        
    
plt.show()


    

    






<matplotlib.figure.Figure at 0x113d541d0>






    

In [10]:

    

from pandas.tools.plotting import bootstrap_plot
bootstrap_plot(s, size=5, samples=10, color='blue')


    

    
Out[10]:












    

In [ ]: