In [50]:

    

import pandas as pd


    

In [51]:

    

raw_data = pd.ExcelFile('london.xlsx')
data = raw_data.parse('Sheet1')

print data.head()


    

    




               Date   Time  Number_of_Casualties
2770115  23/11/1990  00:01                     2
4661940  07/12/1998  00:01                     1
2264722  11/09/1988  00:01                     1
2268405  06/08/1988  00:01                     2
5583244  13/07/2002  00:01                     1

In [52]:

    

data['Date'] = pd.to_datetime(data['Date'])


    

In [53]:

    

data['Date'][:5]


    

    
Out[53]:





2770115   1990-11-23
4661940   1998-07-12
2264722   1988-11-09
2268405   1988-06-08
5583244   2002-07-13
Name: Date, dtype: datetime64[ns]

In [54]:

    

data.sort(['Date'], inplace=True)
data.head()


    

    
Out[54]:






  

    

      

      
Date
      
Time
      
Number_of_Casualties
    
  
  

    

      
21
      
1979-01-01
      
 13:10
      
 2
    
    

      
6 
      
1979-01-01
      
 03:00
      
 2
    
    

      
7 
      
1979-01-01
      
 03:00
      
 1
    
    

      
15
      
1979-01-01
      
 10:00
      
 1
    
    

      
2 
      
1979-01-01
      
 01:25
      
 3
    
  

In [55]:

    

data2 = data[(data['Date'] > pd.to_datetime('2000-08-01')) & (data['Date'] < pd.to_datetime('2000-08-30'))]


    

In [56]:

    

data2.set_index('Date', inplace=True)
data2.head()

data2 = data2[['Number_of_Casualties']]
data2.head()


    

    
Out[56]:






  

    

      

      
Number_of_Casualties
    
    

      
Date
      

    
  
  

    

      
2000-08-02
      
 1
    
    

      
2000-08-02
      
 1
    
    

      
2000-08-02
      
 1
    
    

      
2000-08-02
      
 2
    
    

      
2000-08-02
      
 1
    
  

In [57]:

    

%pylab inline
import matplotlib.pylab as plt
data2.plot()
plt.show()


    

    




Populating the interactive namespace from numpy and matplotlib






    

In [ ]: