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In [1]:

    
%matplotlib inline
import pandas as pd



In [2]:

    
from IPython.core.display import HTML
css = open('style-table.css').read() + open('style-notebook.css').read()
HTML('<style>{}</style>'.format(css))









    Out[2]:



In [3]:

    
sales1 = pd.read_csv('sales1.csv')
sales1









    Out[3]:






  
    
      
      Book title
      Number sold
      Sales price
      Royalty paid
    
  
  
    
      0
      The Bricklayer’s Bible
      8
      2.99
      0.55
    
    
      1
      Swimrand
      2
      1.99
      0.35
    
    
      2
      Pining For The Fisheries of Yore
      28
      2.99
      0.55
    
    
      3
      The Duck Goes Here
      34
      2.99
      0.55
    
    
      4
      The Tower Commission Report
      4
      11.50
      4.25



In [4]:

    
sales2 = pd.read_csv('sales2.csv')
sales2.fillna('')









    Out[4]:






  
    
      
      Title
      Units sold
      List price
      Royalty
    
  
  
    
      0
      
      
      
      
    
    
      1
      Sales report for Q4
      
      
      
    
    
      2
      E-Book Reader US Store
      
      
      
    
    
      3
      Pining for the Fisheries of Yore
      80
      3.5
      14.98
    
    
      4
      Swimrand
      1
      2.99
      0.14
    
    
      5
      The Bricklayer's Bible
      17
      3.5
      5.15
    
    
      6
      The Duck Goes Here
      34
      2.99
      5.78
    
    
      7
      The Tower Commission Report
      4
      9.5
      6.2
    
    
      8
      US royalties (USD)
      
      
      32.25
    
    
      9
      
      
      
      
    
    
      10
      
      
      
      
    
    
      11
      Sales report for Q4
      
      
      
    
    
      12
      E-Book Reader UK Store
      
      
      
    
    
      13
      Pining for the Fisheries of Yore
      47
      2.99
      11.98
    
    
      14
      The Bricklayer's Bible
      17
      2.99
      3.5
    
    
      15
      The Tower Commission Report
      4
      6.5
      4.8
    
    
      16
      UK royalties (GBP)
      
      
      20.28
    
    
      17
      
      
      
      
    
    
      18
      
      
      
      
    
    
      19
      Sales report for Q4
      
      
      
    
    
      20
      E-Book Reader France Store
      
      
      
    
    
      21
      Swimrand
      8
      1.99
      0.88
    
    
      22
      The Duck Goes Here
      12
      1.99
      1.5
    
    
      23
      France royalties (EUR)
      
      
      2.38

Challenge: first combine these sales together into a single dataframe, then compute how much money consumers spent on each book in each currency.



In [ ]:



In [ ]:

	Book title	Number sold	Sales price	Royalty paid
0	The Bricklayer’s Bible	8	2.99	0.55
1	Swimrand	2	1.99	0.35
2	Pining For The Fisheries of Yore	28	2.99	0.55
3	The Duck Goes Here	34	2.99	0.55
4	The Tower Commission Report	4	11.50	4.25

	Title	Units sold	List price	Royalty
0
1	Sales report for Q4
2	E-Book Reader US Store
3	Pining for the Fisheries of Yore	80	3.5	14.98
4	Swimrand	1	2.99	0.14
5	The Bricklayer's Bible	17	3.5	5.15
6	The Duck Goes Here	34	2.99	5.78
7	The Tower Commission Report	4	9.5	6.2
8	US royalties (USD)			32.25
9
10
11	Sales report for Q4
12	E-Book Reader UK Store
13	Pining for the Fisheries of Yore	47	2.99	11.98
14	The Bricklayer's Bible	17	2.99	3.5
15	The Tower Commission Report	4	6.5	4.8
16	UK royalties (GBP)			20.28
17
18
19	Sales report for Q4
20	E-Book Reader France Store
21	Swimrand	8	1.99	0.88
22	The Duck Goes Here	12	1.99	1.5
23	France royalties (EUR)			2.38