Percentage of permanent residence issued to Chinese and Indian nationals in 2015, comparing with the rest of Asia

Data source: Yearbook of Immigration Statistics 2015, Homeland Security, United States



In [2]:

    
import pyexcel as p

base_url = "https://raw.githubusercontent.com/pyexcel/pyexcel-chart/master/"
sheet=p.get_sheet(url=base_url+"fy2015_table3d.xls")
sheet.top()









    Out[2]:




pyexcel sheet:


Table 3.                                                                                                                                            
PERSONS OBTAINING LAWFUL PERMANENT RESIDENT STATUS BY REGION AND COUNTRY OF BIRTH: FISCAL YEARS 2006 TO 2015                                         
                                                                                                                                                    
Region and country of birth                                                                                 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
REGION

Let skip the first three rows because they contain meta data only.



In [3]:

    
sheet=p.get_sheet(url=base_url+"fy2015_table3d.xls", start_row=3)
sheet.top()









    Out[3]:




pyexcel sheet:


Region and country of birth 2006   2007   2008   2009   2010   2011   2012   2013  2014   2015   
REGION                                                                                          
Total                      1266129 1052415 1107126 1130818 1042625 1062040 1031631 990553 1016518 1051031
Africa                     117421 94710  105915 127046 101355 100374 107241 98304 98413  101415 
Asia                       440335 397834 399027 413312 422063 451593 429599 400548 430508 419297



In [4]:

    
sheet.name_rows_by_column(0)
sheet.row.select(['Region and country of birth','Asia', 'India', 'China, People\'s Republic'])
sheet









    Out[4]:




Table 3 D:


Region and country of birth   2006   2007   2008   2009   2010   2011   2012   2013   2014   2015
Asia                       440335 397834 399027 413312 422063 451593 429599 400548 430508 419297
China, People's Republic    87307  76655  80271  64238  70863  87016  81784  71798  76089  74558
India                       61369  65353  63352  57304  69162  69013  66434  68458  77908  64116



In [5]:

    
sheet.transpose()
sheet









    Out[5]:




Table 3 D:


  Region and country of birth   Asia   China, People's Republic   India


                         2006 440335                      87307   61369
                         2007 397834                      76655   65353
                         2008 399027                      80271   63352
                         2009 413312                      64238   57304
                         2010 422063                      70863   69162
                         2011 451593                      87016   69013
                         2012 429599                      81784   66434
                         2013 400548                      71798   68458
                         2014 430508                      76089   77908
                         2015 419297                      74558   64116



In [6]:

    
sheet.plot(chart_type='line')









    Out[6]:



In [7]:

    
sheet









    Out[7]:




Table 3 D:


      Asia   China, People's Republic   India


2006 440335                      87307   61369
2007 397834                      76655   65353
2008 399027                      80271   63352
2009 413312                      64238   57304
2010 422063                      70863   69162
2011 451593                      87016   69013
2012 429599                      81784   66434
2013 400548                      71798   68458
2014 430508                      76089   77908
2015 419297                      74558   64116



In [9]:

    
pie_dict = {}
pie_dict['China'] = sheet['2015', 'China, People\'s Republic']/sheet['2015', 'Asia']
pie_dict['India'] = sheet['2015', 'India']/sheet['2015', 'Asia']
pie_dict['The Rest of Asia'] = 1 - pie_dict['China'] - pie_dict['India']
pie_sheet = p.get_sheet(adict=pie_dict)
pie_sheet









    Out[9]:




pyexcel_sheet1:


China             India              The Rest of Asia
0.1778166788696318 0.15291309024390826 0.66927023088646



In [10]:

    
pie_sheet.plot(
    chart_type='pie', 
    legend_at_bottom=True,
    title='Percentage of permanent residence issued to Chinese and Indian nationals in 2015, comparing with the rest of Asia'
)









    Out[10]:

Table 3.
PERSONS OBTAINING LAWFUL PERMANENT RESIDENT STATUS BY REGION AND COUNTRY OF BIRTH: FISCAL YEARS 2006 TO 2015

Region and country of birth	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015
REGION

Region and country of birth	Asia	China, People's Republic	India
2006	440335	87307	61369
2007	397834	76655	65353
2008	399027	80271	63352
2009	413312	64238	57304
2010	422063	70863	69162
2011	451593	87016	69013
2012	429599	81784	66434
2013	400548	71798	68458
2014	430508	76089	77908
2015	419297	74558	64116

China	India	The Rest of Asia
0.1778166788696318	0.15291309024390826	0.66927023088646