View source for Example on a report for initial and last year

'''Variable for world'''<br/>This first sheet will include values for the world for all [https://pardee.du.edu/wiki/Variable_names variables ]that were chosen to be compared. This will allow the variables to be sorted and compared easily.

'''Example'''

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{| border="0" cellpadding="0" cellspacing="0" width="678"
|-
| height="19" width="122" style="text-align: center;" | Variables
| width="64" style="text-align: center;" | region
| width="182" style="text-align: center;" | Unit
| width="182" style="text-align: center;" | Ratio
| width="64" style="text-align: center;" | 2015
| width="64" style="text-align: center;" | 2100
|-
| height="19" style="text-align: center;" | WATSAFE
| style="text-align: center;" | World
| style="text-align: center;" | UnImproved
| style="text-align: center;" | IFsNew-X%GDP/IFsbaseold_j
| style="text-align: center;" | 1
| style="text-align: center;" | 0.963
|-
| height="19" style="text-align: center;" | GOVREV
| style="text-align: center;" | World
| style="text-align: center;" | Trillion $
| style="text-align: center;" | IFsNew-X%GDP/IFsbaseold_j
| style="text-align: center;" | 1
| style="text-align: center;" | 1.005
|-
| height="19" style="text-align: center;" | LIFEXP
| style="text-align: center;" | World
| style="text-align: center;" | Total
| style="text-align: center;" | IFsNew-X%GDP/IFsbaseold_j
| style="text-align: center;" | 1
| style="text-align: center;" | 0.9994
|-
| height="19" style="text-align: center;" | EDYRSAG15
| style="text-align: center;" | World
| style="text-align: center;" | Total
| style="text-align: center;" | IFsNew-X%GDP/IFsbaseold_j
| style="text-align: center;" | 1
| style="text-align: center;" | 0.9991
|-
| height="19" style="text-align: center;" | EDYRSAG25
| style="text-align: center;" | World
| style="text-align: center;" | Total
| style="text-align: center;" | IFsNew-X%GDP/IFsbaseold_j
| style="text-align: center;" | 1
| style="text-align: center;" | 0.9991
|-
| height="19" style="text-align: center;" | ENP
| style="text-align: center;" | World
| style="text-align: center;" | Total
| style="text-align: center;" | IFsNew-X%GDP/IFsbaseold_j
| style="text-align: center;" | 1
| style="text-align: center;" | 1.025
|-
| height="19" style="text-align: center;" | INFRAELECACC
| style="text-align: center;" | World
| style="text-align: center;" | Total
| style="text-align: center;" | IFsNew-X%GDP/IFsbaseold_j
| style="text-align: center;" | 1.006
| style="text-align: center;" | 1
|}

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'''Individual variable sheet'''<br/>The following sheets are&nbsp;for individual countries and respective [https://pardee.du.edu/wiki/Variable_names variables]. It includes country, raw data, and ratio for intial year and last year. This allows&nbsp;to compare highest and lowest values and their respective raw data.

'''Example 1 for GDP:'''

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{| border="0" cellpadding="0" cellspacing="0" width="565"
|-
| height="19" width="129" | 
| width="77" style="text-align: center;" | New base
| width="77" style="text-align: center;" | Old base
| width="77" style="text-align: center;" | New base
| width="77" style="text-align: center;" | Old base
| width="64" style="text-align: center;" | 
| width="64" style="text-align: center;" | 
|-
| height="19" style="text-align: center;" | &nbsp;
| style="text-align: center;" | GDP[10]
| style="text-align: center;" | GDP[8]
| style="text-align: center;" | GDP[10]
| style="text-align: center;" | GDP[8]
| style="text-align: center;" | 
| style="text-align: center;" | 
|-
| height="19" style="text-align: center;" | Country
| style="text-align: center;" | 2015 values
| style="text-align: center;" | 2015 values
| style="text-align: center;" | 2100 values
| style="text-align: center;" | 2100 values
| style="text-align: center;" | &nbsp;2015 ratio
| style="text-align: center;" | 2100 ratio
|-
| height="19" style="text-align: center;" | Afghanistan
| style="text-align: center;" | 0.022
| style="text-align: center;" | 0.022
| style="text-align: center;" | 1.055
| style="text-align: center;" | 0.882
| style="text-align: center;" | 1
| style="text-align: center;" | 1.196145
|-
| height="19" style="text-align: center;" | Albania
| style="text-align: center;" | 0.014
| style="text-align: center;" | 0.014
| style="text-align: center;" | 0.045
| style="text-align: center;" | 0.04
| style="text-align: center;" | 1
| style="text-align: center;" | 1.125
|-
| height="19" style="text-align: center;" | Algeria
| style="text-align: center;" | 0.229
| style="text-align: center;" | 0.229
| style="text-align: center;" | 1.595
| style="text-align: center;" | 1.495
| style="text-align: center;" | 1
| style="text-align: center;" | 1.06689
|-
| height="19" style="text-align: center;" | Angola
| style="text-align: center;" | 0.135
| style="text-align: center;" | 0.135
| style="text-align: center;" | 5.518
| style="text-align: center;" | 6.271
| style="text-align: center;" | 1
| style="text-align: center;" | 0.879923
|-
| height="19" style="text-align: center;" | Argentina
| style="text-align: center;" | 0.538
| style="text-align: center;" | 0.538
| style="text-align: center;" | 2.472
| style="text-align: center;" | 2.493
| style="text-align: center;" | 1
| style="text-align: center;" | 0.991576
|}

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'''Example 2 for POP:'''

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{| border="0" cellpadding="0" cellspacing="0" width="648"
|-
| height="19" width="196" style="text-align: center;" | POP
| width="81" style="text-align: center;" | New base
| width="81" style="text-align: center;" | Old base
| width="81" style="text-align: center;" | New base
| width="81" style="text-align: center;" | Old base
| width="64" style="text-align: center;" | 
| width="64" style="text-align: center;" | 
|-
| height="19" style="text-align: center;" | Row Labels
| style="text-align: center;" | 2015
| style="text-align: center;" | 2015
| style="text-align: center;" | 2100
| style="text-align: center;" | 2100
| style="text-align: center;" | &nbsp; &nbsp; &nbsp; 2015 ratio
| style="text-align: center;" | 2100 ratio
|-
| height="19" style="text-align: center;" | Afghanistan
| style="text-align: center;" | 34.41
| style="text-align: center;" | 34.41
| style="text-align: center;" | 110.7
| style="text-align: center;" | 90.51
| style="text-align: center;" | 1
| style="text-align: center;" | 1.223069
|-
| height="19" style="text-align: center;" | Albania
| style="text-align: center;" | 2.891
| style="text-align: center;" | 2.891
| style="text-align: center;" | 1.654
| style="text-align: center;" | 1.657
| style="text-align: center;" | 1
| style="text-align: center;" | 0.998189
|-
| height="19" style="text-align: center;" | Algeria
| style="text-align: center;" | 39.73
| style="text-align: center;" | 39.73
| style="text-align: center;" | 64.63
| style="text-align: center;" | 61.63
| style="text-align: center;" | 1
| style="text-align: center;" | 1.048678
|-
| height="19" style="text-align: center;" | Angola
| style="text-align: center;" | 27.88
| style="text-align: center;" | 27.88
| style="text-align: center;" | 168.6
| style="text-align: center;" | 153.5
| style="text-align: center;" | 1
| style="text-align: center;" | 1.098371
|-
| height="19" style="text-align: center;" | Argentina
| style="text-align: center;" | 43.08
| style="text-align: center;" | 43.08
| style="text-align: center;" | 53.17
| style="text-align: center;" | 52.91
| style="text-align: center;" | 1
| style="text-align: center;" | 1.004914
|-
| height="19" style="text-align: center;" | Armenia
| style="text-align: center;" | 2.926
| style="text-align: center;" | 2.926
| style="text-align: center;" | 2.132
| style="text-align: center;" | 1.977
| style="text-align: center;" | 1
| style="text-align: center;" | 1.078402
|-
| height="19" style="text-align: center;" | Australia
| style="text-align: center;" | 23.93
| style="text-align: center;" | 23.93
| style="text-align: center;" | 39.61
| style="text-align: center;" | 38.86
| style="text-align: center;" | 1
| style="text-align: center;" | 1.0193
|}

----



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'''Final sheet'''<br/>This final sheet is created by appending all individual variable sheets. This sheet allows to sort values among all variables and countries.

'''Example'''<br/>------------------------

{| border="0" cellpadding="0" cellspacing="0" width="670"
|-
| height="19" width="122" style="text-align: center;" | Variable
| width="196" style="text-align: center;" | Country
| width="64" style="text-align: center;" | 
| width="119" style="text-align: center;" | ratio
| width="64" style="text-align: center;" | 2015 ratio
| width="105" style="text-align: center;" | 2100 ratio
|-
| height="19" style="text-align: center;" | INCOMELT310LN
| style="text-align: center;" | Slovak Rep
| style="text-align: center;" | Mil People
| style="text-align: center;" | IFsNew-X%GDP/IFsbaseold_j
| style="text-align: center;" | 180.2
| style="text-align: center;" | 3,672
|-
| height="19" style="text-align: center;" | INCOMELT310LN
| style="text-align: center;" | Montenegro
| style="text-align: center;" | Mil People
| style="text-align: center;" | IFsNew-X%GDP/IFsbaseold_j
| style="text-align: center;" | 149.5
| style="text-align: center;" | 42,635
|-
| height="19" style="text-align: center;" | INCOMELT310LN
| style="text-align: center;" | Poland
| style="text-align: center;" | Mil People
| style="text-align: center;" | IFsNew-X%GDP/IFsbaseold_j
| style="text-align: center;" | 114.1
| style="text-align: center;" | 22,586
|-
| height="19" style="text-align: center;" | INCOMELT310LN
| style="text-align: center;" | Hungary
| style="text-align: center;" | Mil People
| style="text-align: center;" | IFsNew-X%GDP/IFsbaseold_j
| style="text-align: center;" | 99.91
| style="text-align: center;" | 2,502
|-
| height="19" style="text-align: center;" | INCOMELT310LN
| style="text-align: center;" | Estonia
| style="text-align: center;" | Mil People
| style="text-align: center;" | IFsNew-X%GDP/IFsbaseold_j
| style="text-align: center;" | 28.16
| style="text-align: center;" | 161
|-
| height="19" style="text-align: center;" | INCOMELT310LN
| style="text-align: center;" | Serbia
| style="text-align: center;" | Mil People
| style="text-align: center;" | IFsNew-X%GDP/IFsbaseold_j
| style="text-align: center;" | 19.4
| style="text-align: center;" | 51,771
|-
| height="19" style="text-align: center;" | INCOMELT310LN
| style="text-align: center;" | Latvia
| style="text-align: center;" | Mil People
| style="text-align: center;" | IFsNew-X%GDP/IFsbaseold_j
| style="text-align: center;" | 16.14
| style="text-align: center;" | 87.06
|-
| height="19" style="text-align: center;" | VADD
| style="text-align: center;" | Lesotho
| style="text-align: center;" | Materials
| style="text-align: center;" | IFsNew-X%GDP/IFsbaseold_j
| style="text-align: center;" | 10.75
| style="text-align: center;" | 7.464
|-
| height="19" style="text-align: center;" | VADD
| style="text-align: center;" | Turkmenistan
| style="text-align: center;" | ICTech
| style="text-align: center;" | IFsNew-X%GDP/IFsbaseold_j
| style="text-align: center;" | 4.554
| style="text-align: center;" | 6.966
|-
| height="19" style="text-align: center;" | INFRAELECACC
| style="text-align: center;" | Sudan South
| style="text-align: center;" | Total
| style="text-align: center;" | IFsNew-X%GDP/IFsbaseold_j
| style="text-align: center;" | 4.186
| style="text-align: center;" | 1.012
|}

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''This page was updated on 08/24/2020.''