Example on a report for initial and last year
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Variable for world
This first sheet will include values for the world for all variables that were chosen to be compared. This will allow the variables to be sorted and compared easily.
Example
| Variables | region | Unit | Ratio | 2015 | 2100 |
| WATSAFE | World | UnImproved | IFsNew-X%GDP/IFsbaseold_j | 1 | 0.963 |
| GOVREV | World | Trillion $ | IFsNew-X%GDP/IFsbaseold_j | 1 | 1.005 |
| LIFEXP | World | Total | IFsNew-X%GDP/IFsbaseold_j | 1 | 0.9994 |
| EDYRSAG15 | World | Total | IFsNew-X%GDP/IFsbaseold_j | 1 | 0.9991 |
| EDYRSAG25 | World | Total | IFsNew-X%GDP/IFsbaseold_j | 1 | 0.9991 |
| ENP | World | Total | IFsNew-X%GDP/IFsbaseold_j | 1 | 1.025 |
| INFRAELECACC | World | Total | IFsNew-X%GDP/IFsbaseold_j | 1.006 | 1 |
Individual variable sheet
The following sheets are for individual countries and respective variables. It includes country, raw data, and ratio for intial year and last year. This allows to compare highest and lowest values and their respective raw data.
Example 1 for GDP:
| New base | Old base | New base | Old base | |||
| GDP[10] | GDP[8] | GDP[10] | GDP[8] | |||
| Country | 2015 values | 2015 values | 2100 values | 2100 values | 2015 ratio | 2100 ratio |
| Afghanistan | 0.022 | 0.022 | 1.055 | 0.882 | 1 | 1.196145 |
| Albania | 0.014 | 0.014 | 0.045 | 0.04 | 1 | 1.125 |
| Algeria | 0.229 | 0.229 | 1.595 | 1.495 | 1 | 1.06689 |
| Angola | 0.135 | 0.135 | 5.518 | 6.271 | 1 | 0.879923 |
| Argentina | 0.538 | 0.538 | 2.472 | 2.493 | 1 | 0.991576 |
Example 2 for POP:
| POP | New base | Old base | New base | Old base | ||
| Row Labels | 2015 | 2015 | 2100 | 2100 | 2015 ratio | 2100 ratio |
| Afghanistan | 34.41 | 34.41 | 110.7 | 90.51 | 1 | 1.223069 |
| Albania | 2.891 | 2.891 | 1.654 | 1.657 | 1 | 0.998189 |
| Algeria | 39.73 | 39.73 | 64.63 | 61.63 | 1 | 1.048678 |
| Angola | 27.88 | 27.88 | 168.6 | 153.5 | 1 | 1.098371 |
| Argentina | 43.08 | 43.08 | 53.17 | 52.91 | 1 | 1.004914 |
| Armenia | 2.926 | 2.926 | 2.132 | 1.977 | 1 | 1.078402 |
| Australia | 23.93 | 23.93 | 39.61 | 38.86 | 1 | 1.0193 |
Final sheet
This final sheet is created by appending all individual variable sheets. This sheet allows to sort values among all variables and countries.
Example
------------------------
| Variable | Country | ratio | 2015 ratio | 2100 ratio | |
| INCOMELT310LN | Slovak Rep | Mil People | IFsNew-X%GDP/IFsbaseold_j | 180.2 | 3,672 |
| INCOMELT310LN | Montenegro | Mil People | IFsNew-X%GDP/IFsbaseold_j | 149.5 | 42,635 |
| INCOMELT310LN | Poland | Mil People | IFsNew-X%GDP/IFsbaseold_j | 114.1 | 22,586 |
| INCOMELT310LN | Hungary | Mil People | IFsNew-X%GDP/IFsbaseold_j | 99.91 | 2,502 |
| INCOMELT310LN | Estonia | Mil People | IFsNew-X%GDP/IFsbaseold_j | 28.16 | 161 |
| INCOMELT310LN | Serbia | Mil People | IFsNew-X%GDP/IFsbaseold_j | 19.4 | 51,771 |
| INCOMELT310LN | Latvia | Mil People | IFsNew-X%GDP/IFsbaseold_j | 16.14 | 87.06 |
| VADD | Lesotho | Materials | IFsNew-X%GDP/IFsbaseold_j | 10.75 | 7.464 |
| VADD | Turkmenistan | ICTech | IFsNew-X%GDP/IFsbaseold_j | 4.554 | 6.966 |
| INFRAELECACC | Sudan South | Total | IFsNew-X%GDP/IFsbaseold_j | 4.186 | 1.012 |
This page was updated on 08/24/2020.