Vast amounts of data are stored in the world's computer systems. Making that data accessible is a first step to solving many problems we face, but humans are poor data processors. On the other hand we are excellent information processors. A first step in making data meaningful to people is to transform it into information. This begins with formatting it for viewing, and progresses through visualizations which let us see at a glance what the data is saying, to interactive simulations that let us ask what-if questions and play out scenarios.
I apologize if I've got you excited thinking about visualizations and simulation, because in this unit we're going to work on the more prosaic first step: Neatly tabulating and summarizing raw data.
What we have is a file whose contents are formatted like this,
Asia:Japan:120:144 North America:Mexico:78:762 Europe:England:56:94 Asia:USSR:275:8649 Europe:Germany:61:96 South America:Brasil:134:3286 North America:USA:237:3615 Asia:China:1032:3705 North America:Canada:25:3852 Europe:France:55:211 Asia:India:746:1267
but what we'd like is a report that looks like this:
CONTINENT COUNTRY POPULATION AREA POP. DEN.
(,000,000s) (,000s MI^2) (POP./MI^2)
Asia China 1032 3705 278.5
India 746 1267 588.8
Japan 120 144 833.3
USSR 275 8649 31.8
---- -----
Total 2173 13765
Europe England 56 94 595.7
France 55 211 260.7
Germany 61 96 635.4
---- -----
Total 172 401
North America Canada 25 3852 6.5
Mexico 78 762 102.4
USA 237 3615 65.6
---- -----
Total 340 8229
South America Brasil 134 3286 40.8
---- -----
Total 134 3286
You can see that it is much easier to scan the report and answer questions about the data than it is to scan the raw data file. The report has organized the data hierarchically from continent to country, and alphabetized the output by continent and country (helpful when looking for values in longer lists than we have here). In addition it has computed totals by continent, and population densities by country, and included those in the report enriching the raw data.