Recently, we stumbled upon a very useful public, web-based service, the Greek Fuel Prices Observatory ("Παρατηρητήριο Τιμών Υγρών Καυσίμων" in Greek). Its main objective is to allow consumers find out the prices of liquid fuels per type and geographic region. Having a wealth of fuel-related information at his disposal, one could build some innovative services (e.g. taking advantage of the geo-location of gas stations), find interesting stats or create meaningful charts.
One of the site's most interesting pages is that which contains the min, max and mean prices over the last 3 months: http://www.fuelprices.gr/price_stats_ng.view?time=1&prodclass=1
However, the hyperlink at the bottom right corner of the page (with the text "Γραφήματος") which is supposed to display a comprehensive graph returns an HTTP Status 500 exception message instead (at least as of 13th of April 2013). So, we could not resist scraping the data from the table with DEiXTo and presenting it nicely with a Google line chart after some post-processing. We used a regular expression to isolate the date, we reversed the order of the records found (so that the list is sorted chronologically, the oldest one first), we replaced commas in prices with dots (as a decimal mark) and we wrote a short script to produce the necessary lines for the arrayToDataTable method call of the Google Visualization API. Therefore, it was pretty straightforward to create the following:
Generally, there are various remarkable data visualization tools out there (one of the best is Google Charts of course) but we would not like to elaborate further on this now. Nevertheless, we would like to give emphasis on the fact that once you have rich and useful web data in hand you can exploit them in a wide variety of ways and come up with smart methods to analyze, use and present them. Your imagination is the only limit (along with the copyright restrictions).
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