looking for a platform to share our trajectory data, I got interested in buzz data. They started a little contest, and since it seemed to be a nice way to test the functionality of the web site, I participated.

I downloaded the dataset of water consumption in Canada for the last years. The data is split by year and ward. I focused on the total water consumption and ran a little analysis.

A simple ANOVA shows that the total consumption is dependent on the year, the ward and the combination of the two (this means that the differences between years consumption is not equivalent in the distinct wards). In the visualization, one can see that the mean consumption decreased in the last three years (black dots are means of consumption for each year). In the trace for each ward, we can pick particular wards with specific results. For instance ward 11 had a huge increase in consumption in 2002; and ward 2 decrease its (relative to the other very important) consumption every year since 2002.

water consumption in Toronto in the last few years in the different wards

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anova results

                     Df     Sum Sq    Mean Sq  F value    Pr(>F)
data$Year             1 6.2445e+13 6.2445e+13 110.0587 < 2.2e-16 ***
data$Ward            43 5.1300e+15 1.1930e+14 210.2682 < 2.2e-16 ***
data$Year:data$Ward  43 1.0535e+14 2.4500e+12   4.3181 2.399e-15 ***
Residuals           396 2.2468e+14 5.6738e+11
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Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
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The test show that it is quite easy to take data and perform its own  analysis. Buzz data is not (yet?) very good in updating data, since  there is no way to directly add data (in this case, once the 2011 data  come, it will be needed to download the dataset, add the new data and  reupload the new dataset. Not very convenient.