The Dashboard Dude

Results for the Canadian Community Health Survey, 2016 edition, was released in late September, 2017. I finally got around to putting it into a set of interactive Tableau report card dashboards to bring out the most telling information from the survey, which is comparisons to the national average in each year, and comparisons to 2015 results for the 2016 results. You can embed these dashboards into websites allowing for JavaScript below, like I did below, by clicking on the Share icon (third right in from bottom right), or send as a link. The embedding actually carries the variable values at whatever is set on the view you have when you grab the JavaScript, so you can leave the desired view on your blog and talk about it, rather than make the reader change the parameters so they can see what you were seeing when you wrote about it! Lovely feature! In these report cards, immediate visual results are shown as dots. Green dots mean (statistically) significantly better* results than th...

My latest Tableau project involves Canadian population demographics. Statistics Canada has estimates publicly available with many age groups, both traditional genders, and all the provinces and territories, for each year from 1971 to 2016. It's a lot of data which is not only cumbersome to manage and use, but hard to visualize without a lot of work. Well, Tableau enabled me to change that so here are some of the initial offerings. I will write more as I create more interfaces with different ways to organize and/or access the data. First up is your common scatterplot by single age years. The default view is for all of Canada, both genders. You can see the bump that is the baby boom now in their mid-50s to late 60s, hitting 70. That break in the smooth curve at 70 was 1946, after all the soldiers returned home and people started having babies again. The war ended in late 1945 so give 9 months for birth and you got the boom in 1946 that is a massive jump from 1945. If you...

You can find average values of various populations' height, weight and such, but that doesn't give you any idea about the distribution of those measures in the population. If you were to compare yourself to them, the best you could do is to see if you were higher or lower than the average (mean, possibly median if given). You could also do the difference in your measurement to the average, but doesn't give you much of an idea what portion of the population might lie between you and that average. The Canadian Health Measures Survey (CHMS) measures and surveys thousands of Canadians on some physical measures and health determinants, and reports it in various percentiles of the Canadian population. That is, in addition to an average (mean), they also give you values that have 5% of the population below it, as well as 10%, 25%, 50% (median), 75%, 90% and 95% of Canadians below it, with some small margin of error. The CHMS also did it for various demographics of gender and...

Please note the following is my work and has not been validated by anyone. That's the nature of things when people do things with public data. However, I take great pride in work I do in my name that I don't do it recklessly, so I had used extensive systematic checks using Excel formulae to make sure nothing got inadvertently changed. I also didn't waste a lot of time to do this if I didn't think it had something valuable to offer that little, or anything else, currently out there could do so well. But without being able to give you authoritative validation, I would recommend you use this tool to get what you want to know, then go verify the values before you were to do anything serious with it, if you need some authoritative validation. I have converted the 2015 Canadian Community Health Survey (CCHS) into a report card format, with some graphs showing results for a different kind of visual comparison. I've embedded it below and after all that work, I'm go...

OK. So the first Tableau visualization I got done wasn't anything too thrilling. That's because it was for government work. However, it was with data just two days old, and public data from Statistics Canada that's cumbersome to do analysis on, or even analytics to show what's in there and quickly see what it all means, so there's value in it. StatCan has also never done anything like this publicly with their data, which they should because those CANSIM tables they have are inaccessible in a practical sense to the vast majority of the public. I'm betting the public would love their work a lot more if they visualized all their work to make it interactive and easy to understand like this! Maybe they could hire me to do this full time with all the data they released! :) The 2015 Canadian Community Health (CCHS) Nutrition Survey  seemed to have been one of these horribly complex surveys that will ultimately yield very little useful data unless you really work har...