Earlier this year the pudding published an excellent analysis into the myth that various events were a trigger for mini baby booms. The analysis was based on CDC data on natality in America. Fast forward to August and the data set was selected by Andy for week 33 of Makeover Monday. ...
This week a makeover of an article and Tableau chart about sanitation in rural Indian schools, based on data from the ASER Centre. Here is the original chart posted by Eva and Andy: Made over A tile map seemed like a good way to retain some of the benefits of the map whilst mitigating the downsides. It was an interesting exercise to make a tile map for India and the end result still retains some similarity to an outline of India. The addition of imagery featuring the Indian flag reinforces the fact that the viz is about India, and I like the analogy of a child putting their hand up to ask to go to the toilet!. ...
Back into it with a revisualisation of a 2015 Southeast Asian Games infographic. A simple and engaging infographic telling the history of the games. The data provided was a little different; only covering 2007 to 2015. I’ve focussed on a medal table for 2015 and area chart showing medal count trends over the period. Firstly this keeps things simple, secondly it was something I could compare against medal tables on Wikipedia. The reason I wanted to be able to sense check the data against something was due to the structure. For team events both the team medal and individual participants were included so some extra filtering was needed and I wanted to check I had that right. ...
I was on holiday for week 27 to 30 so caught up with these four later in the year… Week 27: Tourism in Berlin and Brandenburg For week 27 a makeover of a filled map showing visitor stats for Berlin and Brandenburg. I’ve retained the filled maps but focussed on an angle that interested me; whilst Berlin ranks top for both number of visitors and total number of nights in all years, when you look at average nights per visitor it is one of the regional districts that usually tops the list. Check out the interactive version here on Tableau Public where you can look at different years, and explore how the figures differ for domestic or international tourists. ...
It’s the half way point for Makeover Monday in 2017: 26 charts selected by Andy and Eva, 26 makeovers submitted and 26 blog posts written. It’s been a tough challenge for me to produce a visualisation every week and tougher still to write about each one. However, both of those aspects have been enjoyable, and the practice and reflection has really helped me get more out of Tableau in my job. I’ve had a few submissions selected in the weekly round up and one was selected in a #VizForSocialGood project for use by Inter American Development Bank. The way the Makeover Monday project works this year with the weekly wrap up lessons and the community input has made a huge difference to me. If you’re reading this, chances are you’ve helped me so thanks! ...
More Exasol-based data in Makeover Monday week 25. 200 Million+ ozone air quality readings from the EPA and a goal to make over a multi-year air quality tile plot on the EPA website. I spent way too much time exploring the data so only had time for a quick make over in the end and this short blog post. Checkout some of the other participants efforts on twitter or wait for Andy and Eva’s weekly summary to see some really cool visualisations. ...
Week 24 of Makeover Monday and a fascinating data set of art work in the Tate Collection. Nominally we’re making over charts from an article by Florian Kräutli such as this one: Thoughts on the original charts The chart highlighted to Makeover Monday participants was a pie chart showing the proportion of works in the collection by Turner versus all other artists. It works well to illustrate a key point about the data and explain why the author excluded Turner’s works from a number of their beautiful visualisations; when Turner’s works are included they skew the data to the point where other artists can’t be seen. The Tate Collection includes the Turner Bequest of roughly 30,000 works of art. Many of these art works are unfinished or preparatory sketches – e.g. each page in a sketch book is counted as a separate work. Angie Chen’s submission explains this nicely and is well worth checking out along with the original article. ...
Makeover Monday was live from TCOT in London this week and it was amazing to see some of the output produced in just one hour! The challenge was to redo an already great graph from FiveThirtyEight on US National Park popularity: Thoughts on the original chart I like the original chart – actually the whole article is really interesting and the charts engaged me throughout. The chart focussed on above shows the ranking nicely, but not the actual number of visitors over time. So we don’t know how much more popular Great Smoky Mountain has been than Rocky Mountain or Yosemite. It’s hard to follow some of the threads without interactivity – although the colour coding of some of them certainly helps. You also can’t tell which states the parks in question are located in. ...
Just a quick write up this week. Eva selected a map from Knoema showing what proportion of each country’s population had internet access. I quite like the interactive map, but it suffers from some problems common to filled maps. Eva and Andy have talked about the use of maps a few times in their weekly write ups so this week I thought I’d explore the issue in a bit more detail. ...
According to data released by Britain’s Office for National Statistics, and a recent BBC article, Brits drinking habits are changing. Are the British falling out of love with booze? The data and graphs involved were the topic for Makeover Monday this week. Thoughts on original charts The data set provided focussed on the first section and chart in the article. It’s a good simple bar chart clearly showing the changes in certain categories between 2005 and 2016. What we can’t see is the pattern in the intervening years. We also cannot see the parts that make up the whole in any given year; we can see the proportion drinking at least once during the week before the survey, and the proportion that do not drink at all, but there is no mention of those that drink but not during the week in question. Finally the response of drinking on 5 or more days of the week is presumably a subset of those drinking at least once during the week. The bar chart does not represent these sets fully. ...