This weeks Tableau Makeover Monday was a challenge to visualise a small amount of data; two data points – total size of US National Debt versus the rest of the world. The original visualisation can be seen on the visualcapitalist website and also include comparisons of the US$ 19.5 trillion debt to thinks like company sizes, oil exports, cash held, etc. The pie chart works well here and the comparisons give some idea of scale. ...
This weeks #MakeoverMonday was a look at US presidential election forecasting data by Drew Linzer on Daily Kos Elections. The original charts plot the average percentage being polled by Clinton and Trump over time, along with percentage undecided and other (independents). Personally I wasn’t sure I could improve on the existing charts or some of the community versions (loving the tile maps!) so instead I’ve focussed on a different angle – it wasn’t always easy to see at a glance who was predicted to win the election and why. Particularly with the complexity of the electoral college voting system. ...
Having a go at Tableau #MakeoverMonday this week, with a reworking of a FT visualisation of European public transportation satisfaction survey results in 2015. A good opportunity to look into ways to visualise Likert scale survey results, and to practice some table calculations in Tableau! Adding the ranking by country along with an indicator of the number of places gained/lost gives a quick idea of how satisfaction has changed. ...
Leicester City FC defied the odds to avoid relegation from the English Premier League in May. Rock bottom at Christmas and seven points adrift by late March, a resurgence in form saw the foxes to safety with a game to spare. In the following interactive visualisations I look at the club’s results, league position and points over the season, along with player performance data: LCFC 2014/15 Season (mobile version) ...
If you’ve heard the term Moneyball, then you’ll know that in 2002 the Oakland ‘A’s Major League Baseball team began to use statistical analysis to identify and sign undervalued players, in order to compete against their richer competitors. The approach is credited with getting them to the playoffs in both 2002 and 2003 and has since been adopted more widely. In the football world, Brentford FC are reportedly embarking on a similar journey using the data-driven approach proven at their Danish sister club. ...
An embedded, blog and mobile-sized version of the NZ Population map to see how well it works on an iPhone. You can zoom in and out, or choose a territorial authority (e.g. Auckland) to focus in on. See the previous blog post for a link to the full version of the map on Tableau Public.
Map of New Zealand showing “usually resident” population at the NZ Stats area unit level, using data from the 2013 census. The map was produced in Tableau and can be interacted with (zoom in to whichever region you are most interest in, etc.) on Tableau Public. Data sources, the approach used and credits are referenced in the workbook caption.
Following on from part 1, here is an example of using HTQL to pull data from a table on a webpage. We’ll use the Wikipedia list of most expensive football transfers as our source web page. You can check out the list here. On viewing the page and the HTML source you’ll see that the first row of the table is a header row and that the “player”, “from” and “to” columns contain quite a bit of HTML in order to provide a link to the player/team and a graphical link to their country. Our HTQL will need to cut through this to just get the data that we want. ...
HTQL – Hyper-Text Query Language – is a language for querying and extracting content from HTML pages. If SQL is a language to get data from tables within a database, then HTQL is a language to get data from webpages on the internet. It is useful when you need to pull data from the web and there is no web service available to use. An example might be to pull population statistics from Wikipedia. ...
Some screenshots from the recently refreshed Friendly Islands Kayak Company website. The client was keen to refresh the colour scheme, focus in on images on their home page and replace the plain backdrop with one of the home page images.