In Week 6 we challenged the community to work with a rather large dataset and create a makeover of a couple of simple line charts that visualised taxi trips and fares for Chicago from 2013 – 2016.
We provided a data extract for 2015/2016 data as well as the full dataset using EXASOL as the back-end database. To be honest, I was completely blown away by the interest from the community in accessing ALL the data and using the database as a playground to analyse 105 million taxi trip records. At the time of writing we had over 180 registrations, which is about 150 more than I expected. Well done everyone and thanks for getting involved in a bit of a novel challenge for Makeover Monday.

Did we see any issues this week? Well, nothing glaringly obvious stood out when it comes to the analysis of the data. It helped that the data itself was pretty straight-forward. We limited the columns to only those that were useful for the analysis (removing empty columns and additional ID fields) and the metrics were easy to understand (fare, tips, extras, toll charges, number of trips…).
One challenge may have been that people who accessed the whole dataset with a live connection often tried putting every single taxi trip on one map. Not a good idea :-), it will take an hour or so for Tableau to render 105 million marks on a map, so my advice is that you filter the data first when it comes to the visualisations. For example, pick a single day (Christmas day, New Years eve, etc.) and start from there.

What I really enjoyed seeing was people going through iterations with their vizzes, trying one way and taking feedback on board to produce an even better visualisation afterwards.
I certainly noticed a step-up in the quality of vizzes and people taking the opportunity to practice crafting a story around their charts, which is great. There were sporting themes, tipping analysis, people focusing on geographical areas and particular holidays or events.

It was really difficult to pick favourites this week and I have decided to make it a little easier for myself by having 2 categories: Live data and extract vizzes. The extract category contains vizzes that were built on the extract we provided with 2015/2016 data, while the live data category is for everyone who used ALL the data in their makeovers.

As a small incentive and as mentioned in the announcement blog last Saturday, the favourites in the live data category will feature on EXASOL’s Tableau Server, visible on the EXASOL website so that viewers can interact with the viz. We will also produce a webinar with those authors, so well done to everyone who took on the challenge.

So let’s look at this week’s favourites, starting with the live data category

Author: Adam Crahen
Link: Dear Data Duo

What I like:

  • Adam went all out and experimented with the whole dataset, creating different charts to tell a story
  • the ‘Beating Heart of Chicago Taxis’ is a really cool animation that shows the ebb and flow of taxi traffic
  • minimalist colours let the story speak for itself
  • the design is neat and uncluttered and the viewer is guided by annotations and commentary
  • data source is referenced clearly

Author: Michael Mixon
Link: Tableau Public

What I like:

  • beautiful design with nice colour choices that are easy on the eye but still relate to the ‘Taxi’ topic through the use of yellow hues
  • use of different techniques including floating sheets, transparency, spark lines, filters, parameters, different types of charts – Michael used them all and very effectively combined them in a great layout that only reveals its complexity once you grasp all the components involved
  • the highlight table benefits from the additional labelling for highest and lowest number of trips and together with the bar charts gives me a good idea of when Chicago taxis are busiest
  • data source is referenced clearly

Author: Jamie Coles
Link: Tableau Public

What I like:

  • this was Jamie’s first Makeover Monday submission – and he set the bar really high!
  • I love the mood of this viz, with the skyline at the top and and the yellow being bright but not offensively so
  • the map is stunning! It looks like an image but is a worksheet that has been included effectively
  • the highlight table works really well and I like that the grey comes up again as a colour in the filters
  • overall the design is neat and engaging. Using a question as a worksheet title inside the dashboard makes me curious to find out more
  • data source is referenced clearly

Author: Curtis Harris
Link: Tableau Public

What I like:

  • Curtis just knows what to do with Taxi data it seems 😉
  • love the colour scheme. It is unexpected for taxi data but given the focus of his story it worked really well and the colours carry the story effectively through the entire dashboard
  • I like the transparent band with the colour legend going across the maps. Very clever!
  • the heading updates when you change the date filter, so YOU get to drive the story
  • data source is referenced clearly

Author: Pooja Gandhi
Link: Tableau Public

What I like:

  • Pooja’s story provides insights into the taxi industry in Chicago more broadly by highlighting key metrics over time
  • use of a parameter to allow me some choice in what I’m looking at (fare vs trips vs miles), which brings this story back to the original viz that looked at fares and trips
  • the map is stunning
  • simple colours that are consistent throughout
  • the highlight table is very easy to understand with the standard calendar layout
  • neat formatting
  • data source is referenced clearly

Following are my favourite extract vizzes. These authors used the 14 million record extract we provided, which included data for a single pick-up area (Near North Side) from 1 Jan 2015 to 31 Dec 2016.

Author: Roberto Reif
Link: Tableau Public

What I like:

  • Roberto found a story and ran with it, showing us how one could earn $25/hr in tips by driving a taxi
  • I like the design, it’s very ‘Taxi’ but he made it his own by using a specific font
  • the call-outs enhance the story and tell me why I should care and continue to read
  • data source is referenced clearly

Author: Josh Jackson
Link: Tableau Public

What I like:

  • it’s different! Josh created a mobile viz with the ‘customer’ in mind, i.e. the taxi companies using his report to assess their performance
  • the colours work well, they’re subtle bit still distinct
  • Josh tweeted that he didn’t have enough time to finish the viz, but he posted it anyway and I like where he got to, so I hope we get to see many more from him in the future

Author: Hendrik Kleine
Link: Tableau Public

What I like:

  • Hendrik took a minimalist approach, submitting a nice and clean design without any unnecessary lines or borders. I like his choice of colours that are used effectively throughout the viz
  • the area chart at first glance looks like a background image but doesn’t even need an explanatory title to tell the story. Yes, I have read the article, so I know what data Hendrik is working with, but from the chart I can still tell that there is something in decline
  • the call out at the bottom left immediately tells me that overall taxi rides are down, and I can link this back to the area chart showing me a decrease
  • I like that the key statistics and the callouts below them look harmonious over all but still each have their own focus (rather than each being a comparison against prior year)