For week 50 of Makeover Monday in 2019, we’re analysing the revenue of America’s biggest fast food chains. Thanks to Andy for finding the viz and the data when all my search efforts resulted in terrible results.
Given the buzz of #data19 last week, we’re working with a small and simple dataset for week 47, so we can all have some extra time to catch up on the things we missed at home.
#data19 has arrived and with it a live #MakeoverMonday session with A LOT of people. We want to use that opportunity of getting everyone in a room with their ideas and skills to tackle a topic that is very relevant today. Literacy and how literacy rates differ across countries, ages and gender.
For week 45, Andy selected a dataset about Las Vegas. It contains a number of metrics, including visitor numbers, gaming revenue, occupancy rates, etc.
There are quite a few stories in the data.
Before winter really takes hold, let’s look at some sunshine hours in cities around the world.
Being a triathlete and a big Ironman Hawaii fan myself, I thought, why not challenge our Makeover Monday community to visualise the medal table for the men’s and the women’s race.
For week 41, Andy chose a dataset about donations accepted by political parties, published by the electoral commission. The visualisation is an interactive Tableau dashboard, but it’s far from best practices and screams for a makeover
There is a dataset we’ve had in our backlog for months and I’m excited that Andy decided to use it for this week. It’s about book checkouts at the Seattle Public Library, particularly those of work by James Patterson.
September 1st is the first day of autumn, meteorologically speaking. So I picked a dataset about how Americans feel about the different seasons.
The original viz and data comes from YouGov.
This week we’re looking at a viz and data collected by Spencer Philips Hey, who brought together years worth of data about clinical trials and all their published details.