Tableau, Travel and Triathlons
This week brings a challenging topic. One that requires all of us to slow down a bit rather than rush to work with the data. Topics that are polarising and/or taboo in society give us analysts an extra bit of responsibility treat the data carefully, check our assumptions and conclusions and be mindful of the wording we use to draw attention to a topic.
Looking at different countries and comparing their numbers I noticed that among all EU27 countries, Latvia was the only one where production from renewables decreased since 2000, while all other countries went to increase their production from renewables.
As we turn over the calendar to 2021, we also kick off another year of #MakeoverMonday. This week’s visualization challenge is about the trail usage of people in the US, measured through observational data in outdoor areas where trails provide access to nature for people across the country.
This week’s design comes from Canva with analysis done in Tableau to show the poor performance of Arsenal FC in the current Premier League season 2020/21
Line charts are easy and quick to create in Tableau and you have great flexibility to move your date fields into any order you choose. That’s how I created this week’s cycle plot for book prices in Germany.
How do you create a true makeover of a viz? Evaluating the existing one, then taking several steps to improve on it is the approach I took this week for come up with my own viz about calories and sugar in breakfast cereals.
A simple bar chart for this week’s #MakeoverMonday about tech companies in Scotland
For week 19 Andy picked baseball data and I’ll be the first to admit that I expected it to not be fun, because it’s a topic I know nothing about and I wasn’t quite ready to spend hours learning about baseball. Until I did.
For this week’s Makeover, Andy picked a dataset that looks at the fiscal health of all 50 US states. Where do different states place in the ranking?
For week 13 we are using a viz about consumer spending by generation, using data that indicates what people spend
