For this weeks’ #MakeoverMonday Eva treated us to a data set on potato production in the EU. As a vegan living in Germany I think Eva has a thing for potatoes 😉 .

The original visualisation was a basically just a data table with a few graphs included in the main report by Eurostat which can be found here. I’ve also included an extract of the report below:

potato-eurostat

What do I like about the original?

  • The information is presented in a clear format.
  • The table includes overall totals for the EU at the top which is good for reference purposes.
  • The colours are clean and not too busy.
  • The report itself is very detailed and is summerised into sections which makes it easier to digest.

What do I dislike about the original?

  • Since the data table includes numbers only it is hard to see the key information without analysing the data for some time. It would have been better if they had included some colouring or highlighted the key numbers in some way.
  • The main report includes some donut charts (like the one below) which include too many segments and colours (in my opinion).

Potato Donut.PNG

I had a few ideas about what I wanted to produce this week so I decided to sketch them on paper first. I always find this a useful process as it gives you a starting point before beginning anything in Tableau. At this point I knew I wanted heat maps to show the price/harvested production by country over time. I also thought about including some sparklines, a scatter plot and a few additional graphs. My initial sketch turned out like this:

potato-viz-drawing

I started in Tableau by looking at harvested production by country. I decided to display this in a bar chart rather than as a sparkline; my thinking being that the heat map would show changes over time to some extent. I initially created two sets of bar charts and heat maps; one for harvested production and one for selling price by country. However, I thought it would look cleaner, save precious dashboard space and aid comparison if I created a back-to-back bar chart/pyramid chart (I’m not exactly sure what you call these) to show harvested production vs. price by country. I then put the heat maps beside this to show changes over time.

I initially left some space a the bottom for additional charts. I was hoping by this point I would have found a story in the data I could focus on but unfortunately nothing specific was standing out to me. Instead I decided to look at the correlation between harvested production and selling price. Having studied economics at university this analysis brought me right back! This is the kind of topic used when talking about the laws of supply & demand and how these determine the price. As any economist will tell you when supply increases, prices fall which in turn increases the demand (as the product is cheaper thus more affordable and accessible). This is certainly the case for the potato industry too! It turns out were poorer harvests in 2012 & 2013 due to flooding which resulted in higher potato prices.

My final graph looked at the correlation between the average yield  and the average harvested production for the 2010 – 2016 period in a scatterplot. I thought there would be a direct correlation between the two but I was surprised to see this isn’t always the case. Some countries (such as Denmark) have a high yield but a lower harvested production. Notice the potatoes on the scatterplot? Since this viz is about potatoes I couldn’t resist using a potato shape as the mark 🙂

Now my graphs were ready I decided to choose a colour scheme. I wanted to create a new colour palette especially for this viz. I have been doing this quite a lot lately and enjoy experimenting with different colours. I started by looking for pictures of potatoes online for some colour inspiration. Unsurprisingly this wasn’t very interesting so I Googled ‘potato harvesting’ instead. That was how I found this picture:

potato-harvest-header-bdn-data-s3-amazonaws-com

It’s actually a picture from a daily newspaper in Maine, USA but never mind (original here). I like this a lot; the autumn tree colours are beautiful and I like how there is a lot of space at the bottom where the field is which would make it easier to use as a header. I decided to upload the picture to Canva to build a header for my viz. I have been using Canva for various projects ever since I first heard about it during Jewel Loree’s ‘Pimp my Viz’ talk at #Data16. It’s so simple to use and the results are excellent.

Before moving onto Canva I created a colour palette in Tableau using this website to find the hex codes from the colours in the harvest picture. Here are the codes for my colour palette in Tableau if you want to use it yourself:

<color-palette name=”Potato Harvest” type=”regular”>
<color>#A45D31</color> <!– Dark Brown –>
<color>#BA8559</color> <!– Light Brown –>
<color>#8A1D00</color> <!– Deep Red –>
<color>#EAB229</color> <!– Mustard Yellow –>
<color>#7D7129</color> <!– Brown/Green –>
<color>#D85121</color> <!– Burnt Red –>
<color>#BE9D5A</color> <!– Wheat –>
</color-palette>

Now I had my colour hex codes I could use these in Canva also. When creating a header for a viz in Canva I tend to use the blog title design option. This creates a wide, narrow banner which is perfect for a viz header. I don’t usually use the pre-set options (I prefer to work from a blank canvas) but I found this one this week which seemed appropriate and inspired the title of my viz:

Canva.PNG

After messing around with fonts, colours & filters I ended up with this:

cream-of-the-crop

Here is my final viz. You can also use the interactive version on Tableau Public here.

cream-of-the-crop-mm-wk8

Thanks for reading.