It’s 2020 and everyone is reflecting on last year and making goals for this year. I didn’t do a lot of things well in 2019; namely, blogging. Now any reason I give will be (or sound like) an excuse so I won’t bother. I hope to viz and blog more this year but I also want to do more travelling, spend more time with my loved ones, volunteer more and take time to care for my health so who knows what will happen – all I can say is I will try my very best!
I thought my Best of DS11 blog would be my final blog post on the Data School website but no, I have one quick blog post left. Set Actions. They’re new and exciting, right? Today at the Data School, Harry of DS11 taught us (and the coaches) set actions as he was assigned to teach the public this topic a few weeks ago. He has two blog posts on set actions which will delve much deeper than my blog post right now, check them out here and here. Andrew has also written one on proportional brushing here.
In this blog post, I will show you how to use set actions to change the colour scale of your filled maps depending on the locations you choose to lasso.
Figure 1 below shows a map of Europe with sum of sales on colour (this is EU Superstore). The first step to creating this set action is to create a set. Right-click on ‘State’ which is every region or some sort of chunk within each country and click Create> Set. Select all the “states” and call the field ‘State Set’.
Two major contenders in the ring tonight: new but developing at light speed, Tableau Prep and tried and trusted, Alteryx Designer.
Who will win this time after a draw in the last Prep Off? Watch the replay of Round 1 here.
How do these two softwares compare when cleaning an Excel spreadsheet with 182 fields? The chosen data features the table seen in Figure 1. This data was used in Makeover Monday Week 2 2019 (after it was cleaned, of course). Download the Excel file (Freedom of the Press) and follow along with me.
Today DS11 and DS12 were treated to a talk from Simon Beaumont about data architecture, enabling customers to understand your dashboards, how to make your workbooks easy for others to pick up and more. In this post, I will go over a few things about organising your Tableau workbook Data Pane to make it easier for others to understand.
Why organise your Data Pane?
If you are working in an organisation with multiple analysts and/or people who you will hand over workbooks to, you want them to be able to understand your workbook quickly. It is better to avoid future analysts having to spend hours picking your workbook apart to understand what a calculation does or what this set is used for, etc…
Also, if you publish your work to Tableau Public, you might want to make the workbook easy to understand in case someone downloads it to learn a technique you demonstrated.
Additionally, it may help you later down the line. If you have to refer back to an old workbook and realise you don’t understand how you got to what you did, that would be a pain.
As you can see, there are numerous reasons why one should organise their Data Pane.
Last month, DS11 taught the public Tableau and Alteryx and this month, we are conducting webinars teaching the same content. Check out our meetup page for more details on upcoming webinars and events!
For both of these lessons, I taught Alteryx Data Prep. If you missed my webinar, it was recorded and will be uploaded so I will update this post with a link later.
In this blog post, I will go over my teaching experience and some top tips from myself and from the beautiful people at the Information Lab.
My Teaching Experience and Top Tips!
To prepare for teaching, I sought advice from the wealth of experience of the Information Lab consultants. The advice I received was super useful and helped me to prepare my lesson plan. Figure 2 below shows all the teaching tips I gathered categorised into four sections.
Tableau’s Analytics pane allows you to slap an average line onto your view. Drag, drop, done?
Not quite. In this blog, I will show you an example of when the average line Tableau creates for you may not be doing what you think it does.
So Figure 1 below shows a vertical bar chart with the height of each bar indicating the number of customers that fall into each number of orders bucket. For example, 134 customers have ordered 5 times; 1 customer has ordered 17 times.
For Dashboard Week Day 4, we looked at Seattle cycling data (see my blog here). I decided to incorporate Viz in Tooltips to enhance my infographic (Tableau Public here) and give the reader more context (see Figure 1).
Now I don’t often use Viz in Tooltips because I’ve always had issues with filtering, this was again true for this viz. This issue is when the filters in the parent sheet applies to the tooltip sheet. I want my tooltip sheet to be static and unaffected by the filters in the parent sheet but for some reason, my tooltip sheet kept being filtered. In this post, I go over how to overcome this common Viz in Tooltip issue.
It’s day 4 of dashboard week and I am starting to fatigue. No matter! We push on.
Today’s dataset counts the number of cyclists riding through the roads of Seattle. Potentially very interesting for a Seattleite (/satellites) or a keen cyclist. For me, a person who learned to ride a bike at 12 and has hardly touched one since, it didn’t excite me. The data is as shown in Figure 1 below.
Looking at this dataset didn’t immediately give me ideas (well.. besides a map. But I’ve overdone that). So I decided to make a colourful infographic-type viz to make the cycling data pop. I did a quick google search on cycling infographics for inspiration and came across this one:
My first day of Dashboard Week! Yesterday the rest of DS11 enjoyed vizzing >200M rows of data about snow ploughing while I watched from home (hurray for a coincidental day of annual leave).
This morning I was rested and ready to take on the challenges of the week. Today, Andy set us the challenge of analysing New Orleans Police Department (NOPD) body-worn camera data. Now, this would have been super fun and interesting if there was information on the crime that was being recorded, whether this led to an arrest, etc.. but no. As you can see from Figure 1, the data contained information on the times body cams were used, where, how long each video is, when it was uploaded to the system… not exactly the juicy stuff.