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.
At the Data School, we are constantly challenged and pushed with limited time projects. This is to develop our time management capabilities, to teach us to set realistic goals and to give us the confidence and knowledge that we can do it.
So, what have I learned? In this post, I will go over my top tips on how to approach a time-limited project.
Step One – Finding your Story
You have been inspired to start a project on a certain topic or you have been assigned a project by your employer. Where do you start? You have to find your story.
If your data has already been given to you, you can begin exploring the data. Identify the interesting parts of your data or find an issue you would like to investigate. Be careful not to spend too long exploring the data and deliberating on a story. Make note of what’s interesting and try to settle quickly on the story you would like to tell. I recommend writing down your story as it will help you keep to the topic and avoid wasting time by straying.
For my TIL Christmas Song viz in Figure 1 (see it here!), I embedded a Spotify playlist so you can listen to the music in the viz as you explore. Embedding a Spotify playlist/ track/ album can be great for adding another dimension to your vizzes. For example, they can supplement a viz about podcasts, movie soundtracks, or other musical topics.
Doing this though, was not as easy as I expected. I expected a simple ‘copy playlist link’ from Spotify and paste into the Web Page object on Tableau Desktop (Figure 2) and boom! Embedded playlist. Nope.
Did you know you can make your own colour palettes for Tableau? This is great for businesses and individuals who want to incorporate branding into your dashboards and to ensure regularity of colour in dashboards across your company.
So, how do you make one?
Navigate to ‘My Tableau Repository’ on your computer and open the Preferences.tps file in a text editor of your choice.
If you have never added any custom colour palettes before, your preferences file will likely look similar to Figure 1.
Two major contenders in the ring tonight: new kid on the block, Tableau Prep and reigning champion here at the Information Lab, Alteryx Designer.
How do these two softwares compare when cleaning two Excel sheets (within the same workbook)? The chosen data features the table seen in Figure 1. The data includes merged cells, totals, unnecessary content, dates in a row and times in a column, plus its in German! Download the Excel file (2018-09-18 Hamburg) and follow along with me.
Among the many things we learned during our first official Tableau Server lesson with Jonathan MacDonald, we learned the importance of an often underutilised Server feature, custom view.
In this post, I will go over what custom views are, why they’re super useful aaand hopefully by the end of this post convince you to use them more!
What are Custom Views?
Custom views are like they sound. They are snapshots of a dashboard or sheet that you, the user, choose and save for quick future reference. Custom views are especially useful for dashboards or sheets that have lots of filters and drilling down.
NOTE (edit 10/11/18): Custom views can only be created by those with an Explorer license, but created custom views can be viewed by those with Viewer licenses. Thank you Chris Love for this info!
Let’s try an example. I will be using my UK House Prices viz (data source: Exasol) which I have uploaded onto Server.
Since my last blog, I have used Tableau Prep 2018.2 to clean five different datasets so I think it’s a good time to discuss the good, the bad and the ugly of Prep…
As with Tableau Desktop, Prep is pretty. Compared to Alteryx, it looks modern, clean and is just overall, aesthetically pleasing. The user interface is friendly and intuitive. Who doesn’t love a good ol’ drag and drop? I mean, we love Tableau Desktop right?
Unlike Alteryx, Prep lets you actually interact with your data as you would in Desktop. I personally love being able to do this.
Tableau Prep has some great built-in features for data cleansing. It’s easy as pie to split fields as you would in Alteryx with Text to Columns. It’s easy to remove whitespace and change the case of your fields (note: you can only change the case of the whole string, not title cases).
Another super useful function is the Pronunciation Group and Replace. Take a look at Figure 1, you can see that ‘Growlith’ should be spelt like ‘Growlithe’. You could click on ‘Growlith’ and type the ‘e’ manually or… you could use Pronunciation as seen in Figure 1. Doing this groups the two terms together under ‘Growlithe’ (denoted by the paperclip icon).
Amazing right? Yes, but there are limitations. This segways us nicely into…
Tableau Prep version 2018.1.1 was released in April this year. Six months on and five versions later, Emily Chen introduced DS11 to Tableau Prep 2018.3.1.
My first thoughts? Its user interface is modern and intuitive with some great functions but there are some limitations. Tableau Prep won’t surpass Alteryx in power at the moment but definitely has potential!
Being a new software, many of you probably haven’t given it a go yet. In this guide, I will run through everything you need to know to get started! See my previous posts on getting started with Alteryx (link) and Tableau Public/Desktop (link).
Now, if you haven’t got Tableau Prep downloaded yet, you can get the free trial here. Otherwise, start up Prep and let’s get started!
The first thing you’ll see when you start up Tableau Prep is something like Figure 1.
Ah… The much-awaited Part Two of my ‘Making Every “Show Me” Chart From Scratch” series (see part one here). Thank you for following my series so far! To recap, we have so far gone through text tables, heat maps, highlight tables, symbol maps, filled maps and pie charts.
In this post, I will go through how to create a bar chart, stacked bar chart, side-by-side bar chart, treemap, circle view and side-by-side circles. For this series, I will be using the “EU Superstore” dataset found in My Tableau Repository.
Let’s get started!
Horizontal Bar Chart
Tableau’s Show Me bar chart is known as “Horizontal Bars”, though really, bar charts can be both vertical and horizontal. I will show you both. For this bar chart, I want to look at the profit for each sub-category.
Drag the measure “Profit” to the Columns Shelf and the dimension “Category” to the Rows Shelf. As we want to look at sub-category, we can either drag the dimension “Sub-Category” to the Rows Shelf next to “Category” or the quicker way: click the little plus sign shown in Figure 1. This expands category to its next level of detail, sub-category. This only works because sub-category is below category in its hierarchy. If these dimensions aren’t in a hierarchy together, the regular drag-and-drop works too.
Tableau has a super useful “Show Me” function which allows you to choose from 24 chart types based on dimensions and measures you select. This is a brilliant feature for beginners. However, what if you’re a little bit more experienced and want to know how to make these charts from scratch? Or even if you’re a beginner who doesn’t want a shortcut? In this four-part series, I will go through how to create all 24 “Show Me” chart types.
For this series, I will be using the “EU Superstore” dataset found in My Tableau Repository. In this post, I will go through how to create a text table, heat map, highlight table, symbol map, filled map and pie chart.
Let’s get started!
Text tables are exactly like they sound. A table of values similar to what you get in an Excel spreadsheet. For this text table, I would like to look at how much each sub-category of products have made in sales.
From the Data Pane, drag over the dimension “Sub-Category” over to the Rows Shelf (Figure 1).