Hello everyone, we’ve finally reached day 3. For this challenge many of us experienced dashboard block (if that’s a thing). In my case, I had multiple ideas that I was trying to cram into one dashboard, but that obviously doesn’t work as it doesn’t support one main story – this is known as clutter. So, join me through this process to learn how I managed to overcome my dashboard block.
The challenge
Today’s challenge was webscraping an airplane crashes dataset (see below). This meant that we had over 100 years’ worth of crash data, this measured the fatalities, deaths on ground and number of passengers. Our task is to extract and visualise this data. The question is how?
My approach
Upon first glace I noticed that the dataset has over 100 years of crash data, there is a large amount of history that has happened within that period. So, I wanted to combine the two, the struggle then became finding a story between the two. What do plane crashes have to do with something like the Civil Rights Moment? Is there a relationship between the two?
I began to try and combine multiple ideas into one dashboard. So, I wanted to look at the different historical eras, whilst creating a spatial analysis on a map, whilst also joining on a list of aircrafts that had the greatest number of incidents. As you can probably tell, I’m trying to use all my data fields to create a dashboard. But a good dashboard doesn’t need an overload of charts, just a good story.
This is what my original dashboard draft looked like:
Not very clear on the story right.
What I did instead
First, I started with a quick google search to familiarise myself with the history of aircrafts, this wasn’t too intensive, just 30 minutes, just to get some inspirations. Then I found my story. So, I chose to create a time measure of eras, this meant I didn’t have too many dates to work with initially. Then I wanted to have a look at the evolution of airplane safety over the different eras. What were the newest security measures and did this have an impact on the future years? Was it effective? So, let’s explore that story!
The workflow
It was a bit of a challenge getting this data as the website was kept crashing as all 8 of us were trying to download the links in Alteryx. This meant that we kept getting incomplete data. Before we got locked out of the site for hitting the website through multiple devices, one person was able to download and extract the data. Thankfully, we were all able to pass that data around and this meant we all had to perform our own regex and cleaning steps.
Here is a look at my cleaning process to extract the data I required to make my dashboard:
Now that we have covered the workflow, let’s look at the dashboard. The user can select the icon for the specific era and view the technologic advancement for the time and compare that to the following years. Once they compare this, they can then select the bubble to filter the line chart to drill down into further analysis.
This one was definitely a tough one
