Day 3 of dashboard week and we’re still powering through. Today’s assignment was to web scrape data off of Numbeo’s website, so I first took the crime index data (which was the requisite data) and added the quality-of-life index data to it. These can be found at Crime Index by City 2024 Mid-Year (numbeo.com) and also at Quality of Life Index by City 2024 Mid-Year (numbeo.com).
This was achieved through the web scraping process in Alteryx, followed by joining the two tables together once the data had been properly retrieved. Below is my workflow detailing this process.
I then crafted my dashboard from this data, keeping in mind the fact that our dashboards in dashboard week need to be more explanatory than exploratory. Below is how my dashboard ended up looking.
I made sure to put more writing so viewers can understand any nuances in the data and how the dashboard works, as well as what exactly the index scores are and what the numbers actually mean. The first visualization is simply a top (or bottom depending on which you choose on the parameter) 10 of cities based upon the index chosen from the 9 total indexes available. While some are positive and negative, I mention in the text of notes, as well as in the pink symbols, that the lower the negative index value, the better it actually is.
Further down, there is a box and whisker plot for positive, negative, and overall index scores, which are just the combination of positive or negative index categories (or both altogether) and then divided by how many index categories there were. The tooltip shows either how the city changes over time (for overall index) or the distribution of positive or negative index categories. When you click on a city in the plot, you can see its’ location on the world map, or if you’re clicking on the overall index plot, you can see both positive and negative index distribution bar charts for the city.