Dashboard Week at The Data School is a week was filled with different data challenges. Armed with tools we have learned such as Tableau, Alteryx and Power BI, we are challenged to create a dashboard each day as well as a blog. Follow me through my journey as I dive into this week’s challenge of building creative workflows and dashboards to meet each day’s challenge.

Today marks the first day of dashboard week. Web-scraping day is about finding some data online and web scraping it to build a dashboard in Tableau. This blog will show you the steps I took in tackling this challenge and producing the final product.

Having just enjoyed the 2023 Formula 1 Monza races over the weekend, I immediately knew what I was going to be looking at for this challenge. The data I chose is from the F1 website showing the race results in a table format that I would web scrap and put into Alteryx. The data in this table included the Grand Prix name, date of the race, the race winner, the car, laps raced and the drivers’ best lap time.

Data source: https://www.formula1.com/en/results.html

The first step to this challenge was getting the data was finding what to scrape within the HTML code of the website. As the table format was clean and made it much easier to find where the table is located within the HTML code. The biggest challenge was utilising RegEx to tokenize and parse out the data I needed from the HTML code. To put it simply, RegEx is a way to describe patterns you want to find in a bunch of text. The key thing I learned was simplifying the RegEx to be as readable as possible. This would help us troubleshoot by being able to more easily identify problems in what we had written.

To enrich the current data set, I searched on Kaggle additional data. However, due to the difference in data structure of the original web scraped data, joining the data created multiple issues and roadblocks in this challenge. As a result, I ended up just using the original web scraped data.

This lead me onto the next roadblock which was finding a story with limited data. I challenged myself to create an interesting story from only using 6 fields of data with 4 being dimensions and 2 being measures. Given the small data set, I thought the best way to get the most out of the limited data was to create a table and ask questions about the relationship between the variables. If you’re interested in learning more about this Insights Matrix, you can read about it in my blog post.
Once I had a list of the question, I jumped into Tableau and made some quick charts to see if I could find anything interesting. Of the insights I found, I then tried to dig deeper by merging questions together to produce a dashboard.

The dashboard building process was relatively simple and involved covering 3 main areas:

  1. Rundown of races
  2. Winning racers by team
  3. Grand prix race winners

While building this dashboard, I sought to create something clean and easy to understand. I took into consideration using the Formula 1 red colour to emphasise certain parts of charts. I also implemented some dashboard interactivity and filtering options to give users the option to explore the data more. Lastly, the over time bar charts were very wide so I opted to use navigation buttons to give the wide bar charts more breathing room as well as aesthetic reasons.

My final dashboard can be viewed here on my Tableau Public.

The Data School
Author: The Data School