Final week of training, dashboard week,. Final day of training, day 5.
Today's topic is Bike Counters in Seattle.
Today's requirements, as per Andy's blog: To download the data for all bike counter locations. Then prep and visualise the data.
Bicycle counters are electronic devices that detect the number of bicycles at a location for a certain period of time. (https://en.wikipedia.org/wiki/Bicycle_counter)
They 'track the number of cyclists to measure the need for bike amenities, such as bike parking and understand the need to invest in additional bike roads.' (http://www.bikecount.eu/)
Downloading the data
To download the data for the locations, I went to the webpage (data.seattle.gov) and searched for each of the locations and downloaded the data as a CSV file.
Prepping the Data
I used a formula tool to add the latitude and longitude of each location, so I could plot the location on a map in Tableau. I used a select tool to remove data for pedestrian counts, as I only wanted to focus on bikes. I changed the data types, removed some fields and reordered. I then unioned them into one large table and output the data as a Hyper file.
The Dashboard
The dashboard I created looks at the average number of bikes / hour at different locations across Seattle. I added filter to allow the user to select and view the data for the selected location. The data showed that Fremont Bridge was the location with the highest average number of bikes per hour across all years.
![](https://www.thedataschool.co.uk/content/images/2021/10/Dashboard-1--1-.png)