Another long night on dashboard week. For those who are not familiar with dashboard week, the challenge is to create a dashboard within a day using the data set that was provided. Today is day 3 and the data was about the England House Price Index.
The Data included the following information
- Home prices and index by type
- Average house price and index
- Sales volume by London borough and England region
- Spatial for England region and London boroughs
In addition to the data set provided we had to find extra data to supplement.
The dataset is relatively easy to use. Everything is separated into different tables/sheets/files, and they can all be connected using Borough’s code. After some research and based on my own experience, I decided to use the Crime dataset that was available online as a supplement to understand if a House Price increase might have an impact on crime decrease/increase in London Borough.
Data Processes with Alteryx and Workflow below
Now that the data is ready and before doing anything I need to do a few connections on Tableau with the Spatial file and create a relationship with the Crime. I didn’t join Crime and House price data as it was duplicating the data (the crime was at year level and House data was at month level)
Tableau Connection
I can now start working on Tableau to analyze the data and prepare a dashboard.
Dashboard
Some of the insights I found were
- While Prices increased considerably from 1999 to 2016, crimes also decreased.
- Highest decrease in crimes is mainly around suburbs with avg house prices strong increase. Example with Westminster and Kensington. Those suburbs were among the highest crimes