Photo by James Wheeler | Free License
The purpose of this project is to create a Toronto real estate analysis dashboard to facilitate understanding of Toronto's real estate market for the purposes of making investment decisions. The data sources utilized in this project are from Toronto's neighbourhood census data gathered from the years 2001, 2006, 2011 and 2016. Toronto neighbourhood coordinates data is used for plotting Toronto neighbourhoods into a plotly express mapbox visualization.
The data utilized for this project was retrieved from the following websites:
It is recommended to install the PyViz visualization package to ensure everything runs as expected. PyViz is a Python visualization package that provides a single platform to access multiple visualization packages, including Matplotlib, Plotly Express, hvPlot, Panel, D3.js, etc.
Video Guide for installing PyViz: PyViz Installation Video
In order to run both notebooks panel and its plotly extension, plotly express, hvplot, matplotlib, pandas, pathlib and dotenv libraries are required. A mapbox API key is also required to render the plotly express mapbox visualization.
To register for a public mapbox API key visit this sign-up link. Detailed information on how Mapbox can be used to generate plots can be found on Plotly's documentation page.
In order to run the the panel dashboard via your local machine, follow the the steps below:
- Open your CLI
- Navigate to the location of this cloned repository
- Execute
conda activate pyvizenvto load recommended environment - Execute
panel serve dashboard.ipynb - Copy & paste the localhost address from your CLI to your browser.
Once loaded in your browser, the dashboard will appear as the screenshots below.
