Giter Site home page Giter Site logo

adamgulyas / toronto-housing-analysis Goto Github PK

View Code? Open in Web Editor NEW
0.0 1.0 0.0 14.46 MB

Data analysis of Toronto real estate values over the past fifteen years.

Jupyter Notebook 100.00%
data-analytics data-science data-visualization real-estate toronto

toronto-housing-analysis's Introduction

Toronto Housing Analysis from 2001 to 2016

Usage

You must have Anaconda and Jupyter Lab installed and be running Python >= 3.7 to run this dashboard.

  1. Set up a new Anaconda environment called pyvizenv.

    conda update anaconda
    conda create -n pyvizenv python=3.7 anaconda -y
    conda activate pyvizenv
  2. Install environment dependencies.

    pip install python-dotenv
    pip install numpy==1.19
    pip install matplotlib==3.0.3
    
    conda install -c conda-forge nodejs=12 -y
    conda install -c pyviz holoviz -y
    conda install -c plotly plotly -y
    conda install -c conda-forge jupyterlab=2.2 -y
  3. Install the Jupyter Lab extensions.

    jupyter labextension install @jupyter-widgets/jupyterlab-manager --no-build
    jupyter labextension install jupyterlab-plotly --no-build
    jupyter labextension install plotlywidget --no-build
    jupyter labextension install @pyviz/jupyterlab_pyviz --no-build
  4. Build the Extensions.

    jupyter lab build
  5. Ensure the successful installation of the dependencies by finding them in Anaconda.

    conda list nodejs
    conda list holoviz
    conda list hvplot
    conda list panel
    conda list plotly
  6. You will need a MapBox API key to get map data. If you don't have a MapBox API key, here are instructions on how to get one and set it up as an environment variable.

  7. Run all cells in Jupyter and view the dashboard in the browser by executing the final cell dashboard.servable().


Results

Average House Values in Toronto Overall

Use the map plot to get a birdseye view of the cost of Toronto neighbourhoods. The larger and brighter the dot, the more expensive the neighbourhood. This plot indicates that the most expensive neighbourhoods are near the downtown area.

mapbox

Dwelling Type Units per Year

The sum number of dwelling type units per year. Dwelling values (represented by the bars) change as the years go on, indicating which dwelling types gained or lost popularity.

bar_chart_1-4


Average Shelter Costs in Toronto Per Year

Comparing the cost of owning a dwelling versus renting one. Notice that although owning a house has been more expensive, the value of houses over doubled.

line_chart_1


Neighbourhood Analysis

Use the dropdown menus to look at data for individual neighbourhoods. The data varies widely between each neighbourhood.

line_chart_4

multi_bar_chart


Average House Values in Toronto by Neighbourhood

The average house value in each neighbourhood within each time period. Hover over the bars to view more info.

row_facet


Top 10 Expensive Neighbourhoods Overall

The top 10 expensive neigbourhoods to live in overall between 2001 and 2016.

bar_chart_5


Top 10 Expensive Neighbourhoods by Year

This sunburst chart displays the top 10 expensive neighbourhoods to live in between 2001 and 2016. Darker colours indicate higher value.

sunburst

toronto-housing-analysis's People

Contributors

adamgulyas avatar

Watchers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.