ONGOING
Geocluster: using clustering to get better insights on Berlin and its social context
This is a project I created in order to enable an easier access to the data we collected for our final project at Le Wagon's Data Science Bootcamp.
The result is this webapp, where you can plot the distribution of 100 features on Berlin's social and infrastructural landscape - and use clustering to get more insight on how they interact with each other. You'll find more information on the method employed in the description text.
The data was obtained from Berlin Open Data Platform and Openstreetmap and aggregated to the level of the 542 Berliner Plannungsräume (planning areas), the smallest statistical areas on which social data is publicly available. 6 areas were excluded of the analysis due to a too little amount of observations.
The initial setup.
Create virtualenv and install the project:
sudo apt-get install virtualenv python-pip python-dev
deactivate; virtualenv ~/venv ; source ~/venv/bin/activate ;\
pip install pip -U; pip install -r requirements.txt
Unittest test:
make clean install test
Check for TaxiFareModel in gitlab.com/{group}. If your project is not set please add it:
- Create a new project on
gitlab.com/{group}/TaxiFareModel
- Then populate it:
## e.g. if group is "{group}" and project_name is "TaxiFareModel"
git remote add origin git@github.com:{group}/TaxiFareModel.git
git push -u origin master
git push -u origin --tags
Functionnal test with a script:
cd
mkdir tmp
cd tmp
TaxiFareModel-run
Go to https://github.com/{group}/TaxiFareModel
to see the project, manage issues,
setup you ssh public key, ...
Create a python3 virtualenv and activate it:
sudo apt-get install virtualenv python-pip python-dev
deactivate; virtualenv -ppython3 ~/venv ; source ~/venv/bin/activate
Clone the project and install it:
git clone git@github.com:{group}/TaxiFareModel.git
cd TaxiFareModel
pip install -r requirements.txt
make clean install test # install and test
Functionnal test with a script:
cd
mkdir tmp
cd tmp
TaxiFareModel-run