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Is a project of Hack for LA.
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Helps people look for nearby street parking with the least probability of getting citations.
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Please review LUCKY PARKING_ONBOARDING READ-ME.docx for quick on-board.
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Please review LA Street Curb Parking Citation Study & Prediction.docx for project scope of work.
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Have Jupyter Notebook or Google Colab installed on your computer.
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Have GitHub account and joined hackforla on GitHub.
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Go over GitHub "Branch" workflow created by team member.
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Go over GitHub "Fork" Workflow created by team member.
We will need Python 3.x and pip, the Python Package Installer to run the code in this project.
See directions for installing Python on Windows. https://docs.python.org/3.7/using/windows.html
Use Homebrew to install Python on Mac.
Once you have Python 3 installed, create a new virtual environment to hold your dependencies and activate it:
python3 -m venv ~/.virtualenvs/lucky-parking
source ~/.virtualenvs/lucky-parking/bin/activate
Once the virtual environment is active, navigate to the project folder and install the project dependencies:
pip install -r requirements.txt
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For full entry of citation data from 2015 to 2019. Click Here to download.
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For simplified citation data and other related datasets, clone the repo and find them in "data" folder
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For fetching data directly from city API, please go to https://dev.socrata.com/foundry/data.lacity.org/wjz9-h9np