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Schedule and Predictions for Dublin Bikes using the Dublin Bikes API, OpenWeatherMap API, Google Maps, Flask & Data Analytics using Pandas & Sklearn.

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Dublin Bikes


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View Demo (dublinbikes.ml) · Report Bug · Request Feature

Table of Contents

  1. About The Project
  2. Getting Started
  3. Usage
  4. Roadmap
  5. Contributing
  6. License
  7. Acknowledgements

About The Project

Dublin Bikes Demo

Built With

Contact

Project Link: https://github.com/manningb/dublin_bikes

Getting Started

To get a local copy up and running follow these simple steps.

Prerequisites

This is an example of how to list things you need to use the software and how to install them.

  • Python 3
  • Pip

Installation

  1. Clone the repo
    git clone https://github.com/manningb/dublin_bikes.git
  2. Install Python packages
    pip install -r requirements.txt

Usage

  • Set your current location by typing in your address into the text box and clicking 'Set Location'image

  • Get directions to the closest bike station near you using the 'Find Bike Now' & 'Find Station Now' buttonsimage

  • Get directions from one station to another using the station to station directions featureimage

  • Get an overview of current bike availability using the colored markersimage

  • View detailed statistics and predictions by station by clicking on a station's marker and clicking 'View Statistics' or by using the drop down in the navbarimage

Roadmap

See the open issues for a list of proposed features (and known issues).

Contributing

Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are greatly appreciated.

  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
  3. Commit your Changes (git commit -m 'Add some AmazingFeature')
  4. Push to the Branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

License

Distributed under the MIT License. See LICENSE for more information.

About

Schedule and Predictions for Dublin Bikes using the Dublin Bikes API, OpenWeatherMap API, Google Maps, Flask & Data Analytics using Pandas & Sklearn.

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