MobVis is an open source Python library for perform analysis about mobility data in a simple way. With this framework, it is possible to extract metrics and visualize data from different sources.

MobVis mainly uses the Pandas library for data processing, and Plotly for data visualization.

🔍 Contents

1. Documentation
2. Installation
   1. Windows installation
   2. Linux installation
3. Citing
4. Collaborators

📖 Documentation

The MobVis docs page is still under development. Until then, use this README and the docstrings in the source code to get your bearings.

🔧 Inslatation

In this section, you will be presented with a step-by-step guide on how to install the library locally. This library uses some other packages to work, which are listed below:

• pandas - 1.5.2
• scipy - 1.9.3
• plotly - 5.11.0
• kaleido - 0.2.1

Windows Instalation

The Windows Instalation guide is still under development.

Linux Instalation

To install this library on Debian Linux variants (Ubuntu, Mint, etc), simply follow the following steps:

1. Clone the repository using the command:

git clone https://github.com/lucNovais/MobVis.git

2. Create a Python virtual environment:

python3 -m venv venv

3. Start the environment:

source venv/bin/activate

4. Install the libraries necessary for MobVis to work:

pip install -r requirements.txt

5. Install MobVis locally:

pip install .

These are all the steps necessary to have an environment configured to start using MobVis. As a recommendation, I suggest carrying out developments in a Jupyter Notebook.

📰 Citing

The quotes for this project are yet to come ;)

✉️ Collaborators

Lucas Novais da Silva : lucas.novais@aluno.ufop.edu.br
Bruno Pereira dos Santos : bruno.ps@ufop.edu.br
Vinicius F. S. Mota : vinicius.mota@inf.ufes.br
Paulo H. L. Rettore : paulo.lopes.rettore@fkie.fraunhofer.de