Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/matteofasulo/paris-euler

Euler Team - Social Network Analysis of Paris Transportation
https://github.com/matteofasulo/paris-euler

data-science jupyter-notebook map matplotlib network-analysis networkx openstreetmap pandas python social-network-analysis transport

Last synced: about 8 hours ago
JSON representation

Euler Team - Social Network Analysis of Paris Transportation

Awesome Lists containing this project

README 

        
# Multiplex Network Analysis Public Transportation

## University Project

Social Network Analysis Project



### Paper

The paper associated to this project is available [here](https://github.com/MatteoFasulo/Paris-Euler/blob/main/Multiplex_Network_Analysis.pdf)



### Multiplex Class

The `Multiplex` Class written in python is a nx.Graph wrapper for creating multi-layer networks and includes:

* Adding layers to a multiplex

* Linking the layers by proximity using [Haversine formula](https://en.wikipedia.org/wiki/Haversine_formula).

* Writing networks back to NetworkX

* Summarizing a multilayer network



### Maps

* [Stations and roads](https://matteofasulo.github.io/Paris-Euler/maps/france.html)

* [Public transport lines](https://matteofasulo.github.io/Paris-Euler/maps/france_transport.html)

> **Tip:** Our map can be modified using the draw icons in top-left corner and then exported as GeoJSON file through the `export` button



### Datasets

- The GeoJSON file is available at [ComplexNetTSP GitHub](https://github.com/ComplexNetTSP/MultilayerParis) or in `geojson` folder.

> **Error:** The file cannot be viewed since has no escape character at the end of each line. Download it.



### Libraries



| Name | Description |

| ------------- | ------------------------------ |

| [Numpy] | package for scientific computing with Python.

| [Pandas]| fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language.

| [Folium]| folium builds on the data wrangling strengths of the Python ecosystem and the mapping strengths of the Leaflet.js library.

| [Os]| this module provides a portable way of using operating system dependent functionality.

| [Json]| the json library can parse JSON from strings or files.

| [Math]| access to the mathematical functions defined by the C standard.

| [Random]| pseudo-random number generators for various distributions.

| [NetworkX]| package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.

| [PowerLaw]| package for Analysis of Heavy-Tailed Distributions

| [EmpiricalDist]| library that represents empirical distribution functions.

| [Matplotlib]| library for creating static, animated, and interactive visualizations in Python.

| [Plotly]| graphing library makes interactive, publication-quality graphs.

| [Kaleido]| cross-platform library for generating static images (e.g. png, svg, pdf, etc.) for web-based visualization libraries.

| [MPL Toolkits]| matplotlib module for 3d plots.



### Classes:                

         

| Class                   | Description                    |

| -------------------------- | ------------------------------ |

| `ParisTransportation`                       |GeoJSON preprocessing|

| `MapMaker(ParisTransportation)`              |Nodes map creation|

| `TransportMap`              |Public transport line creation + road network|

| `Multiplex`             |Thin nx.Graph wrapper for multi-layer networks|

| `LayeredNetworkGraph`             |3D plot using GraphViz of public transport networks|

----



[os]: 

[json]: 

[Numpy]: 

[Pandas]: 

[Folium]: 

[Math]: 

[Random]: 

[NetworkX]: 

[PowerLaw]: 

[EmpiricalDist]: 

[Matplotlib]: 

[Plotly]: 

[Kaleido]: 

[MPL Toolkits]: