babakkhavari/Clustering

Script and data from: "Population cluster data to assess the urban-rural split and electrification in Sub-Saharan Africa " by Babak Khavari, Alexandros Korkovelos, Andeas Sahlberg, Francesco Fuso-Nerini and Mark Howells. # Clustering Script and data from: **Population cluster data to assess the urban-rural split and electrification in Sub-Saharan Africa** by Babak Khavari, Alexandros Korkovelos, Andeas Sahlberg, Mark Howells and Francesco Fuso Nerini. Datasets produced using the method described in the paper are available at: data.mendeley.com. ## Content This repository contains: * An environment .yml file needed for generating a fully functioning python 3.7 environment necessary for the clustering algorithm. * The clustering code and related functions. These files also contain necessary steps in order to reproduce results. * An example case for Benin. ## Installing and running the clustering notebook **Requirements** The clustering module (as well as all supporting scripts in this repo) have been developed in Python 3. We recommend installing Anaconda's free distribution as suited for your operating system. **Install the clustering repository from GitHub** After installing Anaconda you can download the repository directly or clone it to your designated local directory using: ``` > conda install git > git clone github.com ``` Once installed, open anaconda prompt and move to your local "clustering" directory using: ``` > cd ..\Clustering ``` In order to be able to run the clustering tool (main.ipynb and funcs.ipynb) you have to install all necessary packages. "full_project.yml" contains all of these and can be easily set up by creating a new virtual environment using: ``` conda env create --name clustering --file full_project.yml ``` This might take some time. When complete, activate the virtual environment using: ``` conda activate clustering ``` With the environment activated, you can now move to the clustering directory and start a "jupyter notebook" session by simply typing: ``` ..\Clustering> jupyter notebook ``` ## Changelog **5-April-2020**: Original code base published **8-Sept-2022**: Simplified th …