akorkovelos / interactive_plotting

Jupyter notebook showcasing how to generate interactive maps for key geospatial data formats using geopandas & Folium
MIT License
1 stars 1 forks source link

interactive_plotting

Jupyter notebook showcasing how to generate interactive maps for key geospatial data formats using geopandas & Folium

Content

Setting up the environment & running the model

Install from GitHub

Download repository directly or clone it to you designated local directory using:

git clone https://github.com/akorkovelos/interactive_plotting.git

Requirements

The notebook has been developed in Python 3. We recommend installing Anaconda's free distribution as suited for your operating system.

Once installed, open anaconda prompt and move to your local "interactive_plotting" directory using:

> cd ..\interactive_plotting

In order to be able to run the notebook you should either install necessary packages or the environment. You can do this using the yml file as follows:

conda env create --file inter_plot_env.yml

In case this doesn't work, you can install the necessary libraries manually (check the requirements.txt). Indicatively you may install these as follows:

**pandas** --> conda install -c anaconda pandas
**pyproj** --> conda install -c esri pyproj
**matplotlib** --> conda install -c conda-forge/label/cf202003 matplotlib
**geopandas** --> conda install -c conda-forge/label/dev geopandas
**folium** --> conda install -c conda-forge folium
**branca** --> conda install -c conda-forge branca

Once completed, you can activate the environment using the following command:

..\conda activate inter_plot_env

Finnaly, you can now move to the directory and start a "jupyter notebook" session by simply typing:

..\interactive_plotting> jupyter notebook 

Sample output

The sample output of this exersice is located in the maps directory at html. You may also find it online here.

Credits

Conceptualization & Development : Alexandros Korkovelos
Funding: The World Bank