Dask-GeoPandas introduction tutorial

Setting up to follow the tutorial

Step 1: download the tutorial material

If you are a git user, you can get the tutorial materials by cloning this repo:

git clone https://github.com/martinfleis/dask-geopandas-tutorial.git
cd dask-geopandas-tutorial

Otherwise, to download the repository to your local machine as a zip-file, click the download ZIP on the repository page https://github.com/martinfleis/dask-geopandas-tutorial (green button "Code"). After the download, unzip on the location you prefer within your user account (e.g. My Documents, not C:\).

Step 2: install the required Python packages

To follow the tutorial, we recommend to create a conda environment to ensure you have all the required packages installed (the environment.yml file list the required packages).

If you do not yet have conda installed, you can install miniconda (https://conda.io/miniconda.html) or the (larger) Anaconda distribution (https://www.anaconda.com/download/).

Using conda, we recommend to create a new environment with all packages using the following commands (after cloning or downloading this github repo and navigating to the directory, see above):

# setting the configuation so all packages come from the conda-forge channel
conda config --add channels conda-forge
conda config --set channel_priority strict
# mamba provides a faster implementation of conda
conda install mamba
# creating the environment
mamba env create --file environment.yml
# activating the environment
conda activate geopandas-tutorial

In case you do not want to install everything and just want to try out the course material, use the environment setup by Binder and open the notebooks rightaway.

Step 3: starting Jupyter Lab

The tutorial itself is a Jupyter notebook, an interactive environment to write and run code.

In the terminal, navigate to the dask-geopandas-tutorial directory (downloaded or cloned in the previous section)

Ensure that the correct environment is activated.

conda activate geopandas-tutorial

Start a jupyter notebook server by typing

jupyter lab

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Data included:

• airports.csv from https://ourairports.com/data/
• world.parquet as a copy of naturalearth_lowres dataset from geopandas
• GADM from GADM but that is not included in the repo due to the size