/data-science-book

Primary LanguageJupyter Notebook

Becoming a Spatial Data Scientist Materials

Example notebooks to accompany Becoming a Spatial Data Scientist.

Installation requirements

The notebooks in this repository use a ready-to-run Docker image containing Jupyter applications and interactive computing tools. To run the notebooks, please follow the instructions below.

  1. Clone this repository
$ git clone git@github.com:CartoDB/data-science-book.git
$ cd data-science-book

  1. Download and install docker. Follow instructions here: https://docs.docker.com/install/

  2. Run the image. Open your terminal and run

$ docker run --user root -p 8888:8888 -e JUPYTER_ENABLE_LAB=yes -e GRANT_SUDO=yes -v "$PWD":/home/jovyan/workspace cartodb/data-science-book

A local address will be created. Copy and paste the address in your browser, this will launch Jupyter Lab. Note: If you have another Jupyter server running, make sure it's on a different port than 8888. Otherwise change the port number above or close down the other notebook server.

  1. Start experimenting with the code in each of the Chapter directories

Table of Contents

Chapter 1 - 2

  • Visualizing spatial data with CARTOframes (static preview) - a notebook for easily visualizing your data on a map using CARTOframes.

  • Computing measures of spatial dependence (static preview) - a notebook for exploring spatial dependence in your data and visualize the results using CARTOframes.

  • Discrete spatial models (static preview) - a notebook with examples of spatial models for discrete processes and visualize the results using CARTOframes.

  • Continous spatial models (static preview) - a notebook with examples of spatial models for continuous processes and visualize the results using CARTOframes.

Chapter 3

  • Agglomerative Clustering (static preview) - a notebook demonstrating how to create spatially constrained clusters using agglomerative clustering
  • DBSCAN (static preview) - a notebook demonstrating how to create clusters of points in geographic coordinates
  • SKATER (static preview) - a notebook demonstrating how to create spatially constrained clusters that are homogeneous

Chapter 4

  • Travelling Salesman Problem (static preview) - a notebook demonstrating how to solve travelling salesman problem.