/GPBP_Analytics_Tools

Geospatial Planning and Budgeting Platform

Primary LanguageJupyter NotebookMIT LicenseMIT

Geospatial Planning and Budgeting Platform

Frontline end-users and decision makers in many cases lack simple, powerful, and interactive digital decision support tools for improving public service access. The Geospatial Planning and Budgeting Platform (GPBP) empowers decision-makers at national and sub-national government level to better prioritize public infrasturcture investments in health facilities and transport networks for the greatest value for money impacts.

The Geospatial Planning and Budgeting Platform is designed as a Digital Public Good which allow users to examine key spatial layers related to facility location, road network consolidations, population distribution, administrative boundaries, risk layers (e.g., flooding), and satellite imagery.

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The platform enables descriptive analytics on different data stacks created from such varied geospatial information to perform access analytics, enable data-driven investment prioritisation, provides a platform for risk-based supervision, and support capabilities to model scenarios and prescribe interventions in an interactive and iterative data-driven and data-informed decision support platform.

This repository consists of a collection of Python Notebooks to preprocess Geospatial Data and perform descriptive and prescriptive analytics on them to feed in to the Geospatial Planning and Budgeting Platform.

Repository Structure

  • Scripts -- This section includes the python scripts and functions developed as part of GPBP

  • Analytics Notebooks -- This section includes Descriptive and Prescriptive Analytics Notebooks for Timor Leste and Vietnam

Style Guide for Python Scripts

This repository uses the PEP 8 -- Style Guide for Python Code for improving readability of the code and to maintain consistency.

Some of the key guidelines are outlined below. For details visit PEP 8 -- Style Guide for Python Code

  • Use 4 spaces per indentation level
  • Spaces are the preferred indentation method. Tabs should be used solely to remain consistent with code that is already indented with tabs. Python 3 disallows mixing the use of tabs and spaces for indentation. Python 2 code indented with a mixture of tabs and spaces should be converted to using spaces exclusively.
  • Limit all lines to a maximum of 79 characters. For flowing long blocks of text with fewer structural restrictions (docstrings or comments), the line length should be limited to 72 characters.
  • Although formulas within a paragraph always break after binary operations and relations, displayed formulas always break before binary operations
  • Surround top-level function and class definitions with two blank lines. Method definitions inside a class are surrounded by a single blank line. Extra blank lines may be used (sparingly) to separate groups of related functions. Blank lines may be omitted between a bunch of related one-liners (e.g. a set of dummy implementations).
  • Use blank lines in functions, sparingly, to indicate logical sections.

Connecting with Google Colaboratory

Google Colaboratory is designed to integrate cleanly with GitHub, allowing both loading notebooks from github and saving notebooks to github.

Colab can load public github notebooks directly, with no required authorization step. For example, consider the notebook at this address: https://github.com/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb. The direct colab link to this notebook is: https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb. To generate such links in one click, you can use the Open in Colab Chrome extension.

For detailed information on this and demos on integrating Github with Colab Click here

About the Team

The design, development and deployment of the Geospatial Planning and Budgeting Platform is led by teams at World Bank and Analytics for a Better World in collaboration with governmental, non-governmental organisations, startups and researchers from around the globe.