incognita 0.27.0

Mapping the annual UK Scout Census to local geographies

Incognita

Incognita is a tool to map UK Scout data and enable geospatial analysis.

We use ONS open data to link scout areas (Groups, Districts, etc.) to UK administrative geographies.

Incognita comes from Terra Incognita, or Parts Unknown - solving the known unknowns!

Where to get it

The source code for the project is hosted on GitHub at the-scouts/incognita

We strongly recommended using conda to install Incognita, however pip can be used with a number of manual installation steps as below.

To install Incognita with Conda, run the following commands in the terminal

# conda
conda env create -n incognita_env
conda activate incognita_env
conda install --channel conda-forge geopandas

# or PyPI
pip install incognita

If installing with pip, you will need to manually install geopandas and its dependencies. Please follow below:

Installing geopandas on Windows:

We strongly recommended using conda to install Incognita.

However, to install geopandas using pip on Windows, please follow these instructions.

Dependencies

This project is written and tested in Python 3.9, and depends on:

• geopandas, pandas - for (geospatial) data transformation and arrangement
• shapely, pygeos - for manipulation and analysis of geometric objects
• dash - for simple web-apps

JavaScript dependencies are:

• Leaflet.js - for slippy maps
• chroma.js - for choropleth colour scales

Getting Started:

You will need to obtain the latest version of the ONS Postcode Directory. Note that this has some open licences attached to it.

If this is not May 2018, then you will need to create another child class of ONSPostcodeDirectory in ONS_data.py

You will need to populate the settings.json file with the appropriate file paths

Generating the data file

To generate the datafile needed for most operations, run setup_data_file.py with clean prototype extract.

You may also run setup_reduce_onspd.py to produce a smaller ONS Postcode Directory file to speed up lookup operations and reduce memory consumption.

Directory Structure:

To run Incognita locally, you will need to create a data folder as below, and populate it with the ONS Postcode Directory files and a copy of the Scout Census extract.

• data/
  • ONS_PD_DATE/
  • Scout Census Data/
    • Census Extract Files

Resources:

Postcode Directory:

• Latest ONS Postcode Directory

API endpoints:

To find API endpoints, find a geography from the below resources and click on the API Explorer tab. ``

Shapefiles:

Administrative/Electoral Geographies:

Use the same boundary resolution for each of the following (BFE, BFC, BGC, BUC)

BFE: Full Extent of the Realm; BFC: Full Extent Clipped; BGC: Generalised Clipped; BSC: Super Generalised Clipped

• Local Authority Districts Boundaries UK BGC
• Counties and Unitary Authorities Boundaries UK BGC
• Wards Generalised Clipped Boundaries UK
• Westminster Parliamentary Constituencies UK BGC

Census Geographies:

England and Wales:

• Lower Layer Super Output Areas
• Middle Layer Super Output Areas

Scotland:

• Data Zones
• Intermediate Geographies

Northern Ireland:

Single year of age profiles:

Westminster Parliamentary Constituencies:

• England and Wales
• Northern Ireland
• Scotland

Other useful data sources

• School locations

Guide:

The Beginner's Guide to UK Geography can be useful as an introduction for those new to GIS.

Branches

The heroku branch is specifically for the heroku application: http://scout-mapping.herokuapp.com. It contains a cut down requirements file to ensure that it loads into heroku correctly.

License

Incognita is naturally open source and is licensed under the MIT license.