incognita 0.25.3

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 dependencies with Conda, run the following commands in the terminal

# conda
conda env update
conda activate incognita

# or PyPI
pip install -r requirements.txt

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

Installing geopandas:

We strongly recommended using conda to install geopandas.

However, to install geopandas using pip on Windows, follow the following steps:

1. Download the wheels for GDAL, Fiona, and Rtree. Choose the correct platform and python version (currently 3.9).
2. Install any prerequisites listed on Gohlke's site (e.g. C++ re-distributables)
3. pip install the wheels in the following order (preferably in a Virtual Environment)
   1. GDAL
   2. Fiona
   3. Rtree
4. pip install geopandas

Dependencies

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

• geopandas, pandas - for (geospatial) data transformation and arrangement
• folium - for rendering to Leaflet.js maps
• shapely - for manipulation and analysis of geometric objects
• dash - for simple web-apps

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.

Resources:

Postcode Directory:

• Latest ONS Postcode Directory

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 (link)
• Counties and Unitary Authorities Boundaries UK BGC (link)
• Wards Generalised Clipped Boundaries UK (link)
• Westminster Parliamentary Constituencies UK BGC (link)

Census Geographies:

England and Wales:

• Lower Layer Super Output Areas (link)
• Middle Layer Super Output Areas (link)

Scotland:

• Data Zones
• Intermediate Geographies (link)

Northern Ireland:

Single year of age profiles:

Westminster Parliamentary Constituencies:

• England and Wales (link)
• Northern Ireland (link)
• Scotland (link)

Other useful data sources

• School locations: https://get-information-schools.service.gov.uk/

Guide:

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

Directory Structure:

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

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.