incognita 0.28.0

Creator: bradpython12

Last updated:

Add to Cart

Description:

incognita 0.28.0

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.

License

For personal and professional use. You cannot resell or redistribute these repositories in their original state.

Customer Reviews

There are no reviews.