Metadata-Version: 2.1
Name: incognita
Version: 0.28.0
Summary: Mapping the annual UK Scout Census to local geographies
Home-page: https://github.com/the-scouts/incognita
Author: Adam Turner, Tom Yems
License: MIT
Keywords: API, scouts
Platform: any
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
Classifier: Topic :: Software Development
Classifier: Topic :: Utilities
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pandas
Requires-Dist: numpy
Requires-Dist: geopandas (>=0.8)
Requires-Dist: shapely
Requires-Dist: pyarrow
Requires-Dist: pygeos
Requires-Dist: toml
Requires-Dist: pydantic
Provides-Extra: web
Requires-Dist: dash ; extra == 'web'

# Incognita

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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](https://github.com/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
```shell
# conda
conda env create -n incognita_env
conda activate incognita_env
conda install --channel conda-forge geopandas
```

```shell
# 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](https://geopandas.org/getting_started/install.html).

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

- [geopandas](https://github.com/geopandas/geopandas),
  [pandas](https://github.com/pandas-dev/pandas) - for (geospatial) data
  transformation and arrangement
- [shapely](https://github.com/Toblerity/Shapely), 
  [pygeos](https://github.com/pygeos/pygeos) - for manipulation and
  analysis of geometric objects
- [dash](https://github.com/plotly/dash) - for simple web-apps

JavaScript dependencies are:
- [Leaflet.js](https://github.com/Leaflet/Leaflet) - for slippy maps
- [chroma.js](https://github.com/gka/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](https://geoportal.statistics.gov.uk/search?collection=Dataset&sort=-modified&tags=ons%20postcode%20directory)

### 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](https://geoportal.statistics.gov.uk/search?collection=Dataset&sort=-modified&tags=bdy_lad)
 * [Counties and Unitary Authorities Boundaries UK BGC](https://geoportal.statistics.gov.uk/search?collection=Dataset&sort=-modified&tags=BDY_CTYUA)
 * [Wards Generalised Clipped Boundaries UK](https://geoportal.statistics.gov.uk/search?collection=Dataset&sort=-modified&tags=BDY_WD)
 * [Westminster Parliamentary Constituencies UK BGC](https://geoportal.statistics.gov.uk/search?collection=Dataset&sort=-modified&tags=BDY_PCON)

#### Census Geographies:
##### England and Wales:
 * [Lower Layer Super Output Areas](https://geoportal.statistics.gov.uk/search?collection=Dataset&sort=-modified&tags=BDY_LSOA%2CDEC_2011)
 * [Middle Layer Super Output Areas](https://geoportal.statistics.gov.uk/search?collection=Dataset&sort=-modified&tags=BDY_MSOA)
##### Scotland:
 * Data Zones
 * [Intermediate Geographies](https://data.gov.uk/dataset/133d4983-c57d-4ded-bc59-390c962ea280/intermediate-zone-boundaries-2011)
##### Northern Ireland:

### Single year of age profiles:
#### Westminster Parliamentary Constituencies:
 * [England and Wales](https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationestimates/datasets/parliamentaryconstituencymidyearpopulationestimates)
 * [Northern Ireland](https://www.nisra.gov.uk/publications/2018-mid-year-population-estimates-northern-ireland)
 * [Scotland](https://www.nrscotland.gov.uk/statistics-and-data/statistics/statistics-by-theme/population/population-estimates/2011-based-special-area-population-estimates/ukpc-population-estimates)

### Other useful data sources
 * [School locations](https://get-information-schools.service.gov.uk)

### Guide:
The 
[Beginner's Guide to UK Geography](https://geoportal.statistics.gov.uk/search?collection=Document&sort=name&tags=DOC_BGG)
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](https://github.com/the-scouts/incognita) and is
licensed under the **[MIT license](https://choosealicense.com/licenses/mit)**.



