Metadata-Version: 2.1
Name: demographic-modeling
Version: 0.3.0
Summary: Demographic Modeling
Home-page: UNKNOWN
Author: Joel McCune
License: Apache 2.0
Description: # demographic-modeling-module
        
        Demographic Modeling is _opinionated_ tooling for performing demographic analysis using both geography and machine 
        learning.
        
        ## Opinionated
        
        No, this set of tooling written in Python is not going to have a political debate with you. Rather, while flexible 
        enough to be used in a variety of ways, this tooling provides a clear way to perform analysis. This enables you to
        get started and be productive as quickly as possible.
        
        ## Getting Started
        
        From the project directory, create an environment with all dependencies installed and linked.
        
        ```
        > make env
        ```
        
        This creates a conda environment cloned from the ArcGIS Pro default environment `arcgispro-py3`, and names this new
        environment `demographic-modeling`, and also activates this environment for ArcGIS Pro at the same time. If opening
        a new command prompt, you can easily activate this environment using the command.. 
        
        ```
        > make env_activate
        ``` 
        
        ...which simply calls `> activate demographic-modeling` for you.
        
        From there, the example workflow can be found in the notebooks in the `./notebooks` directory of the project, and
        explored by simply calling.
        
        ```
        > make jupyter
        ```
        
        This command takes care of activating the environment, and also starting jupyter lab, so you can get started quickly.
        
        ## Project Organization
        ------------
        ```
            ├── LICENSE
            ├── Makefile           <- Makefile with commands like `make data`
            ├── make.bat           <- Windows batch file with commands like `make data`
            ├── setup.py           <- Setup script for the library (dm)
            ├── .env               <- Any environment variables here - created as part of project creation, 
            │                         but NOT syncronized with git repo for project.                
            ├── README.md          <- The top-level README for developers using this project.
            ├── arcgis             <- Root location for ArcGIS Pro project created as part of
            │   │                     data science project creation.
            │   ├── demographic-modeling-module.aprx <- ArcGIS Pro project.    
            │   └── demographic-modeling-module.tbx  <- ArcGIS Pro toolbox associated with the project.
            ├── scripts            <- Put scripts to run things here.
            ├── data
            │   ├── external       <- Data from third party sources.
            │   ├── interim        <- Intermediate data that has been transformed.
            │   │   └── interim.gdb
            │   ├── processed      <- The final, canonical data sets for modeling.
            │   │   └── processed.gdb
            │   └── raw            <- The original, immutable data dump.
            │       └── raw.gdb
            ├── docs               <- A default Sphinx project; see sphinx-doc.org for details
            ├── models             <- Trained and serialized models, model predictions, or model summaries
            ├── notebooks          <- Jupyter notebooks. Naming convention is a 2 digits (for ordering),
            │   │                     descriptive name. e.g.: 01_exploratory_analysis.ipynb
            │   └── notebook_template.ipynb
            ├── references         <- Data dictionaries, manuals, and all other explanatory materials.
            ├── reports            <- Generated analysis as HTML, PDF, LaTeX, etc.
            │   └── figures        <- Generated graphics and figures to be used in reporting
            ├── environment.yml    <- The requirements file for reproducing the analysis environment. This 
            │                         is generated by running `conda env export > environment.yml` or
            │                         `make env_export`.                         
            └── src                <- Source code for use in this project.
                └── dm <- Library containing the bulk of code used in this 
                                                          project. 
        ```
        
        <p><small>Project based on the <a target="_blank" href="https://github.com/knu2xs/cookiecutter-geoai">cookiecutter GeoAI project template</a>. This template, in turn, is simply an extension and light modification of the <a target="_blank" href="https://drivendata.github.io/cookiecutter-data-science/">cookiecutter data science project template</a>. #cookiecutterdatascience</small></p>
        
Platform: UNKNOWN
Description-Content-Type: text/markdown
