Simago: Population simulation

Release v0.3.2.

This package can be used to generate random populations based on (publicly availabled) aggregated data.

These populations can then for example be used for experimentation in the field of machine learning or simulation studies.

The simago package is available on PyPI, the source code on Github and the documentation on ReadTheDocs. The package is released under the GPLv3 licence and tested for Python 3.7 and up.

See the changes in the changelog.

Usage

The easiest way to get started, after installing the package with pip install simago, is to use the function generate_population() from simago.population. This function creates an instance of the PopulationClass object with the generated population Pandas DataFrame as the PopulationClass.population attribute.

The population DataFrame contains a row for every person and a column for each property. The values for these properties are randomly drawn from probability distributions defined by the supplied data. This is done by supplying a settings (YAML) file, a data (CSV) file and possibly a conditions (CSV) file. For more guidance see the example in the documentation.

How to contribute

If you would like to contribute to this project, please check out the contributing guidelines.

Contents

• Example
  • Property: Sex
  • Property: Age
  • Property: Income
  • Probability and Population objects
  • Resulting data
• API Reference
  • Population
  • Probability
  • Yamlutils
• File properties
  • Settings (YAML) file
  • Data file
  • Conditions file
• How To Contribute
  • Guidelines
  • Continuous integration (CI)
• Changelog
  • v0.3.2
  • v0.3.1
  • v0.3.0

Indices and tables

• Index

• Module Index

• Search Page