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normet: NORmalising METeorology on air quality

Project description

normet

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normet is a Python package to conduct automated data curation, automated machine learning-based meteorology/weather normalisation and causal analysis on air quality interventions for atmospheric science, air pollution and policy analysis. The main aim of this package is to provide a Swiss army knife enabling rapid automated-air quality intervention studies, and contributing to cross-disciplinary studies with public health, economics, policy, etc.

Installation

conda create -n normet jupyter
conda activate normet

This package depends on AutoML from flaml. Install FLAML first:

conda install flaml -c conda-forge

Install normet using pip:

pip install normet

Or install normet from source:

git clone https://github.com/dsncas/normet.git
cd normet/python
python setup.py install

Main Features

Here are a few of the functions that normet implemented:

  • Automated machine learning. Help to select the ‘best’ ML model for the dataset and model training.

  • Partial dependency. Look at the drivers of changes in air pollutant concentrations and feature importance.

  • Weather normalisation. Decoupling emission-related air pollutant concentrations from meteorological effects.

  • Causal inference for air quality interventions. Attribution of changes in air pollutant concentrations to air quality policy interventions.

Documentation

You can find Demo and tutorials of the functions here.

Project details


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normet-0.1.15.tar.gz (20.4 kB view hashes)

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