normet is a Python and R 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.

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 setup.py install

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.

You can find Demo and tutorials of the functions here.