agrifoodpy-data

AgriFoodPy Data is a data repository and companion package to AgriFoodPy, providing easy access to curated datasets related to agriculture, food systems, environmental impacts, land use, and population. These datasets are essential for modeling, analysis, and research in sustainable food systems.

All datasets are stored in NetCDF format and loaded as xarray DataArrays or Datasets for efficient handling in Python.

Datasets

For a full list of datasets please visit

Installation

To intall AgriFoodPy Data during development:

pip install git+https://github.com/FixOurFood/agrifoodpy-data.git

For stable releases (once available), use:

pip install agrifoodpy-data

Usage

AgriFoodPy Data integrates seamlessly with AgriFoodPy to load and utilize datasets in both pipeline and interactive modes.

Interactive mode

In interactive mode, datasets are loaded as module atributes by importing them

from agrifoodpy_data.food import FAOSTAT

Alternatively, datasets can be imported using the load_dataset function of AgriFoodPy in standalone mode.

from agrifoodpy.utils.nodes import load_dataset

FAOSTAT = load_dataset(module="agrifoodpy_data.food", data_attr="FAOSTAT")

Pipeline mode

In pipeline mode, datasets can be stored in an AgriFoodPy Pipeline datablock using the load_dataset module and used in other modules further along the pipleine

import agrifoodpy as afp

pipe = afp.pipeline.Pipeline()
pipe.add_node(
    afp.utils.nodes.load_dataset,
    name="Load fbs",
    params={
        "datablock_path": "fbs",
        "module": "agrifoodpy_data.food",
        "data_attr": "FAOSTAT",
        "coords": {
            "Item": [2731, 2511],
            "Year": [2019, 2020],
            "Region": 229},
    }
)

# add more nodes to work with the loaded dataset

Contributing

Contributions are welcome! Please see the main AgriFoodPy repository for guidelines.