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The pysat team provides a variety of plug-ins to support\npublic scientific data sets in packages such as pysatNASA, pysatMadrigal, and\nmore, available as part of the general [pysat ecosystem](https://github.com/pysat).\n\nFull [Documentation](http://pysat.readthedocs.io/en/latest/index.html)\n\nJGR-Space Physics [Publication](https://doi.org/10.1029/2018JA025297)\n\nPysat Ecosystem [Publication](https://www.frontiersin.org/articles/10.3389/fspas.2023.1119775/full)\n\n[Citation Info](https://pysat.readthedocs.io/en/latest/citing.html)\n\nCome join us on Slack! An invitation to the pysat workspace is available\nin the 'About' section of the\n[pysat GitHub Repository.](https://github.com/pysat/pysat)\nDevelopment meetings are generally held fortnightly.\n\n# Main Features\n* Instrument independent analysis routines.\n* Instrument object providing an interface for downloading and analyzing a wide\n  variety of science data sets.\n  * Uses pandas or xarray for the underlying data structure;\n    capable of handling the many forms scientific measurements take in a\n    consistent manner.\n  * Standard scientific data handling tasks (e.g., identifying, downloading,\n    and loading files and cleaning and modifying data) are built into the\n    Instrument object.\n  * Supports metadata consistent with the netCDF CF-1.6 standard. Each variable\n    has a name, long name, and units. Note units are informational only.\n* Simplifies data management\n  * Iterator support for loading data by day/file/orbit, independent of data\n    storage details.\n  * Orbits are calculated on the fly from loaded data and span day breaks.\n  * Iterate over custom seasons\n* Supports rigorous time-series calculations that require spin up/down time\n  across day, orbit, and file breaks.\n* Includes helper functions to reduce the barrier in adding new science\n  instruments to pysat\n\n# Installation\n\nThe following instructions provide a guide for installing pysat and give some\nexamples on how to use the routines.\n\n## Prerequisites\n\npysat uses common Python modules, as well as modules developed by and for the\nSpace Physics community.  This module officially supports Python 3.9+.\n\n| Common modules | Community modules |\n| -------------- | ----------------- |\n| dask           | netCDF4           |\n| numpy \u003e= 1.12  |                   |\n| pandas         |                   |\n| portalocker    |                   |\n| pytest         |                   |\n| scipy          |                   |\n| toolz          |                   |\n| xarray         |                   |\n\n\n## PyPi Installation\n```\npip install pysat\n```\n\n\n## GitHub Installation\n```\ngit clone https://github.com/pysat/pysat.git\n```\n\nChange directories into the repository folder and run the pyproject.toml or\nsetup.py file.  For a local install use the \"--user\" flag after \"install\".\n\n```\ncd pysat/\npython -m build .\npip install .\n```\n\n# Using pysat\n\n* The first time pysat is run, you will need to specify a directory to store\n  the data. In Python, run:\n```\npysat.params['data_dirs'] = 'path/to/directory/that/may/or/may/not/exist'\n```\n  * Nominal organization of data is top_dir/platform/name/tag/inst_id/files\n\nDetailed examples and tutorials for using pysat are available in the\n[documentation](http://pysat.readthedocs.io/en/latest/index.html).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpysat%2Fpysat","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpysat%2Fpysat","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpysat%2Fpysat/lists"}